040404124P-Main Thesis Paper

HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE

VULNERABLE COMMUNITIES OF SELECTED AREAS OF

DHAKA CITY

MD. ZAMIL HOSSAIN MUNSHI

DEPARTMENT OF CIVIL ENGINEERING

BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY

DHAKA, BANGLADESH

DECEMBER 2011

HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE VULNERABLE

COMMUNITIES OF SELECTED AREAS OF DHAKA CITY

by

Md. Zamil Hossain Munshi

A thesis submitted to the Department of Civil Engineering,

Bangladesh University of Engineering & Technology, Dhaka

in partial fulfillment of the requirements for the degree

of

MASTER OF SCIENCE IN CIVIL ENGINEERING

DEPARTMENT OF CIVIL ENGINEERING

BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY

December 2011

ii

The thesis titled “HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE

VULNERABLE COMMUNITIES OF SELECTED AREAS OF DHAKA CITY”

submitted by Md Zamil Hossain Munshi, Roll No: 040404124 (P), Session: 2004 has

been accepted as satisfactory in partial fulfillment of the requirement for the degree

of Master of Science in Civil Engineering (Environmental) on 03 December 2011.

BOARD OF EXAMINERS

1. ----------------------------------------------------------- Dr. Md. Mafizur Rahman Chairman Professor Department of Civil Engineering BUET, Dhaka

2. ------------------------------------------------------------- Dr. Md. Mujibur Rahman Member Professor and Head (Ex-Officio) Department of Civil Engineering BUET, Dhaka

3. ------------------------------------------------------------- Dr. Md. Delwar Hossain Member Professor Department of Civil Engineering BUET, Dhaka

4. ------------------------------------------------------------- Major Muhammad Sohail-Us-Samad Member Assistant Director (External) Survey of Bangladesh, Dhaka

iii

CANDIDATE’S DECLARATION

It is hereby declared that this thesis or any part of it has not been submitted elsewhere for the award of any degree or diploma.

--------------------------------------------------- Md. Zamil Hossain Munshi

Roll No: 040404124 (P)

iv

TABLE OF CONTENTS

CERTIFICATION ii

CANDIDATE’S DECLARATION iii

TABLE OF CONTENTS iv

LIST OF TABLES ix

LIST OF FIGURES xiii

LIST OF ABBREVIATIONS xviii

ACKNOWLEDGMENTS xix

ABSTRACT xx

CHAPTER 1: INTRODUCTION 1

1.1 General 1

1.2 Rationale of the Study 2

1.3 Objectives of the Study 4

1.4 Scope of the Study 4

1.5 Limitations of the Study 5

1.6 Organization of the Thesis 6

CHAPTER 2: LITERATURE REVIEW 7

2.1 Introduction 7

2.2 The Vulnerable Community 8

2.2.1 Definition 8

2.2.2 Considerations 8

2.2.3 Estimation of Population of a Community 9

2.2.4 Performance of Community Drinking-Water System 9

2.3 Water Pollution and Related Issues 9

2.3.1 Water Pollution 9

2.3.2 Types of Pollutants, Sources and Effects 10

2.3.3 Background Level of Immunity 13

2.4 Water Quality and Standards 13

v

2.4.1 Water Quality 13

2.4.2 Water Quality Standards 13

2.5 Water Supply 15

2.5.1 Objectives of Water Supply 15

2.5.2 Pattern of Urban Water Supply for Vulnerable Group 15

2.6 Domestic Water Supply 16

2.6.1 Domestic Water and its Usage 16

2.6.2 The Links Between Water Supply, Hygiene and Disease 17

2.7 Sanitation 18

2.7.1 Definition and Objectives of Sanitation 18

2.7.2 Relationships Between Water, Sanitation, Hygiene and Diarrhoea 19

2.7.3 Relationships Between Water, Hygiene and Other Infectious Diseases

21

2.7.4 Quantity and Accessibility 21

2.7.5 Hazards of Water Supply 22

2.8 Dhaka and Its Water Supply System 23

2.8.1 Growth of Dhaka 23

2.8.2 Dhaka Water Supply and Sewerage Authority (DWASA) 24

2.8.3 Water Supply Situation 26

2.8.4 Water Quality Monitoring System 27

2.9 Economic Valuation of Diseases 28

2.9.1 General 28

2.9.2 Importance of Monetary Valuation 28

2.9.3 The Major Economic Impacts of Pollution 29

2.9.4 Techniques to Place Monetary Values on Environmental Impacts 29

2.10 Prevalence Rate (PR) 30

2.10.1 Importance 30

2.10.2 Formula Used in PR 31

2.11 Statistical Analysis Tools 31

2.11.1 Arithmetic Mean 31

2.11.2 Grade Point Average (GPA) 32

2.11.3 Standard Deviation 32

vi

2.11.4 Correlation Coefficient (Cr) 32

CHAPTER 2: METHODOLOGIES 33

3.1 Introduction 33

3.2 Methodologies 33

3.3 Design Procedure 35

3.3.1 Selection of Vulnerable Communities 37

3.3.2 Vulnerability Score 37

3.3.3 Identification of Urban Water Supply Options 38

3.3.4 Field Survey 38

3.3.5 Economic Valuation of Diseases 45

3.3.6 Prevalence Rate (PR) 47

3.3.7 Climatic factors 48

CHAPTER 4: ANALYSIS OF DATA 49

4.1 Introduction 49

4.2 Data Availability in Bangladesh 49

4.3 Selection of Data 49

4.3.1 Yearly Records 50

4.3.2 Monthly Records 53

4.3.3 Meteorological Data 53

4.4 Analysis of Field Data 57

4.4.1 Questionnaires Survey- An Overview 57

4.4.2 Qualitative Assessment 58

4.4.3 Quantitative Assessment 69

4.4.4 Economic Valuation of Diseases 77

4.4.5 Analysis of Prevalence Rate 79

4.5 Development of Correlation Between Diarrhoea Patient Reporting Cases and Climatic Factors

81

4.5.1 Identification of Correlation 81

4.5.2 Development of Correlation Equation 84

CHAPTER 5: RESULTS AND DISCUSSIONS 87

5.1 Introduction 87

5.2 Qualitative Assessment

87

vii

5.2.1 Urban Water Supply Options 87

5.2.2 Distance of Water Source and Time Require to Fetch Water

89

5.2.3 Quantity and Accessibility to Water 90

5.2.4 Water Boiling Practices 92

5.2.5 Storage of Water 93

5.2.6 Sanitation Systems 95

5.2.7 Hygiene Practices-Use of Hand Wash Medium 96

5.2.8 Water Quality of Collected Samples 98

5.2.9 Sanitary Inspection (SI) 101

5.3 Quantitative Assessment 104

5.3.1 Overall Evaluation on Health Impacts 107

5.4 Evaluation on Estimated Health Impact Valuation of Waterborne Diseases 117

5.5 Evaluation of Prevalence Rate 118

5.6 Correlation Between Diarrhoea Patient Reporting Cases and Climatic Factors

121

5.7 GIS Representation of Relevant Data in Thematic Maps

123

CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS 124

6.1 Conclusions 124

6.2 Recommendations

130

REFERENCES 131

APPENDICES

Appendix A Questionnaires Survey Form 135

Appendix B Sanitary Inspection Forms 139

Appendix C 15 Years (1996-2010) Averaged Diarroheal Patients Reported

142

Appendix D 11 Years Monthly Average (2000-2010) Diarrhoeal Patients Reported 143

viii

Appendix E Thana wise Estimated Population of Dhaka City for the Year of 2010 144

Appendix F Data of Selected Climatic Factors for Dhaka Station 145

Appendix G Relevant Data From Questionnaires Survey 146

Appendix H Analysis of Sanitary Inspection (SI) Data 148

Appendix I Analysis of Water Quality of Selected Areas 152

Appendix J Overall Grading Based on Vulnerability Scores 155

Appendix K Estimated Health Impact Valuation of Waterborne Diseases of Dhaka City 158

Appendix L Calculation of Prevalence Rate of Waterborne Diseases of Selected Areas of Dhaka City 160

Appendix M Correlation Between Diarrhoeal Incidences and Climatic Factors 164

Appendix N Criteria Wise Health Impacts of the Selected Communities, Areas and Urban Water Supply Options 168

Appendix O Thematic Maps of Dhaka City 192

ix

LIST OF TABLES

Table 2.1 Heavy Metal Concentration in River Water of Dhaka City 11

Table 2.2 Concentration of Water Quality Indicators of Lake Water of

Dhaka City 11

Table 2.3 Bangladesh Water Quality Standards For Surface Water

For Water Supply 14

Table 2.4 Bangladesh Standard For Drinking Water 14

Table 2.5 Volumes of Water Required For Hydration For the Most

Vulnerable in Tropical Climates 19

Table 2.6 Infrastructures and Establishment of DWASA 28

Table 2.7 Source Wise Water Production of DWASA in October 2009 29

Table 3.1 Vulnerability Score and State of Vulnerability 37

Table 3.2 Basic Data for Grading and Representation 38

Table 3.3 The Water Supply Options Found in the Study Areas 38

Table 3.4 Data Filtering Process: Step-1 41

Table 3.5 Data Filtering Process for Diarrhoea: Step-2a 42

Table 3.6 Data Filtering Process for Typhoid: Step-2b 42

Table 3.7 Data Filtering Process for Eye Infections: Step-2c 43

Table 3.8 Final Result of Data Filtering Process 43

Table 3.9 Criteria Used For Grading the SI Risk Scores 44

Table 3.10 List of Laboratory Tests For Collected Water Samples 45

Table 3.11 Calculation of Hourly Average Wage Rate 46

Table 4.1 Generalized Population of Administrative Areas of Dhaka

City Reporting ICDDR, B in 2010 52

Table 4.2 Selected Thana Wise Different Age Groups Patients 52

Table 4.3 At a Glance of Dhaka City Climate 53

Table 4.4 Sample Area Wise Distribution of Interviewed HHs and Exposed Population

58

Table 4.5 Age Group Wise Distribution of Interviewed Communities 58

x

Table 4.6 Distribution of number of HHs to Urban Water Supply

Options As Per Community Type And Connection Sources 59

Table 4.7 Distribution of Selected Area Wise Observed Water Points

To Urban Water Supply Options 61

Table 4.8 Distribution of Community Wise Observed Water Points to

Urban Water Supply Options 61

Table 4.9 Distribution of number of HHs Residing At Different

Distances From Water Sources. 61

Table 4.10 Distribution of Community Wise HHs Against Water Fetch

Time

62

Table 4.11 Distribution of Number of HHs Against Water Demand and

Water Sources' Connections 62

Table 4.12 Distribution of Community Wise Number of HHs Against

Water Demand and Urban Water Supply Options 63

Table 4.13 Sample Area Wise Number of HHs Reporting Occasional

Aesthetic Quality of Water 63

Table 4.14 Distribution of HHs of Different Community Types Against

Water Boiling Practices and Urban Water Supply Options 64

Table 4.15 Distribution of HHs Against Water Boiling Duration and

Urban Water Supply Options 64

Table 4.16 Distribution of HHs of Different Community With Respect to

Water Storage System at HH Level. 65

Table 4.17 Distribution of HHs of Different Selected Areas With

Respect to Water Storage System at HH Level. 65

Table 4.18 Distribution of HHs of Different Urban Water Supply System

With Respect to Water Storage System at HH Level. 65

Table 4.19 Sample Area Wise Distribution of HHs of Different

Communities Having Different Sanitation Systems 65

Table 4.20 Sample Area Wise Distribution of HHs of Different

Communities Showing Hand Washing Practices 66

Table 4.21 Area Wise Number of Samples of Different Faecal Coliform

Concentration 67

Table 4.22 Community Wise Number of Samples of Different Faecal

Coliform Concentration 67

Table 4.23 Urban Water Supply Option Wise Number of Samples of 67

xi

Different Faecal Coliform Concentration

Table 4.24 Area Wise Distribution of Number of Water Points As Per Risk Grade

68

Table 4.25 Community Wise Distribution of Number of Water Points As

Per Risk Grade 68

Table 4.26 Urban Supply Options Wise Distribution of Number of

Water Points As Per Risk Grade 68

Table 4.27 Gender Wise Overall Incidences of Waterborne Diseases

of Different Age Groups 69

Table 4.28 Sample Areas Wise State of Waterborne Diseases’

Incidences of Different Gender 69

Table 4.29 Community Wise State of Waterborne Diseases’

Incidences 70

Table 4.30 Community Wise Waterborne Diseases’ Incidences With

Respect to Water Sources’ Connections 71

Table 4.31 Waterborne Diseases’ Incidences With Respect to Urban

Water Supply Options 71

Table 4.32 Community Wise Waterborne Diseases’ Incidences With

Respect to Urban Water Supply Options 72

Table 4.33 Waterborne Diseases’ Incidences With Respect to Distance

Between HH and Source 73

Table 4.34 Waterborne Diseases’ Incidences With Respect to Time

Taken to Fetch Water From Source 73

Table 4.35 Waterborne Diseases’ Incidences With Respect to Water

Received Against Demand 74

Table 4.36 Waterborne Diseases’ Incidences With Respect to Boiling

of Water. 74

Table 4.37 Waterborne Diseases’ Incidences With Respect to Time

Spent For Boiling of Water. 75

Table 4.38 Waterborne Diseases’ Incidences With Respect to Storage

of Water.

75

Table 4.39 Waterborne Diseases’ Incidences With Respect to Sanitary Practices.

76

Table 4.40 Waterborne Diseases’ Incidences With Respect to Hand

Wash Media. 76

xii

Table 4.41 Overall Health Impacts Based on Water Quality (FC Concentration)

77

Table 4.42 Waterborne Diseases’ Incidences With Respect to Risk

Grade. 77

Table 4.43 Cost of Waterborne Disease- Diarrhoea 78

Table 4.44 Cost of Waterborne Disease- Typhoid 78

Table 4.45 Cost of Waterborne Disease- Eye infections 79

Table 4.46 Basic Data For Prevalence Rate of Different Age-Groups 79

Table 4.47 Basic Data For Prevalence Rate of Different Community 80

Table 4.48 Basic Data For Prevalence Rate of Different Selected

Areas 80

Table 4.49 Basic Data For Prevalence Rate of Different Urban Water

Supply Options 80

Table 4.50 Correlation Coefficient of Climatic Parameters and

Diarrhoeal Incidences of the Selected Areas 84

Table 4.51 Selection of Correlation Equation Based on Correlation

Coefficients 85

Table 5.1 Number of Likely and Actual Diarrhoeal Incidences With

Respect to Temperature 122

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LIST OF FIGURES

Figure 2.1 Disease Transmission and Sanitation 19

Figure 2.2 Interrelationship between Water, Sanitation and Health Education

20

Figure 2.3 Graph of Travel Time (In Minutes) Versus Consumption 22

Figure 2.4 Generic Flow Diagram of Water Supply System 23

Figure 2.5 DWASA Service Areas in DMPA 25

Figure 2.6 Prediction of Population and Water Demand in Dhaka City 27

Figure 3.1 Methodology Diagram 34

Figure 3.2 Slums of Dhaka Metropolitan Area 36

Figure 4.1 Yearly Trends of Waterborne Disease’s Patients of Dhaka City 50

Figure 4.2 Children Patients Reporting DSH During 2005-06. 51

Figure 4.3 General Trend of Patients of Waterborne Diseases 53

Figure 4.4 Variations of Annual Rainfall of Dhaka city 54

Figure 4.5 Trend of Rainfall of Dhaka City 54

Figure 4.6 Variations of Average Annual Temperature of Dhaka city 55

Figure 4.7 Trend of Temperature of Dhaka city 55

Figure 4.8 Variations of Average Annual Humidity of Dhaka city 56

Figure 4.9 Trend of Average Annual Humidity of Dhaka city 56

Figure 4.10 Distribution of Population by Number of Person per HH 57

Figure 4.11 Sample Areas Wise Different Distance Range Between Households and Water Sources.

62

Figure 4.12 Trend of Diarrhoeal Patients of Sample Area and Dhaka 81

Figure 4.13 Diarrhoeal Patients of Sample Area and Average Rainfall 82

Figure 4.14 Diarrhoeal Patients of Sample Area and Average Temperature 82

Figure 4.15 Diarrhoeal Patients of Sample Area and Average Humidity 82

Figure 4.16 Diarrhoeal Patients-Rainfall Correlation (2000-2010) 83

xiv

Figure 4.17 Diarrhoeal Patients-Temperature Correlation (2000-2010) 83

Figure 4.18 Diarrhoeal Patients-Humidity Correlation (2000-2010) 84

Figure 4.19 Average Diarrhoeal Patients-Temperature Correlation for Study Areas and Dhaka as a Whole (2000-2010)

85

Figure 5.1 Overall State of Different Water Supply Options 88

Figure 5.2 Community wise State of Different Water Supply Options 88

Figure 5.3 Community Wise Different Distance Range Between Households and Water Source.

89

Figure 5.4 Urban Water Supply Options Wise Different Distance Range Between Households and Water Source.

90

Figure 5.5 Overall State of Different Distance Range Between Households

and Water Source. 90

Figure 5.6 State of Different Water Demand Against Community Type 91

Figure 5.7 State of Different Water Demand Against Urban Water Supply Options

91

Figure 5.8 Overall State of Different Water Demand Fulfillment 91

Figure 5.9 Community Wise Percentages of HHs Having Water Boiling Practices

92

Figure 5.10 Sample Area Wise State of Water Boiling Practices by HHs.

93

Figure 5.11 Overall State of Water Boiling Practices Observed in the Study Area

93

Figure 5.12 Overall state of Different Water Storage System 94

Figure 5.13 Community Wise Number of HHs for Different Water Storage System

94

Figure 5.14 Sample Area Wise Number of HHs for Different Water Storage

System 95

Figure 5.15 Distribution of HHs According to Sample Area Based on

Sanitation System in Use. 95

Figure 5.16 Overall State of Sanitary Practices in the Sample Area. 96

Figure 5.17 Overall State of Hygiene Practices 97

Figure 5.18 Community Wise Distribution of HHs Based on Hand Wash Media.

97

Figure 5.19 Sample Area Wise Distribution of HHs Based on Hand Wash Medium.

97

xv

Figure 5.20 Community Wise Percentages Of Households Reporting the

Aesthetic Quality of Water. 98

Figure 5.21 Overall State of Aesthetic Quality of Water of Study Area 99

Figure 5.22 pH Distribution of The Water Sample of Different Communities 99

Figure 5.23 pH Distribution Of The Water Sample Of Different Areas. 100

Figure 5.24 Microbial Water Qualities of Water Supply in Different Communities.

101

Figure 5.25 State of Overall SI Risk Grading of Water points of Study Area 101

Figure 5.26 Comparative State of Communities Based on SI Risk Grading. 102

Figure 5.27 Overall State of Communities Based on SI Risk Grading. 102

Figure 5.28 Comparative State of Vulnerable Areas Based on SI Risk Grading.

102

Figure 5.29 Overall State of Selected Areas based on SI Risk Grading. 103

Figure 5.30 Comparative State of Urban Water Supply Options Based on SI

Risk Grading. 103

Figure 5.31 Overall State of Urban Water Supply Options based on SI Risk Grading.

104

Figure 5.32 Overall State of Waterborne Diseases of Interviewed Households 104

Figure 5.33 Gender Distributions of the Affected Persons 105

Figure 5.34 Comparison between Male and Female Diarrhoeal Incidences 105

Figure 5.35 State of Different Gender Age-Groups for Waterborne diseases 106

Figure 5.36 Overall Vulnerability of Communities 107

Figure 5.37 State of Vulnerability of Communities Based on Diarrhoea Incidences

108

Figure 5.38 Correlation Between Demand And Number of Diarhoea

Incidences. 108

Figure 5.39 Correlation between FC Count and Diarrhoea Incidences in Percentage.

109

Figure 5.40 State of Vulnerability of Communities Based on Typhoid Incidences

109

Figure 5.41 State of Vulnerability of Communities Based on Eye Infections’ Incidences

110

xvi

Figure 5.42 Correlation Between SI Risk Score and Percentage of Eye Infections’ Incidences Against Exposures.

110

Figure 5.43 The Order of Community Based on Cumulative Vulnerability

Scores 111

Figure 5.44 Overall Vulnerability of Selected Areas of Dhaka City 111

Figure 5.45 State of Vulnerability of Selected Areas Based on Diarrhoea

Incidences 112

Figure 5.46 State of Vulnerability of Selected Areas Based on Typhoid

Incidences 113

Figure 5.47 State of Vulnerability of Selected Areas Based on Eye Infections

Incidences 113

Figure 5.48 The Order of Selected Areas Based on Cumulative Vulnerability

Scores 114

Figure 5.49 Overall Vulnerability of Urban Water Supply Options 114

Figure 5.50 State of Vulnerability of Urban Water Supply Options Based on

Diarrhoea Incidences

115


Typhoid Incidences

115


Eye Infections Incidences. 116

Figure 5.53 The Order of Urban Water Supply System Options Based on

Cumulative Vulnerability Scores

116

Figure 5.54 Comparison Between the Cost of Non-Reporting Waterborne

Diseases, GDP at Current Price and GDP at Constant Price (2009-10).

118

Figure 5.55 Prevalence Rate of Waterborne Diseases. 118

Figure 5.56 The State of PR Values of Different Genders 119

Figure 5.57 The State of PR Values of Different Age-Groups of Different

Genders Suffering From Diarrhoea. 119

Figure 5.58 The State of PR Values of Different Age-Groups of Different Genders Suffering From Typhoid

120

Figure 5.59 The State of PR Values of Different Age-Groups of Different

Genders Suffering From Eye Infections

120

xvii

Figure 5.60 Projected Average Diarrhoeal Patients of Study Areas Based on Temperature

121

Figure 5.61 Projected Average Diarrhoeal Patients of Dhaka Based on

Temperature

121

Figure 5.62 Average Maximum Temperature Profile at Different Time Range 122

xviii

LIST OF ABBREVIATIONS

BBS Bangladesh Bureau of Statistics

BCAS Bangladesh Centre for Advanced Studies

BMD Bangladesh Meteorological Department

BOD Biochemical Oxygen Demand

CBO Community Based Organization

CUS Centre for Urban Studies

DALY Disability Adjusted Life Year

DCC Dhaka City Corporation

DMA Dhaka Metropolitan Area

DO Dissolved Oxygen

DOE Department of Environment

DSH Dhaka Shishu Hospital

DWASA Dhaka Water Supply and Sewerage Authority

ECA Environmental Conservation Act

ECR Environment Conservation Rules

EPA Environmental Protection Agency (USA)

EQS Environmental Quality Standard

FC Faecal Coliform

GIS Geographical Information System

HH Household

ICDDR,B International Centre for Diarrhoeal Disease Research,

Bangladesh

IPH Institute of Public Health

ITN-BUET International Training Network Centre, BUET

LGED Local Government Engineering Department

MLD Million Litre per Day

STW Shallow Tubewell

TDS Total Dissolved Solid

UNDP United Nations Development Programme

UNICEF United Nations Children's Fund

UNEP United Nations Environment Programme

WHO World Health Organization

WTP Willingness to pay

xix

ACKNOWLEDGMENTS

The author wishes to express sincere gratitude to his Supervisor Dr. Md. Mafizur Rahman for his continued guidance and encouragement throughout the whole period of the thesis work. His careful guidance, constructive suggestions immensely contributed to the improvement of this thesis paper.

The author is indebted to Dr. A.S.G. Faruque, Scientist,CSD and Md. Abdul Malek, Data Manager,CSD of International Centre for Diarrhoeal Research, Bangladesh (ICDDR,B), Dr Mizanur Rahman of Dhaka Shishu Hospital(DSH) for their enormous support in providing necessary data. The author acknowledges the contributions of members of DOE, BMD, DCC, SOB etc for their support in regard to various data.

The author acknowledges the sacrifice of his family members notably his wife, Papia for all her assistance and encouragement.

Last but not the least, the author expresses his gratitude and appreciation to the members of the Examination Board.

xx

ABSTRACT Water plays a vital role to shape up the health quality of dwellers of Dhaka city. Quite a large number of people are usually affected by waterborne diseases in each year and various studies reveal that due to presence of high percentage of low-income and slum communities in the capital, the high rates of diarrhoeal incidences mostly come from these vulnerable communities who lack of adequate water, sanitation and knowledge on personal hygiene. This study identifies the vulnerable community composed of people (73%) mainly from other districts coming for economic reason. A bimodal distribution of diarrhoeal incidences especially before rainy season (March-May) and during rainy season (July-October) has been observed from these communities.

It is seen that maximum number of HHs (65%) of vulnerable communities had their supplied water of DWASA through private connections and the rest 35% had their supplied water of DWASA through public connections. A high percentage of diarrhoeal (74%), typhoid (60%) and eye infections (77%) incidences in case of private connections were reported. Majority of vulnerable communities’ HHs (47%) were having urban water supply options like “Hand pump connected to supply line”, 38% of HHs were having “Piped water supply without reservoir” and rest 15% HHs were having “Piped water supply with reservoir”. So it was about 85% (47%+38%) of the total HHs those were to rely on unsecured water supply. On the other hand, 95% of HHs never had their demand fulfilled out of which only 55% could mitigate their daily need by just half of their demand. Only 5% showed their fulfillment of their demand as per as water availability are concerned. Overall 68% of HHs did not boil water for drinking purpose and slum do not boil water just for economic reason. The slum community had more pit latrine system (64%) where low-income community based on septic tank system (67%).83% of slum HHs did not use any media to wash their hands following defecation, on the contrary 100% low-income HHs were found very much aware about use of media (in this case soap).

Samples of water from WASA pumps showed the quality of water was quite acceptable as per Bangladesh Standard but the water samples from user ends showed high contamination of water with faecal coliform. It was observed that most of the private connections (mainly slum community) were made with leaky pipes drawn over the waste and wet lands. Moreover maximum water points were in very close proximity to latrines or poorly maintained.

About 58%, 23% and 56% of HH members were suffering from diarrhoea, typhoid and eye infections respectively. It was seen that male were more vulnerable to the waterborne diseases than those of female. It was also seen that female children <5 years(10%) suffer from diarrhoea just double than male percentage (5%). Gender differences could be one of the reasons.

Overall vulnerability of communities indicate that slum had higher combined vulnerability scores for diarrhoea (CVSdiarrhoea = 5.86) and eye infections (CVSeye

infections = 6.67) than those of low-income community and overall vulnerability of selected areas indicate that the slum and low-income communities of Gulshan area are the most vulnerable, followed by the slum and low-income communities of Tejgaon, Mirpur and Badda.

xxi

This study found that for each non-reported diarrhoea incidence remained on average for 5.03 days with standard deviation of 2.02 days. The direct, indirect and total costs were Tk. 759, Tk. 762 and Tk. 1522 respectively. Again each typhoid incidence remained on average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and total costs were about Tk. 3621, Tk. 1361 and Tk. 4982.68 respectively. Finally eye infections’ incidence remains on average for 6.3 days with standard deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 712 and Tk. 917 respectively. The total cost of diseases for selected areas for one year could be from 87,138,383 Tk. to 149,892,036 Tk. and for slum areas of whole Dhaka city is 5,653,819,098Tk. or 81,726,209 USD. This huge amount of money is generally expended by these groups and might remain unnoticed or not considered during city planning or any national development plan. The prevalence rate (PR) reveals that vulnerable people are more susceptible to the diarrhoea (PRdiarrhoea = 480.95) than those of eye infections PReye infections = 309.52 and typhoid (PRtyphoid = 47.62). This study identifies an exponential correlation between numbers of diarrhoea incidences of reporting cases with temperature of Dhaka city. Moreover it also has identified a negative correlation between the demands of water with the number of non-reporting diarrhoea incidences.

1

CHAPTER 1

INTRODUCTION

1.1. General

Water is one of the five essentials (air, water, food, heat and light) for the human

beings, without which life cannot be sustained for longer period. Over 70% of the

earth's surface is water. However, most of it i.e. 98% is salt water and only 2% of

the earth's water is fresh water that we can drink. Water is the basis of all life forms

even including our body. Our muscles that move our body are 75% water; our blood

that transports nutrients is 82% water; our lungs that provide oxygen are 90% water;

our brain that is the control center of our body is 76% water; even our bones are

25% water (Batmanghelidj, 2008). It is undoubtedly the most precious natural

resource that exists on our planet without this seemingly invaluable compound, life

on earth would not be in existence. It is essential for everything on our planet to

grow and prosper. Although we as human recognize this fact but we disregard it by

polluting our lakes, rivers and oceans by throwing industrial effluents, municipal

waste, agricultural waste, sewage disposal, etc. Subsequently, we are slowly but

surely harming our planet to the point of no return! As we understand that our health

is truly dependent on the quality and quantity of the water we drink. Hence any

deficiency either of it is going to have a negative effect on our health. That is why

safe, adequate and accessible supplies of water, combined with proper sanitation,

are basic needs and essential components of primary health care. The larger the

quantity and the better the quality of water, the more rapid and extensive is the

advancement of the public health (Ahmed and Rahman, 2000). Pollution of

freshwater (drinking water) is a problem for about half of the world's population.

Each year there are about 250 million cases of water-related diseases, with roughly

5 to 10 million deaths (GP, 2005). Contaminated water - contaminated by feces, not

chemicals - remains one of the biggest killers worldwide. According to one recent

estimate, lack of adequate water, sanitation and hygiene is responsible for an

estimated 7 percent of all deaths and disease globally. Diarrhoea alone claims the

lives of some 2.5 million children a year (Murray and Alan, 1996). It has been noted

that the Asian rivers are the most polluted in the world. They have three times as

many bacteria from human waste as the global average and 20 times more lead

than rivers in industrialized countries (GP, 2005). On the contrary Bangladesh has

some of the most polluted groundwater in the world. In this case, the contaminant is

2

arsenic, which occurs naturally in the sediments. Around 85% of the total area of the

country has contaminated groundwater, with at least 1.2 million Bangladeshis

exposed to arsenic poisoning and with millions more at risk (GP, 2005). In

Bangladesh, drinking water supplies, both in urban and rural areas are often found

to contain contaminants (ITN-BUET, 2004). Access to safe drinking-water is

essential to health. It has been seen that investments in water supply and sanitation

can yield a net economic benefit, since the reductions in adverse health effects and

health care costs outweigh the costs of undertaking the interventions. Experience

has also shown that interventions in improving access to safe water favor the poor

in particular, whether in rural or urban areas and can be an effective part of poverty

alleviation strategies.

Dhaka is the capital of Bangladesh. Rapid urbanization and population growth in last

decades have changed the physical environment of Dhaka. Population of Dhaka

metropolitan area has been estimated to be 12 million and the city has grown at a

rate of 4.5 sq. km per year in the recent past (Mahmood, 2008). A recent media

report says that there are about 38% of total population of Dhaka is living in slum

areas. Again homelessness and poverty are international crisis where Bangladesh

is not an exception to this. It is being one of the poorest countries in the world; with

an estimated 3.4 million people live in some 5000 slums of its capital city, Dhaka

(Islam, 2005). But interestingly most of the time, it is the low-income groups and

people of slums are human capital greatly contributing to the economy and work

force of the capital city. The majority of them migrated to Dhaka for economic

reasons (Tiina et al., 2002), but unfortunately these peoples suffer unacceptable

levels of malnutrition, hygiene and health, deprived of essential health services,

financial stability, education and security. Dhaka has become one of the dirtiest city

of the world (Tiffany, 2008). Like other environmental factors water plays a vital role

to shape up the health quality of dwellers of Dhaka city. Quite a large number of

people is usually affected by waterborne diseases in each year and most of them

are from vulnerable groups.

1.2. Rationale of the Study

It is estimated that 88% of diarrhoeal disease is caused by unsafe water supply and

inadequate sanitation and hygiene (WHO, 2004). Lack of access to safe and

adequate water supplies contributes to ongoing poverty both through the economic

3

costs of poor health and in the high proportion of household expenditure on water

supplies in many poor communities, arising from the need to purchase water and/or

time and energy expended in collection. Access to water services forms a key

component in the UNDP Human Poverty Index for developing countries

(UNDP, 1999). Access to safe drinking water has been an important national goal in

Bangladesh. As per the WHO report, Bangladesh has already attained 97% total

water coverage and 53% total sanitation coverage with 99% urban water coverage

and 82% urban sanitation coverage during 2000 (WHO/UNICEF, 2000).

While Bangladesh has almost achieved accepted bacteriological drinking water

standards for water supply, high rates of diarrhoeal disease morbidity indicate that

pathogen transmission continues through water supply chain (and other modes)

(Hoque et al., 2006). In case of Dhaka, various studies reveal that due to presence

of high percentage of low-income and slum communities in the capital, these high

rates of diarrhoeal incidences mostly come from these vulnerable communities who

lack of adequate water, sanitation and knowledge on personal hygiene. Though it is

well understood that the adequacy of water and accessibility to those

services/facilities rest on Dhaka Water Supply and Sewerage Authority (DWASA)

who is principally responsible for the provision, operation and maintenance of water

supply, sanitation and storm water disposal services to the population of Dhaka city

as stipulated in the Water Supply and Sewerage Authority Act, 1996. But today it is

facing various challenges both for quantity and quality of supply and heading for

awkward situation due to the unplanned population growth.

To understand the exact cause of major waterborne diseases morbidity of

vulnerable communities of Dhaka city, this study has examined the quality of water

supplied by urban water supply system and information on waterborne diseases the

vulnerable communities generally suffer round the year. Both the information has

been synthesized to relate health impacts in terms of diseases‟ incidences to water

pollution, poor sanitation and bad hygiene practices. Besides, an evaluation has

also been made to quantify these economic valuations of health effects. Additionally

an attempt has been made to correlate the climatic factors with the number of

waterborne diseases‟ incidences of the selected areas of Dhaka city so as to help

decision makers aware about consequent actions to be taken. Hence this research

will provide appropriate technological and management tools to the urban planners,

4

environmentalists and policy makers to formulate control strategy to preserve water

environment of Dhaka city and take appropriate measures to minimize health

hazards on the most vulnerable group exposed to the water pollution.

1.3. Objectives of the Study

The main objectives of the study are:

Qualitative assessment of water of urban water supply system, sanitation

and hygiene practices of different vulnerable communities of the most

affected areas of Dhaka city as per as waterborne diseases are concerned.

Quantitative assessment of impacts on human health due to water pollution,

sanitation and hygiene practices and economic losses incurred for the

vulnerable communities of Dhaka city.

Evaluation of prevalence rate of specific waterborne diseases due to water

pollution, sanitation and hygiene practices by the population under

observation.

Identification of correlation between selected climatic factors and the worst

waterborne disease‟s incidence of the same selected areas of Dhaka city.

1.4. Scope of the Study

This thesis will focus on how vulnerable communities of selected administrative

areas of Dhaka city are being affected due to poor water quality, inadequate

sanitation and hygiene practices of an individual over a period of time and find out

any probability of correlation of selected climatic factors like rainfall, temperature

and humidity on the diarrhoeal incidences of the population under observation. To

carryout comprehensive study comprising all of the above features and facts require

a considerable amount of time, accessibility, economic and human resources. To

materialize those, “Convenience Sampling Method” was carried out in order to find

out the result. Though this method is non-statistical and also assumes a

homogeneous population which was not true in the practical sense. However it still

provides useful information regarding the population under observation. To augment

the thesis, apart from primary data, a substantial amount of data had also been

taken from secondary and tertiary sources. Again due to time and resource

5

constrain, identification of the most affected areas of Dhaka city as per as

waterborne diseases were concerned would be done from the data collected from

the authenticated secondary sources like International Centre for Diarrhoeal

Disease Research, Bangladesh (ICDDR,B), Dhaka Shishu Hospital(DSH) etc. Here

the four most affected areas have been selected out of twenty one administrative

areas/thanas of earlier setup. Again this paper will assume the low-income and

slums as the vulnerable community affected by desired factors. Efforts will be made

to collect all the relevant information from those areas by conducting questionnaire

survey, sanitary inspection and sample collections. In this regard, “Slums of Dhaka

Metropolitan Area” Map developed by Centre for Urban Studies (CUS) will also be

used as tertiary source in order to pin-point the areas to be explored. Since it has

also been planned to identify the correlation between waterborne diseases‟

incidences of those selected areas and climatic factors prevailing in Dhaka city.

Hence relevant and updated information on climate of Dhaka will also be collected

from Bangladesh Meteorological Department (BMD).

1.5. Limitations of the Study

This study might have following limitations:

Due to non-availability of data on new thanas from the secondary sources,

study areas have been selected based on data of earlier setup i.e. twenty

one administrative thanas of Dhaka city.

In the questionnaire survey, the respondents were found not to maintain any

kind of records at their personal level hence the information provided by

them were more or less from their memories only. They often avoid giving

out their confidential information (e.g. sanitation habit, salary etc.) too.

Since the family members of the households also have food at different

places away from houses; hence it will be difficult to pin point the problem

related with waterborne diseases only.

In questionnaire survey, the most of the respondents had confusions in

identifying cholera, diarrhoea and dysentery diseases and hence all three

have been considered as one i.e. diarrhoea.

Due to paucity of time, limited economic and as well as human resources,

Convenience Sampling Method has been conducted. Moreover it is a non-

probability sampling method and hence statistically is not significant.

6

1.6. Organization of the Thesis

This report presents the analysis, results and findings of the study in six chapters as

shown below:

Chapter 1: Introduction: This chapter contains the general background and present

status of the problem, objectives of the study, scopes of the study and the thesis

organization.

Chapter 2: Literature Review: Compiles all relevant literatures on health impacts

due to lack of adequate water, sanitation, and hygiene practices and climatic

factors.

Chapter 3: Methodologies: It describes the methodologies for this thesis starting

with selection of study areas to the display of information on the thematic map using

GIS, different statistical tools used etc.

Chapter 4: Analysis of Data: Here it provides a description of the analysis process

adopted in this study.

Chapter 5: Results and Discussions: Presents the results of the analysis

accompanied by discussions.

Chapter 6: Conclusions and Recommendations: Summarizes the whole study

and provides some guidelines for further research in this area.

7

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

Safe, adequate and accessible supplies of water, combined with proper sanitation,

are basic needs and essential components of primary health care. While man has

always recognized the importance of water for internal bodily needs, his recognition

of its importance to health is a more recent development, dating back only about a

century. Health problems related to the inadequacy of water supplies are universal

but generally of greater magnitude and significance in developing countries. While

population under water supply coverage improved significantly during the Water

Supply and Sanitation Decade and after the decade, it has been estimated about

25% of the population in developing countries still does not have access to safe

water (Ahmed and Rahman, 2000). Presently pollution of freshwater (drinking water)

is a problem for about half of the world's population. Each year there are about 250

million cases of water-related diseases, with roughly 5 to 10 million deaths

(GP, 2005). Water pollution causes number of waterborne diseases like diarrhoea,

cholera, typhoid, hepatitis etc.

There has been an extensive debate about the relative importance of water quantity,

water quality, sanitation and hygiene in protecting and improving health (Esrey et

al., 1985; Cairncross, 1990; Esrey et al., 1991). In this regard, children bear the

greatest health burden associated with poor water and sanitation. Diarrhoeal

diseases attributed to poor water supply, sanitation and hygiene account for 1.73

million deaths each year and contribute over 54 million Disability Adjusted Life

Years (DALY), a total equivalent to 3.7% of the global burden of disease (WHO,

2002). This places diarrhoeal disease due to unsafe water, sanitation and hygiene

as the 6th highest burden of disease on a global scale, a health burden that is largely

preventable (WHO, 2002). Other diseases are related to poor water, sanitation and

hygiene such as trachoma, schistosomiasis, ascariasis, trichuriasis, hookworm

disease, malaria and Japanese encephalitis and contribute to an additional burden

of disease. As of 2000 it was estimated that one-sixth of humanity (1.1 billion

people) lacked access to any form of improved water supply within 1 kilometre of

their home (WHO/UNICEF, 2000).

8

In this study, an attempt has been made to assess the health impacts on the most

vulnerable communities of Dhaka city due to limitations in access to adequate pure

water supplied by urban water supply system, sanitation and lack of adequate

knowledge on personal hygiene.

2.2 The Vulnerable Community

2.2.1 Definition

A Community consists of a group of people with common but also conflicting

interests and ideas and different socio-economic and cultural backgrounds

(Ahmed and Rahman, 2000). The identity of the people in the community is shaped

by their history and their socio-economic and environmental conditions. When the

basic services like water supply, improved sanitation, better hygiene education etc.

of a community are less or sometimes even absent- the members of that community

are likely to be vulnerable to various diseases associated with the particular issue.

2.2.2 Considerations

In this study, two socio-economic settings i.e. slum and low-income communities of

selected areas of Dhaka city have been considered:

(a) Slum: CUS (2006) has defined a slum as a neighborhood or residential

area with a minimum of 10 households or a mess unit with at least 25 members with

four of the following five conditions prevailing within it:

Predominantly poor housing.

Very high population density and room crowding.

Very poor environmental services, particularly water and sanitation facilities.

Very low socioeconomic status for the majority of residents. The key

indicator of this is Tk. 5000 per HH income per month based on the urban

poverty line per capita income estimates (Huque, 2008).

Lack of security of tenure.

9

(b) Low-income: A low-income community resides in compact settlements like

tin-shed or tin-roofing with brick walls etc. which generally grow in a cluster on

government and private vacant land having distinct service facilities offered by land

owner and having better socioeconomic condition (above upper poverty line) than

slum as stated by Huque (2008).

2.2.3 Estimation of Population of a Community

In order to analyze the health impacts of a given population of an area, there is a

requirement to calculate the population of that area. Estimation of population of a

community depends on the latest census data of that community. It is customary to

estimate the population of a community between two census periods based on last

census data by applying some conventional methods. In this study, the most widely

used Geometric Progression Method (Ahmed and Rahman, 2000) has been used to

estimate the population of administrative thanas of Dhaka city for the year of 2010

using the population data of 2001 as given in the Table E.1 of Appendix E.

Pf = Pp (1+r)n (2.1)

Where Pf = future population, Pp = present population; r = rate of yearly population

growth and n = number of years to be considered.

2.2.4 Performance of Community Drinking-Water System

If the performance of a community drinking-water system is to be properly

evaluated, a number of factors must be considered. WHO (2008) suggests for usual

practice to include the critical parameters for microbial quality (normally E. coli,

chlorine, turbidity and pH) and for a sanitary inspection to be carried out. In this

thesis, all these factors (Faecal Coliform instead of E. coli ) have been considered in

order to assess water quality of the urban water supply options.

2.3 Water Pollution and Related Issues

2.3.1 Water Pollution

Water pollution occurs when a body of water is adversely affected due to the

addition of large amounts of materials or chemicals to the water in such a way that it

becomes unfit for its intended use. Water pollution is developed by the release of

waste products and contaminants into surface runoff, into river drainage systems,

10

leaching into groundwater, liquid spills, wastewater discharges, eutrophication and

littering.

2.3.2 Types of Pollutants, Sources and Effects

(a) Types of pollutants based on sources: Two types of water pollutants exist:

Point Sources: It occurs when harmful substances are emitted directly into a

body of water. The industries located at Hazaribagh are the best illustrates

point sources water pollution.

Non-point Source: It delivers pollutants indirectly through environmental

changes. Non-point sources are much more difficult to control. Pollution

arising from non-point sources accounts for a majority of the contaminants

in streams and lakes.

(b) Major sources: The major sources of water pollution can be classified as:

Municipal: Municipal water pollution consists of waste water from homes

and commercial establishments.

Industrial: These contaminants include liquid discharges from spent water of

different industrial processes such as manufacturing and food processing.

Agricultural: Agriculture including commercial livestock and poultry farming

is the source of many organic and inorganic pollutants in surface waters and

groundwater.

(c) Causes: There are many causes as identified by DOE for which the Dhaka

city water bodies get polluted everyday (DOE, 2006):

Untreated Sewage Disposal: The existing sewage treatment plant treats

only 40,000 to 50,000 m3 of sewage while the city generates about 1.3

million m3. Most of the rest directly or indirectly reach the surrounding rivers.

The Table 2.1 shows the concentration of heavy metals above the

Environmental Quality Standard (EQS) in the surrounding rivers of Dhaka

city.

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Table 2.1: Heavy metal concentration in river water of Dhaka city

Sample ID Concentration in mg/l

Al Cd Cr Pb Hg Se Zn

Buriganga River Friendship Bridge 3.27 0.014 0.036 ND1 0.0021 0.001 0.56

Turag River:Amin Bazar 11.884 0.018 0.11 0.394 0.0058 0.0002 1.002

Buriganga River Chandni Ghat 5.396 0.006 0.006 0.25 0.0016 ND 0.984

Lakhya River: Sayedabad WTP Intake point

2.952 0.006 0.028 0.074 0.0032 0.0005 0.246

Balu River Zirani Khal 2.1166 0.006 0.0224 ND 0.0010 ND 1.122

EQS(Drinking water) 0.2 0.005 0.05 0.05 0.001 0.01 5.0

Municipal waste disposal: It is often disposed off into city water bodies. Less

than 50% of generated municipal waste is disposed in the landfill site and a

significant part of the remaining waste goes into the water bodies.

Disposal from water transport vehicles: Disposal of waste, wastewater and

petroleum products from water transport vehicles further pollute the river

water.

Agricultural activities and unsanitary practices: These are like defecating in

the water bodies lead to the contamination of nearby water bodies. The

Table 2.2 shown here is the state of water quality of lake water of Dhaka

city:

Table 2.2: Concentration of water quality indicators of lake water of Dhaka city

Name of the Lake pH

BOD (mg/l)

DO (mg/l)

TS (mg/l)

Coliforms (cfu/100ml)

Dhanmondi lake (near Russell Square)

6.95 1.9 6.1 168 600

Gulshan-Baridhara lake (Near Road No.11 )

7.10 35 0.5 302 1200

Sitadel Lake (East Side ) 6.91 2.6 6.6 92 500

Ramna Lake (beside Ramna Chinese Restaurant)

6.52 25 1.3 87 700

Crescent Lake (East side ) 5.9 2.1 8.3 98 900

EQS2 6.5-8.5 ≤ 3 5 ≥ ≤ 200

Source: DOE (2006)

1 Not detectable 2 Environmental Quality Standard (EQS) of lake water (used as recreation purposes). Five

days BOD at 200C; Coliforms in cfu/100 ml/ (24 hours incubation at 35

0C).

Source: DOE (2006)

12

Unplanned development and encroachment of water bodies: Unplanned

development and encroachment make the water bodies narrower/shorter

and lesser in depth resulting in over flooding the area with polluted water.

(d) Effects of water pollution: Water, sanitation and hygiene have important

impacts on both health and disease. Contamination of food, hands, utensils and

clothing can also play a role, particularly when domestic sanitation and hygiene are

poor. The WHO has made a fact sheet of over 20 water-related-diseases out of

which Cholera, Diarrhoea, Scabies, Schistosomiasis, Trachoma/ eye infections,

Typhoid and Paratyphoid are noteworthy for Dhaka city dwellers.

Cholera: Cholera outbreaks generally occur in any part of the city where

water supplies, sanitation, food safety and hygiene practices are

inadequate. Overcrowded communities like slum areas and other low cost

residential areas with poor sanitation and unsafe drinking-water supplies are

most frequently affected.

Diarrhoea: Water contaminated with human faeces for example from

municipal sewage, septic tanks and latrines is of special concern. Animal

faeces also contain microorganisms that can cause diarrhoea. This

happens to be a regular phenomenon in Dhaka city right after any flood

episode.

Scabies: Scabies is a contagious skin infection that spreads rapidly in

crowded conditions and is very much available in the slums. Personal

hygiene is an important preventive measure and access to adequate water

supply is important in control.

Trachoma: It is an infection of the eyes that may result in blindness after

repeated re-infections. It is the world's leading cause of preventable

blindness and occurs where people live in overcrowded conditions with

limited access to water and health care. Trachoma spreads easily from

person to person and is frequently passed from child to child and from child

to mother within the family.

http://www.who.int/water_sanitation_health/diseases/diseasefact/en/%20/entity/water_sanitation_health/diseases/schisto/en

13

Typhoid and Paratyphoid Enteric Fevers: Typhoid and paratyphoid fevers

are infections caused by bacteria which are transmitted from faeces to

ingestion.

2.3.3 Background Level of Immunity

The effects of exposure to pathogens are not the same for all individuals or, as a

consequence, for all populations. Repeated exposure to a pathogen may be

associated with a lower probability or severity of illness because of the effects of

acquired immunity. For some pathogens (e.g., HAV), immunity is lifelong, whereas

for others (e.g., Campylobacter), the protective effects may be restricted to a few

months to years. On the other hand, sensitive subgroups (e.g., the young, the

elderly, pregnant women and the immuno-compromised) in the population may have

a greater probability of illness or the illness may be more severe, including mortality.

2.4 Water Quality and Standards

2.4.1 Water Quality

Since the quality of water is affected by both man and natural activities, hence pure

water is not available in nature and however nor it is desirable for water supply.

Some of the water quality parameters respond to human senses of sight (turbidity,

color), taste (salty, offensive) and smell (odour) but the presence of pathogens and

poisons in drinking water cannot be identified by human senses. The most important

parameter of drinking water quality is the bacteriological quality, i.e. presence of

pathogenic organisms. The water borne diseases are caused by the ingestion of

pathogens with drinking water. Control of the most water-borne diseases is hinged

upon availability of enough water for domestic and personal cleanliness or sound

hygiene practices. The water-borne diseases can therefore also be described as

water-washed diseases.

2.4.2 Water Quality Standards

Water for public water supplies should be drawn from the best available source for

cost-effective treatment of water. The degree and method of treatment to make

water potable and attractive to the consumers depend on the characteristics of the

raw water. Table 2.4 shows the recommended water quality standards for surface

water sources for development of water supply in Bangladesh.

http://www.who.int/water_sanitation_health/diseases/diseasefact/en/%20/entity/water_sanitation_health/diseases/typhoid/en

14

Table 2.4: Bangladesh water quality standards for surface water for water supply.

Water Quality Parameters

Unit

Values for Water Supply by

Disinfection only Conventional

Treatment

pH - 6.5 – 8.5 6.5 – 8.5

BOD mg/l ≤ 2 ≤ 3

DO mg/l ≥ 6 ≥ 6

Total Coliform cfu/ 100 ml ≤ 50 ≤ 5,000

Source: Ahmed and Rahman (2000)

However the list of parameters presented in this table is not comprehensive; it

provides a general guideline for selection of a source for water supply. Bangladesh

developed the first water quality standards in 1976 based on the WHO 1971

International Drinking Water Standards. The Ministry of Environment and Forests,

Government of Bangladesh adopted comprehensive water quality standards for

drinking water by Gazette notification in 1997 as Environmental Conservation Rules

under the Environmental Conservation Act, 1995. Part of the Bangladesh Drinking

Water Standards, 1997 with WHO guideline values, 2004 are presented in Table

2.5.

Table 2.5: Bangladesh standard for drinking water

Aspects Parameters Bangladesh, ECR 1997,

Schedule 3(B)

WHO guideline values, 2004

Physical pH 6.5-8.5 -

TDS (mg/l) 1000 1000

Color (Hazen Unit) 15 15

Turbidity (NTU) 10 5

Odor Odorless Odorless

Chemical Hardness (as CaCO3) (mg/l) 200-500 -

Chlorine (Residual) (mg/l) 0.2 0.2

Nitrate (NO3) (mg/l) 10 50

Ammonia (mg/l) 0.5 1.5

Iron (mg/l) 0.3-1.0 0.3

Arsenic (mg/l) 0.05 0.05

Microbial TTC (cfu/ 100 ml) 0 0

Faecal Coliform (cfu/ 100 ml) 0 0

E.coli (cfu/ 100 ml) 0 0

Source: Ahmed and Rahman (2000)

15

2.5 Water Supply

2.5.1 Objectives of Water Supply

The broad objectives of any water supply system are:

Supply water in adequate quantity: means that the water supplied to the

community should meet all the requirements for water and be available when

required.

Supply safe and wholesome water to the consumers: Here water is safe

when it does not cause any harm upon consumption. Whereas the wholesome

water is unpolluted, significantly free from toxic substances as well as excessive

amounts of mineral and organic matters that may impair its quality.

Make water easily available to consumers: that the water is accessible and

within easy reach of the consumers so as to encourage the use of adequate

water for personal and household cleanliness.

2.5.2 Pattern of Urban Water Supply for Vulnerable Group

Pattern of Urban water supply pattern for vulnerable communities of Dhaka city was

found broadly in two types:

(a) Community Type DWASA Supply: These have some different patterns:

Simple house connection where all communities collect water.

Flexible pipe carrying water from nearest legal water point by illegal method.

Hand pump fitted with WASA main line and

Conventional public stand post with platform and drains. Some of them have

a reservoir to temporarily store water during non-supply hours.

(b) Shallow Tubewell (STW): Most of the time, these are installed by various

NGOs. However, during the field survey it was found that there were some slum

people who borrow water from nearby middle class community having reservoirs of

their own too.

16

2.6 Domestic Water Supply

2.6.1 Domestic Water and Its Usage

As per WHO‟s guidelines for drinking-water quality, domestic water has been

defined as being 'water used for all usual domestic purposes including consumption,

bathing and food preparation' (WHO, 2008). White et al. (1972) suggested that three

types of use could be defined in relation to normal domestic supply:

Consumption (drinking and cooking)

Hygiene (including basic needs for personal and domestic cleanliness)

Amenity use (for instance car washing, lawn watering).

Thompson et al. (2001) suggest a fourth category can be included of 'productive

use' which was of particular relevance to poor households in developing countries.

Productive use of water includes uses such as brewing, animal watering,

construction and small-scale horticulture. The first two categories identified by White

et al. (1972) i.e. „consumption‟ and „hygiene‟ have direct consequences for health

both in relation to physiological needs and in the control of diverse infectious and

non-infectious water-related disease. The third category- „amenity‟ may not directly

affect health in many circumstances. Productive water may be critical among the

urban poor in sustaining livelihoods and avoiding poverty and therefore has

considerable indirect influence on human health (Fass, 1993; Thompson et al.,

2001).

(a) Consumption: Water is a basic nutrient of the human body and is

critical to human life. It supports the digestion of food, adsorption, transportation and

use of nutrients and the elimination of toxins and wastes from the body (Kleiner,

1999). The per capita water consumption is greatly influenced by various factors.

Some major factors can be cited below:

Population Distribution

Climatic Conditions

Quality of Water

Pressure of Water

17

Water Rates and Metering

Nature of Supply

Water Source Distance

Availability of an Alternative Source

Sanitation

The volume of water required for hydration for the most vulnerable in tropical

climates as given in the Table 2.6 and higher in conditions of raised temperature

and/or excessive physical activity.

Table 2.6: Volumes of water required for hydration for the most vulnerable in tropical climates

Individual Type

Volumes (litres/day)

Average conditions

Manual labour in high temperatures

Total needs in pregnancy/lactation

Female adults

2.2 4.5 4.8 (pregnancy) 5.5 (lactation)

Male adults 2.9 4.5 -

Children l.0 4.5 -

Source: Howard and Bartram (2003)

(b) Hygiene: The need for domestic water supplies for basic health

protection exceeds the minimum required for consumption (drinking and cooking).

Additional volumes are required for maintaining food and personal hygiene through

hand and food washing, bathing and laundry. Poor hygiene may in part be caused

by a lack of sufficient quantity of domestic water supply (Cairncross and Feachem,

1993). The diseases linked to poor hygiene include diarrhoeal and other diseases

transmitted through the faecal-oral route; skin and eye diseases, in particular

trachoma and diseases related to infestations, for instance louse and tick-borne

typhus (Bradley, 1977; Cairncross and Feachem, 1993).

2.6.2 The Links Between Water Supply, Hygiene and Disease

An effective way to inform decision-making is to categorize pathogens /diseases in

relation to the broad mode of transmission. Bradley (1977) suggests that there are

four principal categories that relate to water and which are not mutually exclusive:

18

Water-borne caused through consumption of contaminated water (for

instance diarrhoeal diseases, infectious hepatitis, typhoid, guinea worm).

Water-washed caused through the use of inadequate volumes for

personal hygiene (for instance diarrhoeal disease, infectious hepatitis,

typhoid, trachoma, skin and eye infections).

Water-based- Here an intermediate aquatic host is required (for instance

guinea worm, schistosomiasis).

Water-related vector spread through insect vectors associated with water

(for instance malaria, dengue fever).

While a full analysis of improved water and sanitation services would consider

pathogens passed via all these routes, the present study focuses on water-borne

and water-washed diseases. This is partly because, at the household level, it is the

transmission of these diseases that is most closely associated with inadequate

water supply, poor sanitation and lack of hygiene. Moreover, water-borne and water-

washed diseases are responsible for the greatest proportion of the direct-effect

water and sanitation-related disease burden.

2.7 Sanitation

2.7.1 Definition and Objectives of Sanitation

The word sanitation actually refers to all conditions that affect health and according

to WHO may include things as food sanitation, rainwater drainage, solid waste

disposal and atmospheric pollution (Ahmed and Rahman, 2000). The principal

objectives of providing sanitation facilities are:

To have improved public health

To minimize environmental pollution

Sanitation can contribute greatly to preventing the spread of infectious diseases

through transmission of disease causing agents as is the case when pathogenic

organisms from the excreta of an infected person are transmitted to a healthy

person as can be seen in Figure 2.1. It is important to understand that the

improvement of health is not possible without sanitary disposal of human excreta.

However, neither sanitation nor water supply alone is good enough for health

19

improvement. It is now well established that health education or hygiene promotion

must accompany sufficient quantities of safe water and sanitary disposal of excreta

to ensure the control of water and sanitation related diseases. This interrelationship

was shown by Veenstra, (1994) during his lecture on urban sanitation as shown in

the Figure 2.2.

2.7.2 Relationships Between Water, Sanitation, Hygiene and Diarrhoea

Diseases primarily transmitted through the faecal-oral route (Figure 2.1) include

infectious diarrhoea, typhoid, cholera and infectious hepatitis. Transmission may

occur through a variety of mechanisms, including consumption of contaminated

water and food as well as through person-person contact (Bradley, 1977). These

are dealt with together here, in order to emphasize the importance of local disease

patterns rather than applying generic models. The available evidence from health

studies suggests that interventions are likely to be locality-specific and are

determined by timing and the interaction between different factors.

Figure 2.1 Disease transmissions and sanitation (Ahmed and Rahman, 2000)

Excreta

Water

Hands

Insects

Soil

New Host

Milk

Vegetable

Food

San

itatio

n F

acili

ties

Personal Hygiene

Foot wear

Sanitary Latrines

Food Sanitation TW/Water Treatment

Legend

20

Other factors apart from water and sanitation facilities and hygiene behaviors may

significantly influence diarrhoeal disease. For example breast-feeding has been

noted in several studies as being protective against diarrhoeal disease

independently of other interventions (Al-Ali et al., 1997; Vanderslice and Briscoe,

1995).

The timing of hand washing may be important. Experience suggests that the most

critical times are following defecation and before eating. Curtis et al. (2000) suggest

that the critical time is post-defecation rather than before eating, while other studies

suggest that the reverse is true in some situations (Birmingham et al., 1997).

Stanton and Clemens (1987) found reduction in diarrhoea incidence among young

children was influenced by maternal hand washing prior to food preparation. A

number of studies suggest that hand washing with soap is the critical component of

this behavior and that hand washing only with water provides little or no benefit.

Hoque et al. (1995) found that use of mud, ash and soap all achieved the same

level of cleanliness with hand washing and suggested that it is the action of rubbing

of hands that was more important than the agent used.

Health Education Or

Hygiene Promotion

Sanitation

Improvement of

Health

Water Supply

Figure 2.2 Interrelationship between water, sanitation and health education

(Veenstra, 1994)

21

2.7.3 Relationships Between Water, Hygiene and Other Infectious Diseases

Infectious diseases of the skin (a sub-set of water-washed diseases) and trachoma

are amongst the diseases on which water quantity would be expected to exert

significant influence. Trachoma is the most extensively studied disease, given its

relatively high impact on health. One study in southern Morocco that showed a

difference in incidence in trachoma between the use of less than 5 litres per day and

use of more than 10 litres per day. Prüss and Mariotti (2000) also note six studies

that showed a positive relationship between increased access to water and reduced

incidence of trachoma, with a median reduction of 27%, with a range of 11-83%

reduction. In most studies, distance from primary water source to home appears to

be the most significant water supply factor influencing trachoma.

2.7.4 Quantity and Accessibility

The WHO/UNICEF Joint Monitoring Programme has described reasonable access

as being 'the availability of at least 20 litres per person per day from a source within

one kilometre of the users dwelling' (WHO/UNICEF, 2000). However, it should be

noted that this definition relates to primarily to access and should not necessarily be

taken as evidence that 20 litres per capita per day is a recommended quantity of

water for domestic use. It is evident that increased accessibility equates to

increased volumes of water used (Esrey et al., 1991). Reviewing several studies on

water use and collection behavior, that there is a clearly defined general response of

water volumes used by households to accessibility, shown in Figure 2.3. Once the

time taken to collect water source exceeds a few minutes (typically around 5

minutes or 100m from the house), the quantities of water collected decrease

significantly. This graph contains a well-defined „plateau‟ of consumption that

appears to operate within boundaries defined by distances equivalent to around 100

to 1000m or 5 to 30 minutes collection time. There is little change in quantity of

water collected within these boundaries (Cairncross and Feachem, 1993). Beyond

distance of one kilometre or more than 30 minutes total collection time, quantities of

water will be expected to further decrease, in rural areas to a bare minimum where

only consumption needs can be met. In urban areas, where water supplies may be

close but total collection times are very high, greater volumes may be collected that

will support hygiene, although the overall impact on household poverty is significant

(Aiga and Umenai, 2002).

22

Figure 2.3: Graph of travel time (in minutes) versus consumption (WELL,1998)

As noted by WELL (1998), the first priority is to ensure that households reach the

plateau (Figure 2.3), that is to have access to an improved water source within one

kilometre, which corresponds to the current definition of reasonable access used in

assessing progress in global coverage with water supply and sanitation

(WHO/UNICEF, 2000). Beyond this, unless water is provided at a household level,

no significant changes in water quantities collected will be noted.

2.7.5 Hazards of Water Supply

From the generic flow chart of both urban water supply system and domestic water

supply system as given Figure 2.4, it can be seen that there could be number of

steps involved in exposure of pathogens to the community. The following steps

demonstrate such pathways of pathogens from sewage to consumers

(Azam, 2005):

Pathogen concentration in fresh sewage.

Mixing of sewage with drinking water through leakages, especially during low

pressure condition or interruption of supply in case of intermittent supply.

Transportation of pathogens, survival in water against the residual chlorine

level.

Addition of extra pathogens at supply end due to unsanitary condition and

unhygienic practices.

Pathogen concentration in water sources at the point of consumption.

Return trip travel time

Wa

ter

Co

nsum

ption

(lp

cd

)

23

Figure 2.4: Generic flow diagram of water supply system

Volume of un-boiled water consumed by the population, including person-to person

variation in consumption behaviour and especially consumption behaviour of at-risk

groups. Hence a kind of precaution is always taken at domestic level in terms of

treatment (boiling of water, using disinfection tablets etc.) in order to avoid such

contamination.

2.8 Dhaka and Its Water Supply System

2.8.1 Growth of Dhaka

Dhaka is the capital of Bangladesh. The present population of Dhaka city is now

about 12 million and the projected population by 2025 is about 22 million. It is now

the 7th largest city in the world and by 2020 it will be the 2nd largest city in the world

(Paul, 2009). Actually this particular city passes through various era namely pre-

Ground Water (GW) Surface Water (SW)

GW Extraction Abstraction of SW

Treatment

Disinfection

Storage

Distribution

Collection

Treatment

Storage

Usage

Consumption (drinking and cooking)

Hygiene (including basic needs for personal and domestic cleanliness)

Productive use (brewing, animal watering, construction and small-scale horticulture.)

Amenity use (for instance car washing, lawn watering).

Urban Water

Supply System

Domestic Water

Supply System

24

Mughol Era (before 1608), Mughol Era (after 1608 to 1757), under The East India

Company (1757-1858), under the British (1858-1947), as provincial capital of East

Pakistan (1947-1971) and lastly as capital of independent Bangladesh. During these

times the demographic layout of Dhaka city changed in many folds along with its

population. After the independence of Bangladesh, the urbanization activities have

been achieving tremendous growth for the needs of the newly independent

country‟s capital. The city began to expand in all directions.

On the other hand this Metropolitan City with 360 sq. km has to bear 9.3 million

people with about 6% population growth (DCC, 2009) as estimated by DCC. A water

supply Master plan for the Dhaka city was prepared in 1992 for an area of about 360

sq. km, which has now become redundant as the prediction on population and water

demand has been surpassed by huge margin (Al-Mamoon, 2006). According to the

research conducted by Population Science Division of Dhaka University, in every

year, about 7 lacs and 80 thousands of people are newly added to the existing

trends. Unfortunately the other utility services could hardly keep the pace with this

population growth. As a result environmental degradation has taken place.

2.8.2 Dhaka Water Supply and Sewerage Authority (DWASA)

(a) Brief history: Dhaka Water Supply and Sewerage Authority (DWASA) was

established for proving two major emergency services namely potable water supply

and hygienic and modern sewerage system for Dhaka, one of the rapidly expanding

city in November 1963. Under the ordinance XIX of 1963, DWASA started

functioning in Dhaka Municipality with only 8 Lac populations and now its

operational area includes both Dhaka city and Narayanganj Municipality with more

than 12.5 million people. In 1986, another important responsibility for drainage

system of Dhaka city has been shifted to DWASA. Based on the tremendous

geographical expansion and population growth over the last two decades, DWASA

has been reorganized by DWASA Act, 1996 and according to this act, presently it is

being run as a service oriented commercial organization.

(b) Responsibilities: The major responsibilities and functions of DWASA are:

Construction, operation, improvement and maintenance of the necessary

infrastructures for collecting, treating, preserving and supplying potable

water to the public, industries and commercial concerns,

25


infrastructures for collecting, treating and disposing domestic sewerage and

industrial wastes.


infrastructures for drainage facilities of the City.

According to Citizen Charter of DWASA, it provides the water connections to the

slum communities through Community Based Organization (CBO) or through land

owners subject to reception of such applications from them.

(c) Service area: At present the service area of DWASA extends from Mirpur

and Uttara in the North and to Narayanganj in the South. For better operation,

maintenance and customer care, the total service area of DWASA has been divided

into 11 geographic zones, which includes 10 in Dhaka city and 1 in Narayanganj.

Figure 2.5 shows the thematic map by each service zones of Dhaka city.

Figure 2.5 DWASA service areas in DMPA

7

1

6

2

3

5

4 8

9

10

26

(d) Infrastructures and establishment: Table 2.7 shows the data of DWASA till

October 2009:

Table 2.7 Infrastructures and establishment of DWASA

Ser No Description Acct Unit Qty

1. Water Treatment Plant Numbers 4

2. Deep Tubewell Numbers 533

3. Water production capacity MLD 2,177.91

4. Actual Water production MLD 2,032.04

5. Water Line Kilometer 2533.73

6. Water Connections Numbers 2,77,590

7. Sewer Line (2008-09) Kilometer 882

8. Sewer Connections Numbers 61,349

9. Storm Water Drainage Line Kilometer 275

10. Box Culvert Kilometer 9

11. Open Canal Kilometer 65

12. Drainage System (upto July 2004 & including box culvert and open canal)

Kilometer 303.08

Source: DWASA (2009)

2.8.3 Water Supply Situation DWASA serves a total of 14.15 million people of Dhaka Metropolitan Area and

Narayangong. This service area is projected to increase to 17.2 million by year 2025

while another 4.4 million will be staying within Dhaka Metropolitan Area but in areas

presently not served by DWASA. A sizeable number of population (estimates vary

from 10 to 60%) living in the DWASA service area are living in slum

areas (ADB, 2008). To serve such a huge population of Dhaka city is now

becoming a challenge for DWASA. Table 2.8 shows that the DWASA is heavily

dependent on groundwater with more than 87% of total water production coming

from groundwater source.

Table 2.8: Source wise water production of DWASA in October 2009.

Source Production Capacity

Actual Production Source-Wise % of Production MLD % of Capacity

Ground Water 1,878.74 1,782.37 94.87% 87.71%

Surface Water 299.17 249.67 83.45% 12.29%

Total: 2,177.91 2,032.04 93.30% 100.00%

Source: DWASA (2009)

27

But ground water depletion rate is more than 3m/yr which is alarmingly high

(Al-Mamoon, 2006; Paul, 2009). As a result no further abstraction from upper

aquifer (100-200m) is viable. However, DWASA has already started to draw water

from deep aquifer (> 300m) (DWASA, 2010). On the other hand the water quality of

peripheral rivers and lakes of Dhaka city are polluted in the highest order. Figure 2.6

shows the prediction of population and water demand in Dhaka urban areas basing

on the present supply i.e. 1500 mld (Al-Mamoon, 2006).

Figure 2.6 Prediction of population and water demand in Dhaka city.

2.8.4 Water Quality Monitoring System According to DWASA sources, the groundwater and surface water as extracted are

being monitored and tested regularly by its own Quality Control and Research

Division. Saha, (2001) noticed that groundwater supplied by the DWASA is within

the acceptable limit of WHO guidelines. It was also found during testing of water

from WASA groundwater pump points at number of locations in Dhaka city. DWASA

conducts number of tests on important parameters like pH, turbidity, alkalinity,

residual chlorine, faecal coliform etc. of water in the quality control and research

laboratory of the organization. In addition, groundwater samples from Deep

Tubewells (DTW) are also tested for arsenic every three months and river water

samples are tested for chromium and aluminum every six months (Azam, 2005).

Figure O.1 of Appendix O shows the distribution of DTWs and water bodies around

the selected areas of Dhaka city. According to DWASA, necessary mitigation

measures are adopted if there is any change in the quality of water.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

2005 2010 2015 2020 2025

Year

ML

D

0

5

10

15

20

25

Mill

ion

Water Demand (mld) Shortfall(mld) in comparison with present water supply Population (million)

28

2.9 Economic Valuation of Diseases

2.9.1 General

There is no denying that water pollution lead to serious negative impacts on health

and various economic goods and services. The physical evidence is convincing.

The valuation of these impacts, however, has frequently been ignored because it

was thought that either:

It is too difficult to establish direct cause-effect relationships.

Placing monetary values on those effects, either health or productivity was

not feasible.

Economic valuation of health impacts due to consumption of water of urban water

supply and associated sanitation, hygiene and climatic factors was one of the

objectives of this thesis. Here, field data were used to make the valuation using

standard methods and statistical tools. This valuation can be defined as an attempt

to quantify and express in monetary terms the full value of diseases as affected due

to consumption of water of urban water supply and associated poor sanitation and

hygiene practices.

2.9.2 Importance of Monetary Valuation

To compare benefits and costs- as planning process is influenced by

economic analysis (CBA).

To set priorities. If one can compute the expected benefits of different

actions, and then one compares this to the costs of each action, this information

is a critical aid to setting priorities for action. The benefit of an analysis and the

use of quantitative (and, in some cases, qualitative) results is that it helps

societies to make more rational decisions on allocating scarce financial

resources.

Economic valuation helps to bring the environment into decision-making

process.

29

2.9.3 The Major Economic Impacts of Pollution

There are four most important major economic impacts; these are:

Health impacts are the most important and the ones that receive the most

attention. Also, it is often easier to estimate economic costs of health outcomes;

this information is useful in getting the attention of decision makers.

Productivity impacts are often also very important and can be estimated

fairly easily. If individuals or firms need to install special equipment or take

special measures to protect themselves from pollution, these are measurable

economic costs. If polluted water reduces the productivity of natural systems

(crop or fishery production, for example), these are additional productivity costs.

Also, in some situations, pollution (especially air pollution) may be so critical

that industries are closed or transportation is restricted. Both of these steps

impose important economic and social costs on society.

Ecosystem impacts may also occur when such things as underground

aquifers are contaminated, or vegetative areas die due to pollution. Ecosystem

impacts are harder to measure and value and the true impact may not be felt for

many years. Often they are included in a qualitative manner.

Aesthetic impacts.

2.9.4 Techniques to Place Monetary Values on Environmental Impacts

(a) Market based methods:

Production function approach

Cost of illness approach

Cost-based approaches

(b) Cost of illness approach:

Costs of air/water pollution estimated by looking at costs of human health

impact. Dose-response function identifies relationship between level of pollutant

and degree of health effect (water quality and diarrhoea). Here value health

effect based on cost of illness, including:

30

Direct cost of diseases:

Home treatment cost: These are for extra fooding and/or nursing

costs.

Transportation cost: For availing doctor/clinic/hospital support or/and

purchasing medicine at a long distance etc.

Doctor‟s fee: Single doctor visit charge.

Medical expenses: These are expended after visiting doctors for

purchasing medicines.

Indirect cost of Diseases

Parent‟s work lost (when both/either of them were patient)

Parent‟s work lost due to child disease.

Parent‟s leisure lost due to child disease.

Applicability: Value health costs of water and air pollution.

Limitations:

Dose-response functions not available locally.

Does not measure WTP to avoid illness.

2.10 Prevalence Rate (PR)

2.10.1 Importance

Prevalence Rate (PR) is a kind of tool to identify the severity of any particular issue.

In this study, PR of waterborne diseases of the selected areas of Dhaka city has

been used in order to identify the state of vulnerability of the surveyed population.

The greatest waterborne risk to health in most cases is the transmission of faecal

pathogens, due to inadequate sanitation, hygiene and protection of water sources.

Hence population density, state of water sources including its availability, sanitation

system and hygiene practices are the major concerned. Where the population

density is high and sanitation is inadequate, unprotected water sources in and

around the temporary settlement are highly likely to become contaminated. If there

is a significant prevalence of disease cases and carriers in a population of people

31

with low immunity due to malnutrition or the burden of other diseases, then the risk

of an outbreak of waterborne disease is increased. That is why the higher PR value

signifies the higher vulnerability of population to the waterborne diseases.

2.10.2 Formula Used in PR

In this study Equation 2.2, 2.3, 2.4 and 2.5 were used to identify the PR of different

diseases out of 1000 people.

PR Based on Individual Group (PRIG):

(2.2)

PR Based on Group Total (PRGT):

(2.3)

PR of Particular Group Based on Total Population (PRTP):

(2.4) PR of Total Population (PR):

(2.5)

2.11 Statistical Analysis Tools

During analysis following statistical tools have been used to obtain objectives of this

study:

2.11.1 Arithmetic Mean: If there are n numbers of items x1, x2, x3 . . . . xn then the

average value x is given in the Equation 2.6.

n

xxxxx n

....321

(2.6)

PR=Total Number of Incidences×1000

Total Population Surveyed

PRIG=Total Number of Incidences Based on Individual Group×1000

Total Surveyed Population of That Individual Group

PRTP=Total Number of Incidences Based on Individual Group×1000

Total Population Surveyed

PRGT=Total Number of Incidences Based on Individual Group×1000

Surveyed Group Total Population

32

2.11.2 Grade Point Average (GPA): If there are n numbers of items x1, x2, x3 . . . xn

and having y1, y2, y3 . . . . yn grade points respectively; then the GPA is given in the

Equation 2.7.

n

i

i

n

i

ii

y

yx

GPA

1

1

2.11.3 Standard Deviation: The standard deviation is a measure of how widely

values are dispersed from the average value (the mean). The formula used for

unbiased method can be shown in the Equation 2.8.

)1(

)( 2

n

xx

Where x is the sample means of n number of x data.

2.11.4 Correlation Coefficient (Cr): The correlation coefficient to determine the

relationship between two properties. The formula can be shown in the Equation 2.9.

22),(

)()(

))((

yyxx

yyxxCr yx

Where x and y are the sample means of two data sets.

(2.7)

(2.8)

(2.9)

33

CHAPTER 3

METHODOLOGIES

3.1 Introduction

The objective of this research is to study the health impacts of urban water supply

on the vulnerable communities of selected areas of Dhaka city. Here the data of

twenty one administrative thanas of Dhaka city has been considered and from there

only the four most affected thanas have been selected for this study. To attain the

main objective, effort has been made to carry out qualitative assessment of urban

water supply system, sanitation and hygiene practices of different vulnerable

communities of the most affected areas of Dhaka city. Moreover the impacts of

those factors have been quantified in terms of number of incidences and assess the

economic losses incurred. Since climatic factors play a vital role in case of per

capita consumption of water and other microbiological organisms‟ growth, hence an

effort has also been made to identify the correlation between selected climatic

factors and the worst waterborne disease‟s incidence of the same selected areas of

Dhaka city. These all are used to develop overall grading chart showing prevailing

waterborne diseases‟ profiles and costs of diseases with respect to selected areas,

communities and urban water supply options. These results have also been shown

as thematic maps of Dhaka city using Geographical Information System (GIS)

software.

3.2 Methodologies

Since the causes of waterborne diseases are not limited to urban water supply

system/options alone only, rather cover wide spectrum like food, sanitation,

personal hygiene, climate and other behavioral factors too. Hence, for this thesis

work, health impacts of vulnerable people due to water provided by DWASA and

associated sanitation, hygiene and climatic factors have been considered. The

methodologies for this study have been shown in the Figure: 3.1.

(a) Initially existing secondary data related with waterborne diseases of all the

administrative areas of Dhaka city as preserved and maintained by authenticated

sources has been collected in order to identify the health state of Dhaka dwellers as

per as waterborne diseases are concerned and rank them basing on the severity.

34

(b) Since above data would represent only the number of patients reporting

and/or hospitalized without any reference to baseline data. Hence population of

respective areas of Dhaka city for the year of 2010 has been incorporated to

generalize the data as such. Here population data of 2001 has been used as base

data in order to find out the population for the year of 2010 basing on growth rate of

State of Dhaka city as per waterborne diseases

Collection of waterborne diseases related data from Secondary Sources

Identification of the most affected areas

Selection of locations and time for the top 4 most affected areas

Vulnerable Population

Climatic Data from BMD

Urban water supply

Sanitation Practices

Hygiene practices

Correlation of Climatic factors-

Waterborne diseases

Health impacts in terms of number of patients of different

waterborne diseases

Costs of main waterborne diseases

GIS Representation of relevant data in

thematic maps

Figure: 3.1 Methodology diagram

Prevalence Rate of Non-reporting

Incidences

35

6% as stated by DCC (2009). Due to time and resource constrains only the top 4

most affected administrative areas has been selected.

(c) “Slum-map” developed by CUS (Figure 3.2) has been studied in order to

locate the vulnerable people residing at various places of those selected areas of

Dhaka city as per the considerations described in Section 2.2.2 and to identify urban

water supply options as explained in Section 2.5.2. For sampling of population,

“Convenience Sampling Method” was carried out in order to materialize time, money

and other resources related constrains. Again to select better time frame for primary

data collection, the records of waterborne diseases‟ incidences of those selected

areas of Dhaka city have been studied and hence a general monthly trend has been

developed.

(d) To identify the impacts, the primary data has been composed of all the

relevant questionnaires, sanitary inspection (SI) and water samples collection.

Based on all these data results are shown with respect to sample areas, community

types and urban water supply options and draw overall conditions as a result of a

particular issue and associated health impacts and costs of diseases thereof.

Additionally data on climatic factors have been collected from BMD to formulate

correlation among them. Here the climatic factors selected for this thesis work are

monthly rainfall, humidity and temperature (maximum, minimum and average) for

Dhaka station only. Monthly trends of those meteorological factors and diarrhoeal

incidents have been superimposed and statistical tools have been used to find out

the correlation.

(e) Finally recommendations are made for monitoring, improving water quality,

sanitation and hygiene practices and enforcement programs. Additionally number of

thematic maps has been generated using GIS software like ArcGIS (ArcCatalog and

ArcMap) to show the result on Dhaka city perspective so as to help the decision

maker in identifying areas of improvement.

3.3 Design Procedure

In this study health impacts resulting from urban water supply was assessed for

slum and low-income communities of selected areas of Dhaka city by collecting

relevant information from field. This section provides chronological description of the

36

Figure 3.2 Slums of Dhaka metropolitan area (CUS, 2005)

Mirpur

Uttara

Gulshan

Tejgaon

Mohammadpur

Hazaribagh

Kamrangirchar

Rampura

Banani

Badda

Khilkhet

Shyampur

37

methodologies used in this study. To assess the health impacts and costs valuation

of the diseases, necessary methods/statistical analysis tools have been used.

3.3.1 Selection of Vulnerable Communities

It is one of the most important issues on which the whole study has been based on.

The selection of vulnerable communities started with the evaluation of secondary

information as attained from ICDDR,B and DSH and personal contact with experts

and scientists in this regard. Both the institution referred that most of the time it was

the low-income and slum people who visited them frequently round the year. Hence

in this study, these two communities have been referred as vulnerable communities

and their considerations have been given in the Section 2.2.2.

3.3.2 Vulnerability Score

In order to find the state of vulnerability of the given community, the percentage of

exposure for a particular disease with respect to some predefined factors/sub-

factors have been considered. In this study a total 10 points have been assigned for

each factors/sub-factors for their vulnerability. Each increment of 10% in exposure

accounts for 1 point increment in vulnerability score and intermediate values are

calculated proportionately as such. The Table 3.1 shows such vulnerability score

and state of the vulnerability. As it can be seen in the table that vulnerability of the

community increases with the increase of percentage of exposure. However most of

the case 0% exposure means “No data” was found at the time of survey.

Table 3.1 Vulnerability score and state of vulnerability.

Serial Exposure to Particular Disease (%)

Vulnerability Score

State of Vulnerability

1. 10 1 Low

2. 20 2

3. 30 3

Medium 4. 40 4

5. 50 5

6. 60 6 High

7. 70 7

8. 80 8

Very High 9. 90 9

10. 100 10

38

Again, the basic data of Table 3.2 has been used in order to grade the community,

selected areas and urban water supply options and to represent state of the

selected areas in the thematic maps as per color code.

Table 3.2: Basic data for grading and representation.

Vulnerability Score Range

Grade Point Grade Representation

Color Code Use

≥ 8 to 10 4 Very high In thematic map

≥ 6 to <8 3 High

≥ 3 to <6 2 Medium

≥ 0 to <3 1 Low

3.3.3 Identification of Urban Water Supply Options

The method of selection of water points was primarily based on reconnaissance

survey conducted in Gulshan and Mirpur areas. There were private owned water

points and WASA pump house from where people need to pay for the services.

Urban water supply pattern as identified in slum areas were discussed in Section

2.5.2. The water supply options found in the study areas are given in the Table 3.3.

Table 3.3: The water supply options found in the study areas.

Serial Description of Options Community Using Options

1. Piped water supply with reservoir Low-income

2. Piped water supply without reservoir Low-income/slum

3. Hand pump connected to supply line Low-income/slum

3.3.4 Field Survey

(a) Questionnaires: During questionnaires survey, effort was made to

collect all the relevant information leading to the attainment of the thesis objectives.

A detailed Questionnaire Survey Form (QSF) was made right after the

reconnaissance survey and appended as Appendix A. The form contained as much

as 28 questions of different types in order to acquire following general information

regarding:

Community type i.e. slum or low-income groups.

Economic conditions.

Sanitation and hygiene practices.

Accessibility to urban water supply and their patterns.

Occurrences of various waterborne diseases etc. during last one year.

39

Costs they were to bear as a result of waterborne diseases.

Here each question acted as qualitative aspect of either urban water supply or

sanitation or even hygiene related matter of the vulnerable people and quantitative

aspect i.e. health impacts of the same in terms of number of incidences/occurrences

of waterborne diseases those had taken place last one year. The QSF was also

used for the assessment of prevalence rate of mostly affected waterborne diseases

among the communities for which they were to pay the most. During the survey, the

QSF revealed three such most affected waterborne diseases on which the total

calculation of the thesis has been based on; these are:

Diarrhoea

Typhoid.

Eye Infections

Here overlap of water consumption was not considered in this study because people

especially workers or laborers drink water from their service places, restaurants and

from many other locations which might be hygienically more vulnerable than their

households. It will be very complicated if all the sources of water consumption

patterns have to be considered. Since one of the objectives was to calculate

valuation of diseases, hence the focus was on the diseases for which target groups

were to spend some money during the time of sufferings.

Qualitative Assessment Basing on QSF: Here all the data were put into the

database and the questions or the attributes those were assumed to be directly

involved in the contribution of waterborne diseases‟ incidences were filtered and

results were obtained as such. Here is the list of questions used for data filter

operation:

What is the source of your water?

What is the distance of water point from your house?

How much time do you take to collect water from the source?

How much water do you receive every day?

What is the general condition of supplied water?

Do you boil your drinking water?

How much time you boil your drinking water?

Where do you store your drinking water?

Do you use lid to cover your container?

40

What type of Sanitation System you use?

What do you use to wash your hands after defecation?

These results were collected either in terms of HH or number of respondents and

displayed against:

Selected areas.

Community types

Urban Water Supply Options

Overall Conditions

Quantitative Assessment Basing on QSF: At this stage factors of qualitative

assessment were used for identification of health impacts in terms of quantitative

assessment. Since water quality and source water condition have direct effect on

health, hence, the lab-test result on microbiological quality (faecal coliform) of water

and SI risk grading have been incorporated as additional attribute columns. Hence

quantitative assessment was made with respect to twelve factors. These are:

The source of water.

Urban water supply options.

Distance from HH to water source.

Time to fetch water from water source.

Demand of water being met.

Boiling practices prevailing in the community

Duration of time spent to boil drinking water.

Storage of drinking water.

Sanitary system in use.

Hand wash practices after defecation as personal hygiene.

Water quality in terms of microbiological result.

SI Risk Grading

Here for the calculation of health impacts, the number of incidences and total

number of members affected by respective waterborne diseases against each

above factors were found out. Actual numbers of HH members exposed to the

particular disease were used for calculation during data filtering process. However,

where there were no incidences, no exposures were assumed and percentages

were shown as zero. Again where there were only few persons and all were affected

41

by same disease, then percentage shown as 100%. This assumption will naturally

yield high percentage of incidence rate against exposure which is rare in the reality

due to background level of immunity as explained in the Section 2.3.3. The process

of data filtration shown in the following steps:

Step-1: To find out the number of HH members exposed to diarrhoea,

typhoid and eye infections for the slum of Gulshan area. Here criteria used for

filter operations are:

o Thana: Gulshan

o Community type: Slum.

o Diseases: Diarrhoea, typhoid, eye infections (each considered

separately)

The results have been shown in terms of health matrix in the Table 3.4 through

Table 3.8.

Table 3.4: Data filtering process: Step-1

Thana Community

type

No. of Family

Members per HH

TOTAL Affected

by Diarrhoea

TOTAL Affected by

Typhoid

TOTAL Affected by

Eye Infections

Gulshan Slum. 6 6 6

Gulshan Slum. 3 3

Gulshan Slum. 3 1 3

Gulshan Slum. 6 6

Gulshan Slum. 4 1

Gulshan Slum. 9 1 2

Gulshan Slum. 6 6 6

Gulshan Slum. 2 2

Gulshan Slum. 4 4 4

Gulshan Slum. 3 3 3

Gulshan Slum. 5 4 1 5

Total: 28 3 36 % of incidence against Surveyed Population (rounded to next higher number)

55 6 71

One can see that the same family members might not be affected by more than one

disease at the same time and 51 members should be used for reference data in

order to find percentage of incidences. So to find out the correct percentage of

42

affected people against actual exposed HH family members, this matrix needs to be

corrected as such.

Step-2: To find out the actual number of HH members exposed to diarrhoea,

typhoid and eye infections respectively. Here, all the non-blanks data have been

queried by eliminating the blank data for specific disease. Hence three different

tables have been generated each depicting the actual scenario of single disease.

o For Diarrhoea:

Table 3.5: Data filtering process for diarrhoea: Step-2a

Thana Community

type

No. of Family

Members per HH

TOTAL Affected by Diarrhoea

TO

TA

L A

ffe

cte

d

by T

yp

hoid

TO

TA

L A

ffe

cte

d

by E

ye

in

fectio

ns

Gulshan Slum. 6 6 6

Gulshan Slum. 3 1 3

Gulshan Slum. 4 1

Gulshan Slum. 9 1 2

Gulshan Slum. 6 6 6

Gulshan Slum. 2 2

Gulshan Slum. 4 4 4

Gulshan Slum. 3 3 3


Total: 28 3 27

So it shows that out of 9 HHs of 42 family members only 28 persons were affected

by diarrhoea.

o For Typhoid:

Table 3.6: Data filtering process for typhoid: Step-2b

Thana Community

type

No. of Family

Members per HH

TO

TA

L A

ffe

cte

d

by D

iarr

hoe

a

TOTAL Affected by

Typhoid

TO

TA

L A

ffe

cte

d

by E

ye

infe

ctio

ns

Gulshan Slum. 9 1 2


Total: 5 3 5

43

So it shows that out of 2 HHs of 14 family members only 3 persons were affected by

typhoid.

o For Eye infections :

Table 3.7: Data filtering process for eye infections: Step-2c

Thana Community

type

No. of Family

Members per HH

TO

TA

L A

ffe

cte

d

by D

iarr

hoe

a

TO

TA

L A

ffe

cte

d

by T

yp

hoid

TOTAL Affected by

Eye infections

Gulshan Slum. 6 6 6

Gulshan Slum. 3 3

Gulshan Slum. 3 1 3

Gulshan Slum. 6 6

Gulshan Slum. 6 6 6

Gulshan Slum. 4 4 4

Gulshan Slum. 3 3 3


Total: 24 1 36

So it shows that out of 8 HHs of 36 family members all 36 persons were affected by

eye infections .

Step-3: After filtering process, all the data so far found out are compiled and

shown in the Table 3.6. So one can see that the aforesaid communities were

affected by diarrhoea, typhoid and eye infections at 67%, 22% and 100%

respectively instead of 55%, 6% and 71% as mentioned in the Table 3.2.

Table 3.8: Final result of data filtering process

Item

TOTAL Affected by

Diarrhoea Typhoid Eye

infections

Number of Incidences: 28 3 36

Number of Family Members Exposed: 42 14 36

% of incidence against Exposure (rounded to next higher number)

67 22 100

44

(b) Sanitary Inspection (SI): During sample collections, effort were made

to identify risk involved in the source of water (water point) related with sanitation

practices through Sanitary Inspection (SI) Form (Appendix B). Risk questions for SI

were chosen both in lines with WHO and considering local conditions which

otherwise would reveal the existing sanitation and hygiene practices of the

population under observation. There were 10 questions where risk of each question

was evaluated against either „„Y‟‟ for yes or „„N‟‟ for no type answer. Total score of

risks was calculated against 10 where 10 being the worst condition and 0 being the

best. The details of risk scores obtained during SI have been given in Table H.1 of

Appendix H. During evaluation of SI risk scores, criteria mentioned in Table 3.9

were used to grade the selected areas, communities and urban water supply

options.

Table 3.9: Criteria used for grading the SI risk scores

Serial Risk Score Grade Point Grade

1. >=9-10 4 Very high

2. >=6-<9 3 High

3. >=3-<6 2 Medium

4. >=0-<3 1 Low

Following steps are done in order to grade the areas, communities and urban water

supply options:

Step-1 (Calculation of Risk Scores): In order to calculate the risks involved, 1

was allotted for each one “Y” and 0 for each “N” answer. Finally total risks were

summed up to find out the total score of risks.

Step-2 (Grading of Selected areas, Communities and Urban Water Supply

Options): Here each water point was allotted with grade basing on the total

score of risks as shown in the Table H.1 of Appendix H. Next, basing on the

Equation 2.7 as mentioned in the Section 2.11.2, GPA was calculated and

graded the particular issue accordingly. Table H.2 to Table H.4 of Appendix H

have been given for the overall grading of selected areas, communities and

urban water supply options.

45

Step-3 (Using SI Risk Grade in Health Impact Assessment): Firstly a

new attribute column has been introduced in the Table G.1 of Appendix G and

then filling it by putting SI risk grade of each water point of Table H.1 of

Appendix H. Secondly the health impacts were found out using the filter process

as described before.

(c) Sample Collections: Initially aesthetic qualities of water were

examined in-situ. The users were asked about the presence of color, odor, dirt etc.

in their collected water and accordingly the observations were noted. At the same

time the exact location of water points were taken using Global Positioning System

(GPS) in order to mark it on the map for representation. Collected samples after

properly marked sealed and were taken to laboratory for testing. Table 3.10 shows

the list of laboratory tests were done on given parameters in order to get clear

picture of urban water quality both at source (WASA pump house/stand posts) and

at user‟s end.

Table 3.10: List of laboratory tests for collected water samples

Test Parameters Method of Testing

Aesthetic

Color (Pt-Co Unit) DR 5000 Spectrophotometer (HACH)

Odor Field observation and Questionnaire Survey

Presence of dirt

Physical Turbidity (NTU)

HI 93703 Microprocessor Turbidity Meter

pH HI 9024 Microcomputer pH Meter

Chemical Chlorine (Residual) (mg/l)

DR 5000 Spectrophotometer (HACH)

Microbiological FC (cfu /100ml)

Membrane Filtration and incubation in BOD Incubator (HACH) using MFC Broth media

3.3.5 Economic Valuation of Diseases

(a) General: There are a total of 1025 slums within Dhaka Metropolitan Area

(DMA) with a total of 267,065 households and on average 138 households per slum

(LGED 2005). 50 % of the slums rely on tap water as their primary drinking water

source, 2.6% use tube well Water, 0.4% use pond water, 1.3 % use river water and

0.1% uses other sources. The remaining 887 slums have no specified water source.

They rely on buying from vendors, public tankers and nearby slums. The vulnerable

community especially slum dwellers spend time on collecting water from public

sources, storing water and treating water before consumption. Households could

46

avoid all of these coping costs if piped water services are improved (i.e., water is

sufficient, reliable, and potable). Detail calculation of estimated health impact

valuation of waterborne diseases of Dhaka city has been given in Appendix K.

(b) Method Adopted: In this study an attempt was made to quantify and express

in monetary terms the full value of diseases as affected due to consumption of water

of urban water supply and associated poor sanitation and hygiene practices. To do

that, “Cost of illness approach” of Market based methods as stated in Section 2.9.4

was followed. Here willing to pay (WTP) to avoid the illness was not measured

rather health effect based on cost of illness of family members were valued by

calculating the costs.

(c) Quantifying the Indirect Cost: Quantifying direct cost is very simple and

easily available. But quantifying indirect cost requires different approach to follow. It

has been assumed that:

If the parents/earning member would not have affected by waterborne

diseases or would not have to take care of their family members like children,

then the parents/earning member would have gone for his/her work and earned

his/her wages in time. So here needs identification of wage of a daily-labour per

hour. Accordingly Table 3.11 shows the hourly average wage rate of various

types of labours.

Table 3.11: Calculation of hourly average wage rate

Serial Type of Labour

Average Wage Rate (Taka)

Remark Daily

(8 Hours/day) Hourly

1. Mason 300.00 37.50 BBS (2010)

2. Labour 200.00 25.00

3. Rickshaw/van Puller 150.00 18.75 Field Interview

4. Scavenger 50.00 6.25

Average 175.00 21.88

47

The leisure time costs of child diarrhoea also have been converted into

monetary terms by multiplying the time lost by a proportion of the hourly wage of

an individual in the household. For this study, it has been considered 50% of the

average hourly wage rate Tk. 10.94 (mean hourly wage rate was Tk. 21.88). The

50% estimate is similar to fractions used in estimating time costs of water

collection in Nepal (Pattanayak et al. 2005).

(d) Calculation for Whole of Dhaka: Table K.2a of Appendix K used the total

number of HH of slum community as found out by LGED (2005) and total population

found out by multiplying it with HH size (5.25) as found out by this study. Prevalence

rate was used to identify the likely incidences and cost of diseases was

implemented as such. Another approach used in Table K.2b of Appendix K, where

to identify the likely incidences, total population of Dhaka city as found out by BBS

(2011) was multiplied by percentage of population living in slum areas as reported.

Finally costs of diseases were used to find out the total value.

3.3.6 Prevalence Rate (PR)

Evaluation of PR for this study has been made on diarrohea, typhoid and eye

infections. Moreover, since data collected on various age-groups of both male and

female gender, hence the formula (Equation 2.2, 2.3, 2.4 and 2.5 ) as stated in the

Section 2.10.2 has been modified and used for different age-groups and gender too.

Here following steps were followed:

Step-1 (Identification of number of incidences): Here total number of

incidences was calculated for a particular group from existing data of

questionnaire survey e.g. female children of <5 years has been found out.

Step-2 (Identification of total surveyed population of particular group): Here

total number of family members (includes affected and non-affected persons)

exposed to certain diseases were calculated for a particular group from existing

data of questionnaire survey. Here total population (i.e. 210 persons) surveyed

or total female population (i.e. 96 persons) surveyed or total female HH

members of different age-group (i.e. 16 female persons of aging < 5 years)

surveyed have been considered in order to find different PR values. Since this

48

value has been used as denominator, hence the PR values of total population

surveyed differ significantly for each individual case.

Step-3 :(Use of required formula to identify PR): Here for particular issue

different formulas as given in Section 2.10.2 were used to find out PR of different

points of interest. The detail calculation of prevalence rate has been given in

Table L.1 through L.6 of Appendix L.

3.3.7 Climatic Factors

To identify correlation between selected climatic factors and the diarrhoeal incidents

of the selected areas, the annual and monthly records for both elements were

collected. Appendix C and Appendix D cover the yearly and monthly data of

diarrhoeal patients reporting ICDDR,B whereas Appendix F covers the yearly and

monthly climatic data. Correlation can be used effectively to study the future impact

of one factor when value of another factor is known. Following steps were followed

in order to find out the correlation:

Step-1 (Generation of trend of the factor): When monthly records of many

years of a particular climatic factor are plotted, a general trend of that factor can

be generated with reasonable probability. Here trends for both climatic factor

and incidences of waterborne diseases are plotted in the same chart; where

abscissa denotes the months of year and ordinate (primary and secondary axes)

for different values of two factors to see the similarity in occurrences.

Step-2 (Development of Correlation): Basing on the above information, now

scatter chart is used to find out the probable correlation between climatic factor

and number of patients reporting the ICDDR,B with waterborne diseases.

Step-3 (Formulation of Correlation): After a correlation is found out, a best fit

trend line is drawn using Microsoft Excel and the associated equation is

formulated as such. Here point to note that for formulation using regression

analysis, data is checked in order to find out if the correlation is linear or non-

linear i.e. exponential/ logarithmic. For linear correlation no data transformation

is required but for non-linear case data will be transformed.

49

CHAPTER 4

ANALYSIS OF DATA

4.1 Introduction

Water is undoubtedly the most precious natural resource that exists on our planet

without this seemingly invaluable compound, life on earth would not be in existence.

As we understand that our health is truly dependent on the quality and quantity of

the water we drink. Hence any deficiency either of it is going to have a negative

effect on our health. That is why safe, adequate and accessible supplies of water,

combined with proper sanitation, are basic needs and essential components of

primary health care. This chapter describe in details about the analysis part of the

total thesis work covering the important aspects like water, sanitation, hygiene and

climatic factors which have direct impact on human health.

4.2 Data Availability in Bangladesh

It is often found that relevant data on health are rarely maintained by an individual of

any class. Preservation and maintenance of data at national level is also in very

initial stage. With these limitations, attempt has been made to look for organizations

maintaining relevant health data so as to identify the severity of the areas of Dhaka

city as per as waterborne diseases are concerned. Analyzing such data will provide

more realistic scenario than that of guessing at random in order to select the sample

areas for this study. As such all the data related with waterborne diseases have

been collected from ICDDR,B and DSH. On the other hand, to fulfill another

objective of the thesis related with correlation between waterborne diseases and

climatic factors, the meteorological data has been collected from BMD. Other

secondary data have also been collected from WASA, DOE, DCC, BCUS, RAJUK,

Survey of Bangladesh (SOB), Bangladesh Bureau of Statistics (BBS) etc. All these

data and data collected at field level will allow us to attain the objective of this thesis.

4.3 Selection of Data

The number of patients suffered from waterborne diseases, reported to and/or

hospitalized to ICDDR,B from 1996 to 2010 have been used to identify the general

50

public health condition of Dhaka as per as waterborne diseases are concerned.

Here the types of data used are:

4.3.1 Yearly Records: Yearly records of patients of different age groups (e.g. <5,

5-14 and > 15 years) from different thanas of Dhaka city reported/hospitalized to

ICDDR, B from 1996 to 2010 have been averaged and given in Appendix-C. Basing

on these 15 years of records, a yearly trend could be developed as given in the

Figure 4.1 .

Figure 4.1 Yearly trends of waterborne disease’s patients of Dhaka city

While visiting the hospital and discussing with concerned authority of ICDDR, B

about the type of people and their pattern of reporting the hospital; following

information could be extracted:

Patients are mostly from vulnerable groups i.e. low-income and slum people.

Patients, those are critical in nature report to hospital more than those who

suffer regular basis.

Children (<5 years) and elderly people (> 15 years) suffer much than those

of middle ages (5-14 years) people.

0

2000

4000

6000

8000

10000

12000

Nu

mb

er

of

pat

ien

t

Thanas of Dhaka city

<5 Yrs 5-14 Yrs 15+ Yrs

51

Patients residing nearer to the hospitals, report more than those residing

away from it.

On the other hand, Figure 4.2 shows the number of children admitted during 2005-

2006 to Dhaka Shishu Hospital (DSH).

Figure 4.2 Children patients reporting DSH during 2005-06.

This figure also shows that patients locating nearby DSH have more reporting

incidences. The yearly trend as shown in Figure 4.1 to be more effective, the data of

different administrative areas of Dhaka city have been generalized against its

population. Here the population of thanas of Dhaka for the year of 2010 has been

estimated using geometric progression method as mentioned in the Section 2.2.3

and given in Appendix E. With this estimated thana population and number of

reported patients during 2010, a more generalized data for each 1000 people has

been calculated as shown in the Table 4.1. Now from this generalized data only the

first top four thanas i.e. Gulshan, Badda, Tejgaon and Mirpur have been selected

for this study. It may be noted that though the patients reporting ICDDR,B from

Mirpur and Demra have been found same (i.e. 12 out of 1000); but due to high

incidences of Mirpur (10,950) than Demra (8,300), Mirpur has been chosen. Here

Table 4.2 shows the average patients of different age groups of selected areas of

Dhaka city.

05

10152025303540

Nu

mb

er

of

Ch

ildre

n A

dm

itte

d

Diarrhoea Viral Hepatitis Jaundice Typhoid

52

Table 4.1 Generalized population of administrative areas of Dhaka city reporting ICDDR, B in 2010

Ser Name

Ma

le

Po

pu

lati

on

Fem

ale

Po

pu

lati

on

To

tal P

op

ula

tio

n

(200

1)

Pp=

c+

d

Pro

jecte

d P

op

(2

010)

Pf =

Pp (

1+

r)n

(r =

6%

, n

=9)

Re

po

rte

d t

o IC

DD

R,B

(2010)

Ou

t o

f 1

00

0

h =

g X

1000 / P

f

(a) (b) (c) (d) (e) (f) (g) (h)

1 Gulshan 107000 83000 190000 321002 8250 26

2 Badda 198000 161000 359000 606523 9200 16

3 Tejgaon 174000 128000 302000 510223 7450 15

4 Mirpur 301000 250000 551000 930903 10950 12

5 Demra 238000 190000 428000 723097 8300 12

6 Mohammadpur 251000 205000 456000 770403 7200 10

7 Uttara 188000 157000 345000 582871 5400 10

8 Lalbag 206000 140000 346000 584560 4500 8

9 Khilgaon 185000 152000 337000 569355 4350 8

10 Kotawali 162000 92000 254000 429128 3100 8

11 Hazaribag 71000 57000 128000 216254 1350 7

12 Kamrangirchar 76000 67000 143000 241596 1650 7

13 Sutrapur 206000 147000 353000 596387 3600 7

14 Kafrul 157000 133000 290000 489949 3250 7

15 Shabujbag 318000 131000 449000 758577 3850 6

16 Cantonment 70000 48000 118000 199359 1050 6

17 Shyampur 211000 165000 376000 635245 3050 5

18 Motijheel 162000 108000 270000 456160 1950 5

19 Ramna 149000 109000 258000 435886 2150 5

20 Dhanmondi 147000 106000 253000 427439 1850 5

21 Pallabi 232000 200000 432000 729855 1550 3

Source: BBS (2010), ICDDR, B (2010)

Table 4.2 Selected thana wise different age groups patients

Sample Areas <5 Yrs 5-14 Yrs 15+ Yrs Total

Gulshan 4150 650 3100 7900

Badda 3650 500 2850 7000

Tejgaon 2500 350 2250 5100

Mirpur 4950 900 5100 10950

Total: 15250 2400 13300 30950

Source: ICDDR,B (2010)

53

4.3.2 Monthly Records: To identify the general trends of waterborne diseases,

monthly records of eleven years (2000 to 2010) of patients from different thanas of

Dhaka city reported/hospitalized to ICDDR,B as given in Appendix-D has been

used. Basing on average monthly records of those eleven years, a general trend of

incidences has been found out for selected areas as given in the Figure 4.3.

Figure 4.3 General Trend of Patients of Waterborne Diseases

In this study, the data collected during second peak as marked by vertical lines.

4.3.3 Meteorological Data. The climate of Dhaka is tropical in nature with heavy

rain and bright sunshine in the monsoon and warm for the greater part of the year.

On the other hand during winter which is from November to March are however cool

and pleasant. Table 4.3 shows “at a glance” of Dhaka city climate:

Table 4.3 At a glance of Dhaka city climate

Temperature

Maximum Minimum

Summer 36.70 C 21.10 C

Winter 31.70 C 10.50 C

Rainfall 2540 mm annually

Humidity 80 per cent (approximately)

Source: DCC (2009)

Here monthly and annual records of selected factors of last 21 years (1990 to 2010)

have been collected from BMD and given in Appendix F. Since the diarrhoeal

diseases is a major problem as per as waterborne diseases are concerned; hence

0

200

400

600

800

1000

1200

1400

1600

1800

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Num

ber

of

dia

rrhoeal patients

Month

Tejgaon Badda Gulshan Mirpur

54

the effect of climatic factors have been used to find out the correlation with

diarrhoeal diseases only.

(a) Rainfall Pattern of Dhaka city: The 21 years rainfall pattern of Dhaka city is

based on the annual total rainfall data whose average value has been given in the

Table F.1 of Appendix F. Here the minimum rainfall has been recorded as 1169 mm

in the year of 1992 and maximum was 2885 mm in the year 2007 and the average

rainfall is about 2148 mm. Figure 4.4 shows the variations of annual rainfall of

Dhaka city from the year 1990 to 2010 (BMD 2010).

Figure 4.4 Variations of annual rainfall of Dhaka city

Basing on the average monthly rainfall of aforesaid 21 years, a general trend can be

developed and can be used for subsequent interpolation of data with waterborne

diseases. Figure 4.5 shows such trend of rainfall of Dhaka city indicating two peaks

at two different time frames mostly around Jun-July and another in September.

Figure 4.5 Trend of rainfall of Dhaka city

Average annual rainfall 2148mm

0

100

200

300

400

500


Mo

nth

ly R

ain

fall (

mm

)

Month

55

(b) Temperature Pattern of Dhaka city: The 21 years temperature pattern of

Dhaka city is based on the annual average minimum, average maximum and

average temperature data as given in the Table F.1 of Appendix F. Here the

average minimum annual temperature has been recorded as 21.6°C in the year of

1997 and average maximum annual temperature was 31.7°C in the year 1996.

Figure 4.6 shows the variations of annual temperature in Dhaka city from the year

1990 to 2010 (BMD 2010).

Figure 4.6 Variations of average annual temperature of Dhaka city

Basing on the average monthly temperature of aforesaid 21 years, a general trend

can be developed and can be used for subsequent interpolation of data with

waterborne diseases.

Figure 4.7 Trend of temperature of Dhaka city

15

20

25

30

35

Tem

pera

ture

(°C

)

Year

Maximum Minimum Avgerage

10

15

20

25

30

35


Tem

pe

ratu

re(°

C)

Month

Mean Maximum Minimum Avgerage

56

Figure 4.7 shows such trend of rainfall of Dhaka city indicating two peaks at two

different time frame i.e. around April-May and another around August-September.

(c) Humidity Pattern of Dhaka city: The 21 years humidity pattern of Dhaka city

is based on the annual average humidity data as given in the Table F.1 of Appendix

F. Figure 4.8 shows the variations of annual humidity in Dhaka city from the year

1990 to 2010 (BMD 2010).

Figure 4.8 Variations of average annual humidity of Dhaka city

Basing on the average monthly temperature of aforesaid 21 years, a general trend

can be developed and can be used for subsequent interpolation of data with

waterborne diseases. Figure 4.9 shows such trend of humidity of Dhaka city.

Figure 4.9 Trend of average annual humidity of Dhaka city

66

68

70

72

74

76

78

Hu

mid

ity(%

)

Year

55

60

65

70

75

80

85


Month

Hu

mid

ity(%

)

57

4.4 Analysis of Field Data

Basing on information in the Section 4.3.2, the field data was collected from July-

November 2010 only i.e. collecting data during second peak period (Figure 4.3).

4.4.1 Questionnaires Survey- An Overview

In this study, 40 HHs of 210 family members were interviewed. It can be seen that

the 3 to 6 members HH were the maximum covering about 79% of the total family

members surveyed. The average size of a HH was found to be more than 5

members/HH (i.e. 5.25 members/HH, Figure 4.10). During survey, it was found that

a single water point was being shared by in average more than 5 HHs (i.e. more

than 25 family members - one cluster) and same kind of water by number of

clusters. Accordingly, it was found that about 2,651 family members of different

clusters directly exposed to same water points and 67,500 members being indirectly

affected due to use of same kind of water supplied by urban water supply system.

Table 4.4 shows the distribution of these members residing in the following sample

areas are.

Figure 4.10 Distribution of population by number of person per HH

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Po

pu

lati

on

Su

rve

yed

Person per HH

5.25

58

Table 4.4 Sample area wise distribution of interviewed HHs and exposed

population

Serial Sample Areas

Number of HHs

Number of HH

Members

Number of Directly Exposed

Population

Number of Indirectly Exposed

Population

1. Gulshan 12 56 1150 27000

2. Tejgaon 10 48 455 12300

3. Badda 8 42 600 12700

4. Mirpur 10 64 446 15500

Total: 40 210 2,651 67,500

Table 4.5 shows the distribution of communities interviewed. However it was found

that about 55% and 45% were male and female gender respondents respectively.

Table 4.5: Age group wise distribution of interviewed communities

Community Type

Age Groups Interviewed (Number of HHs) Total Number of

HHs 15-30 Year 30-45 Year 45-60 Year

Slum 6 15 2 23

Low-income 6 7 4 17

Total: 12 22 6 40

The most of the interviewed male members were masons, rickshaw pullers, drivers

(baby taxi, mishuk, truck drivers etc.), vegetable vendors, workers, hawkers,

scavengers who mainly came from other districts (73% of total surveyed

respondents) of Bangladesh for economic reasons. Actually these people were

manual labourers who generally earned their livelihood under different climatic

condition and remained susceptible to the high temperatures. During survey, it was

learnt that they drink water usually from unreliable sources like construction sites,

road side hotels/restaurants, stand posts etc. without considering the quality of it.

This happened to be more during the day with high temperature.

4.4.2 Qualitative Assessment

(a) Sources of Water and Urban Water Supply Options: Qualitative assessment

starts with the identifications of the connection sources and urban water supply

options available to the communities of different selected areas. Table 4.6 shows

the distribution of number of HHs to urban water supply options as per community

and connection sources. It is seen that the most of the case, the sources of water

59

for the above communities were from private connections from nearby WASA line

using rubber, low quality plastic pipes following over the wasteland or most

unhygienic area as these can be seen in the Image 4.1, 4.2 and 4.3. The relevant

details of Questionnaire Survey have been given in Table G.1 of Appendix G.

Table 4.6 Distribution of number of HHs to urban water supply options as per

community type and connection sources

Community Type

Connection Sources

Urban Water Supply Options (Number of HHs)

Pip

ed

wa

ter

su

pp

ly w

ith

res

erv

oir

Pip

ed

wa

ter

su

pp

ly w

ith

ou

t

res

erv

oir

Ha

nd

pu

mp

co

nn

ecte

d t

o

su

pp

ly lin

e/S

TW

To

tal

Slum Private connection. 0 4 10 14

Public connection/Tap water 3 2 4 9

Low- income Private connection. 1 7 4 12


Overall Private connection. 1 11 14 26


Grand Total: 6 15 19 40

There were 27 water points as shown in Figure O.2 of Appendix O whose water

samples were tested. 3 of those were collected directly from WASA pump house in

order to test the state of delivery water quality. Table 4.7 and 4.8 are showing the

disposal of the rest 24 observed water points available for different urban water

supply options and having direct impact on to the vulnerable communities.

60

Image 4.1: Exposed water line at Mirpur

Image 4.2: Exposed water line at Gulshan (IPS Bosti)

Image 4.3: Exposed water line at Tejgaon

61

Table 4.7: Distribution of selected area wise number of observed water points

to urban water supply options

Selected Areas

Piped water supply with

reservoir (No)

Piped water supply without

reservoir (No)

Hand pump connected to supply line

(No)

Total Nos.

Gulshan 1 3 2 6

Tejgaon 1 2 2 5

Badda 1 5 6

Mirpur 2 4 1 7

Total: 4 10 10 24

Table 4.8: Distribution of community wise number of observed water points to

urban water supply options

Community

Piped water supply with

reservoir (No)


reservoir (No)


(No)

Total Nos.

Slum 2 4 7 13

Low-income 2 6 3 11

Total: 4 10 10 24

(b) Distance and Time Related with Water Source: Table 4.9 and 4.10

summarizes the distribution of HHs residing at different distances from water

sources and time taken for fetching water from those sources respectively. Figure

4.11 shows different distance range between households and water sources for the

selected sample areas.

Table 4.9: Distribution of number of HHs residing at different distances from

water sources.

Distance Urban Water Supply Options Community (Number of HHs)

Slum Low income Total

<50m

Piped water supply with reservoir 0 3 3

Piped water supply without reservoir 4 9 13

Hand pump connected to supply line 11 4 15

Sub Total: 15 16 31

<100 (50-100)m




Sub Total: 3 0 3

<250 (100-250) m




Sub Total: 5 1 6

Grand Total: 23 17 40

62

Table 4.10: Community wise number of HHs against time taken to fetch water

Community Type

Distance Travel

Time Taken (Number of HHs)

5 minutes

5-15 minutes

15-30 minutes

Total

Slum

<50m 15 0 0 15

<100 (50-100)m 0 2 1 3

<250 (100-250) m 0 1 4 5

Sub Total: 15 3 5 23

Low income

<50m 16 0 0 16

<100 (50-100)m 0 0 0 0

<250(100-250) m 0 1 0 1

Sub Total: 16 1 0 17


Figure 4.11: Sample areas wise different distance range between households

and water sources.

(c) Water Demand: In this study Table 4.11 shows the distribution of number of

HHs against water demand and water sources' connections. While Table 4.12

shows the distribution of community wise HHs against water demand and urban

water supply options.

Table 4.11: Distribution of number of HHs against water demand and water

sources' connections

Sources' Connections Water Demand (Number of HHs)

100% 75% 50% Total

Supplied water through private connection

2 10 14 26

Supplied water through public connection/Tap water

0 6 8 14

Total: 2 16 22 40

0

2

4

6

8

10

12

14

Gulshan Tejgaon Badda Mirpur

Sample Area

Nu

mb

er

of

HH

s

<50m <100 (50-100)m <250 (100-250) m

63

Table 4.12: Distribution of community wise number of HHs against water demand and urban water supply options

Water Demand

Urban Water Supply Options Community Type

Total Slum Low income

Full/As per demand




Sub Total: 0 2 2

75% of demand




Sub Total: 6 10 16

50% of demand




Sub Total: 17 5 22


(d) Aesthetic Quality of Water: During interview, the members of respective

communities were asked to give their opinion on the general condition of water they

use day to day life. Their observations on the aesthetic quality of supplied urban

water were noted. However, it was informed that those observations were temporary

in nature and generally observed right after the absence of electricity on the part of

WASA pump house. Sample area wise number of HH reporting different aesthetic

quality of water has been given in the Table 4.13.

Table 4.13: Sample area wise number of HHs reporting aesthetic quality of

water

Sample Areas

Clean and fresh

Odorous Turbid Contains dirt and

other foreign materials

Total

Gulshan 2 4 0 6 12

Tejgaon 0 7 2 1 10

Badda 0 6 0 2 8

Mirpur 5 1 0 4 10

Total: 7 18 2 13 40

(e) Boiling Practices of Drinking Water: In the context of water supply in Dhaka

city, due to risk of outbreaks of waterborne diseases, people often boil the supply

water prior to drinking. But boiling practices depend on the availability of fuel,

economic ability, awareness of diseases and its consequences. Table 4.14 shows

the distribution of HHs of different communities against water boiling practices and

64

Table 4.14: Distribution of HHs of different community types against water boiling practices and urban water supply options

Boiling Practices

Urban Water Supply Options Community Type

Total Slum Low income

Yes




Sub Total: 0 13 13

No




Sub Total: 23 4 27


urban water supply options. Table 4.15 shows the distribution of HHs of low-income

community using different water supply options. There were 13 HHs of low-income

community who usually boiled water for different time range.

Table 4.15: Distribution of low-income community HHs against water boiling duration and urban water supply options

Urban Water Supply Options Boiling Duration

5-15 minutes 15-30 minutes

Piped water supply with reservoir 0 3

Piped water supply without reservoir 3 3

Hand pump connected to supply line 1 3

Total: 4 9

(f) Storage of Water in Practice: At domestic water supply system, storage of

water plays a vital role; because it provides a kind of assurance to the user about its

availability and quality during scares time. There were mainly 4 types of storage

container noticed during the survey; these are:

Drum: These are plastic drums formerly used for preservation and storage of

chemicals.

Kolosh (Pitcher): These were both earthen and silver pitchers.

Patil (Cooking ware): These were also used side by side after their cooking.

Water Bottle: These were the PET bottles usually collected from unreliable

sources by vulnerable groups after being used.

Table 4.16, Table 4.17 and Table 4.18 show the different distribution of HHs with

respect to storage system for different communities, selected areas and urban

supply options. Generally the community was seen using lids to cover the

containers which provide them first hand safety from the flies, leaves etc.

65

Table 4.16 Distribution of number of HHs of different community with respect to water storage system at HH level.

Community Drum Kolosh Patil Water Bottle Total

Slum 8 8 0 7 23

Low-income 1 14 1 1 17

Total: 9 22 1 8 40

Table 4.17 Distribution of number of HHs of different selected areas with respect to water storage system at HH level.

Selected Areas Drum Kolosh Patil Water Bottle Total

Gulshan 4 4 0 4 12

Tejgaon 3 6 0 1 10

Badda 1 6 0 1 8

Mirpur 1 6 1 2 10

Total 9 22 1 8 40

Table 4.18 Distribution of number of HHs of different urban water supply system with respect to water storage system at HH level.

Urban Water Supply Options Drum Kolosh Patil Water Bottle

Total

Piped water supply with reservoir 0 5 0 1 6

Piped water supply without reservoir 3 9 1 2 15

Hand pump connected to supply line 6 8 0 5 19

Total: 9 22 1 3 40

(g) Sanitation Systems in Use: Sanitation can contribute greatly to preventing

the spread of infectious diseases through transmission of disease causing agents as

is the case when pathogenic organisms from the excreta of an infected person are

transmitted to a healthy person. In this study different sanitation systems were taken

Table 4.19: Sample area wise distribution of number of HHs of different communities having different sanitation systems

Sample Area

Community Type

Sanitation Systems

Sanitary sewer

Septic tank

system

Pit latrine

Hanging latrine

Unsanitary Total

Gulshan Slum 0 0 10 0 1 11

Low-income 0 0 1 0 0 1

Tejgaon Slum 0 0 2 0 2 4


Badda Slum 0 2 0 0 2 4


Mirpur Slum 0 0 2 2 0 4


Subtotal Slum 0 2 14 2 5 23

Low-income 2 11 4 0 0 17

Grand Total: 2 13 18 2 5 40

66

into consideration in order to locate any possibilities of linking between waterborne

diseases‟ incidences in the selected areas. Table 4.19 shows such information as

sample wise distribution of HHs of different communities.

(h) Hygiene Practices-Use of Hand Wash Medium: Hand washing is one of the

important aspects for effective personal hygiene maintenance. It has direct impact

on the hygiene practices only when its three points are addressed properly; these

are quantity of water, time of washing and medium used for washing. As it was

already discussed in Section 2.7.2 that the most critical times for hand washing are

following defecation and before eating. However this study identified soap, ash/soil

as means of hand washing following defecation. Table 4.20 shows the details of the

study area about the state of hand washing among the communities.

Table 4.20: Sample area wise distribution of number of HHs of different communities showing hand washing practices

Sample Area Community Type Soap Ash/Soil Nothing Total

Gulshan Slum 1 0 10 11

Low-income 1 0 0 1

Tejgaon Slum 1 1 2 4

Low-income 6 0 0 6

Badda Slum 0 0 4 4

Low-income 4 0 0 4

Mirpur Slum 1 0 3 4

Low-income 6 0 0 6

Total Slum 3 1 19 23

Low-income 17 0 0 17


67

(i) Water Quality of Collected Samples: In this study, the sample water was

tested for its physical, chemical and microbiological qualities as stated in the Section

3.3.3. During interview with pump operators (representative from WASA), it was

learnt that generally the quality of pump house water was quite acceptable and

needed no extra treatment. However sometimes they use chlorine gas or bleaching

powder in order to make residual chlorine available in the distribution network. It

was found that the samples of WASA pump houses were within the range of

drinking water standards of Bangladesh. It shows the source water quality on which

the community has to rely on. The detailed analysis of samples has been given in

Appendix I. Following Tables (Table 4.21 through 4.23) shows the state of

contamination described in terms of number of samples at different FC count.

Table 4.21: Area wise number of samples of different faecal coliform concentration

Selected Areas FC Count (cfu/100ml)

0-100 100-200 200-300 300-400

Gulshan 2 1 3 0

Tejgaon 1 2 2 0

Badda 0 3 2 0

Mirpur 0 3 3 1

% Covering 17 37 42 4

Table 4.22: Community wise number of samples of different faecal coliform concentration

Community FC Count (cfu/100ml)

0-100 100-200 200-300 300-400

Slum 2 3 7 0

Low-income 1 6 3 1

% Covering 17 37 42 4

Table 4.23: Urban water supply option wise number of samples of different faecal coliform concentration

Urban Water Supply Options FC Count (cfu/100ml)

0-100 100-200 200-300 300-400

Piped water supply with reservoir 0 3 1 0

Piped water supply without reservoir 2 3 4 1

Hand pump connected to supply line 2 3 5 0

% Covering 17 37 42 4

68

(j) Sanitary Inspection (SI): Sanitary Inspection (SI) form (Appendix B) was

used to identify risk involved in the source of water (water point) related with

sanitation practices. There were 27 water points out of which 3 were from WASA

Ground Water Supply Pump (WGWSP). SI was done for those water points and

Table 4.24: Area wise distribution of number of water points as per risk grade

Selected Area

Number of Water Points Obtained Grade

Low Medium High Very High Total

Gulshan 2 3 1 6

Tejgaon 2 2 3 7 Badda 3 3 6 Mirpur 1 3 3 1 8

Total: 3 10 12 2 27

samples were tested in order to find out the source contamination. Detail risk score

analysis has been given in Appendix H. Following Table 4.24 shows the distribution

of water points as per grade obtained after analyzing in Table H.1 of Appendix H.

However for the sake of exact calculation of the community, the above three “low”

graded water points were not considered in this study. However they have been

considered as one of the comparative measures. Here the WGWSPs had very low

score and maintained properly. Community wise and urban supply options wise risk

grade have been given in the Table 4.25 and 4.26 respectively.

Table 4.25: Community wise distribution of number of water points as per SI risk grade

Community Type

Number of Water Points Obtained Grade

Medium High Very High Total

Slum 5 6 2 13

Low-income 5 6 0 11

Total: 10 12 2 24

Table 4.26: Urban supply options wise distribution of number of water points as per SI risk grade

Urban Supply Options Number of Water Points Obtained Grade

Medium High Very High Total




Total: 10 12 2 24

69

Detail calculation for overall grading using formula as mentioned in the Section

2.11.2 have been given in the Table H.2 to H.4 of Appendix H.

4.4.3 Quantitative Assessment

(a) An Overview: The overall incidences of waterborne diseases of various age

groups according to the genders have been given in the Table 4.27. Here it shows

that elderly people (> 15 Years) of both male and female genders were found to be

more in percentage than those of other age groups. On the other hand, Table 4.28

shows the Sample areas wise state of waterborne diseases‟ incidences of different

genders. This table shows that in every sample areas, the rates of incidences are

more for male than those of females.

Table 4.27: Gender wise overall incidences of waterborne diseases of different age groups

Gender Age

Groups Exposure Number

Number of Incidences


Infections

Female (F)

<5 Years 16 10 2 3

5-14 Years 20 9 1 8

>15 Years 60 26 3 14

Subtotal: 96 45 6 25

Male (M)

<5 Years 17 5 1 7

5-14 Years 26 18 1 9

>15 Years 71 33 2 24

Subtotal: 114 56 4 40

Grand Total: 210 101 10 65

Table 4.28: Sample areas wise state of waterborne diseases’ incidences of

different genders

Sample Areas

Gender



Infections

Gulshan

Female (F) 13 2 15

Male (M) 17 1 21

Subtotal: 30 3 36

Tejgaon

Female (F) 9 2 5

Male (M) 12 0 6

Subtotal: 21 2 11

Badda

Female (F) 9 1 4

Male (M) 11 2 8

Subtotal: 20 3 12

Mirpur

Female (F) 14 1 1

Male (M) 16 1 5

Subtotal: 30 2 6


70

Table 4.29 shows the community wise waterborne diseases‟ incidences. It is evident

that the incidents of slum were more than those of low-income group. To be more

specific, though the slum communities were comprised of 23 HHs of 117 family

members, but while interviewing, it was found that 61 persons of 21 HHs suffered

from diarhoea, 8 persons of 6 HHs suffered from Typhoid and 42 persons of 14 HHs

suffered from eye infections . Out of 40 HHs, 101 members have been found

affected by diarhoea, 10 members by typhoid and 116 members by eye infections

during last one year. These data will be useful to identify health impacts for

communities, selected areas, urban water supply options and present overall state

of the incidences against exposure.

Table 4.29: Community wise state of waterborne diseases’ incidences

Community

Num

ber

of H

H

Num

ber

of H

H M

em

bers


Diarrhoea Typhoid Eye Infections

Affecte

d

Not A

ffecte

d

Out of

Mem

bers

/HH

Affecte

d

Not A

ffecte

d

Out of

Mem

bers

/HH

Affecte

d

Not A

ffecte

d

Out of

Mem

bers

/HH

Slum 23 117 61 47 108/21 8 30 38/6 42 29 71/14

Low-income 17 93 40 26 66/12 2 4 6/1 23 22 45/9

Total: 40 210 101 73 174/33 10 34 44/7 65 51 116/23

(b) Water Sources‟ Connections: In qualitative assessment it was seen majority

of the connections were using private means (65%) and 54% of it was shared by

slum people. Table 4.30 shows the waterborne diseases‟ incidences found against

water sources‟ connections.

71

Table 4.30: Waterborne diseases’ incidences with respect to water sources’

connections

Water Sources’ Connections


Num

ber

of In

cid

ences

Num

ber

of F

am

ily

Mem

bers

Expose

d

% o

f in

cid

ence a

ga

inst

Exposure

% o

f in

cid

ences a

gain

st

Tota

l in

cid

ences

Num

ber

of In

cid

ences

Num

ber

of F

am

ily

Mem

bers

Expose

d

% o

f in

cid

ence a

ga

inst

Exposure

% o

f in

cid

ences a

gain

st

Tota

l in

cid

ences

Num

ber

of In

cid

ences

Num

ber

of F

am

ily

Mem

bers

Expose

d

% o

f in

cid

ence a

ga

inst

Exposure

% o

f in

cid

ences a

gain

st

Tota

l in

cid

ences

Private Connection

75 121 62 74 6 27 23 60 50 93 54 77

Public Connection/Tap

Water 26 53 50 26 4 17 24 40 15 23 66 23

Grand Total: 101 174 59 100 10 44 23 100 65 116 57 100

(c) Urban Water Supply Options: Health impact due to use of urban water

supply options was the main objective of this thesis. Table 4.31 shows the health

impacts in terms of waterborne diseases‟ incidences with respect to urban water

supply options and Table 4.32 shows community wise waterborne diseases‟

incidences with respect to urban water supply options.

Table 4.31: Waterborne diseases’ incidences with respect to urban water

supply options


Diarrhoea Typhoid Eye infections

Nu

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of In

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ces

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ga

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Piped water supply with reservoir

20 31 65 0 0 0 10 11 91

Piped water supply without reservoir

27 56 49 4 15 27 22 40 55


54 87 63 6 29 21 33 65 51

Grand Total: 101 174 59 10 44 23 65 116 57

72

Table 4.32: Community wise waterborne diseases’ incidences with respect

to urban water supply options

Community Gender




reservoir


Dia

rrho

ea

Typhoid

Eye

infe

ctions

Dia

rrho

ea

Typhoid

Eye

infe

ctions

Dia

rrho

ea

Typhoid

Eye

infe

ctions

Slum

Female 3 0 3 7 1 4 19 4 9

Male 5 0 4 5 1 7 22 2 15

Sub Total: 8 0 7 12 2 11 41 6 24

Low-income

Female 6 0 2 6 1 4 4 0 3

Male 6 0 1 9 1 7 9 0 6

Sub Total: 12 0 3 15 2 11 13 0 9

Grand Total: 20 0 10 27 4 22 54 6 33

(d) Distance and Time Related with Water Sources: In this study Table 4.33 and

Table 4.34 show that incidences of waterborne diseases queried against distance

and time taken to fetch water from its sources respectively. Though the number of

incidences are more within 50m distance or < 5minutes walk. This happened due to

the fact, the maximum people reside within 50m distance or < 5minutes walk. But

however percentage of exposure found to be more for consumers who had to fetch

water from longer distance.

73

Table 4.33: Waterborne diseases’ incidences with respect to distance

between HH and source

Distance Between HH and Water Source


Nu

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<50m 81 137 60 7 30 24 51 98 53

<100m (50m-100m) 6 18 34 3 14 22 5 5 100

<250m (100m-250m) 14 19 74 0 0 0 9 13 70

Table 4.34: Waterborne diseases’ incidences with respect to time taken to

fetch water from source

Time Taken to Fetch Water from

Source


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5 minutes 81 137 60 7 30 24 51 98 53

5-15 minutes 3 18 17 2 9 23 2 6 34

15-30 minutes 17 19 90 1 5 20 12 12 100

74

(e) Water Demand: This entails the usual quantity of water accessible to

communities. Table 4.35 shows the number of incidences with respect to water

demand as observed during survey.

Table 4.35: Waterborne diseases’ incidences with respect to water received

against demand

Water Received Against Demand


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Full/As per demand 5 5 100 2 6 34 3 5 60

75% of demand 29 50 58 2 8 25 36 50 72

50% of demand 67 119 57 6 30 20 26 61 43

(f) Water Boiling Practices: Since boiling practices depend on the availability of

fuel, awareness of diseases it also guide user to boil water at certain time duration

so as to reduce the pathogens survival rate. Table 4.36 shows the incidences with

respect to water boiling practices while Table 4.37 shows the incidences with

Table 4.36: Number of waterborne diseases’ incidences with respect to

boiling of water.

Water Boiling Practices


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Yes 35 62 57 2 6 34 15 31 49

No 66 112 59 8 38 22 50 85 59

75

respect to water boiling duration for the HHs having boiling practices in vogue.

Table 4.37: Number of waterborne diseases’ incidences with respect to time

spent for boiling of water.

Water Boiling Time


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5-15 minutes 10 18 56 2 6 34 0 0 0

15-30 minutes 25 44 57 0 0 0 15 31 49

Total: 35 62 57 2 6 34 15 31 49

(g) Storage of Water: Table 4.38 shows the incidences with respect to water

storage system. It clearly shows that though the use of patil as storage system is not

that versatile; the high values of percentage in exposure suggests further as non-

hygienic means of storing drinking water.

Table 4.38: Waterborne diseases’ incidences with respect to storage of

water.

Water Storage System


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Drum 20 45 45 3 15 20 0 25 0

Kolosh 55 84 66 5 21 24 36 67 54

Patil 4 5 80 0 0 0 0 0 0

Water Bottle 22 40 55 2 8 25 17 24 71

(h) Sanitary Practices: Table 4.39 shows the incidences with respect to

sanitation system that the community uses every day.

76


sanitary practices.

Sanitary System


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Sanitary sewer 2 6 34 0 0 0 3 6 50

Septic tank system 32 54 60 1 4 25 19 43 0

Pit latrine 50 81 62 7 28 25 38 52 74

Hanging latrine 7 11 64 0 0 0 1 6 17

Unsanitary 10 22 46 2 12 17 4 9 45

(i) Hygiene Practices: Table 4.40 shows the incidences with respect to hygiene

practices using different hand wash media like soap, ash, soil etc.


hand wash media.

Hygiene Practices- Hand

Wash Media


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Soap 46 84 55 4 14 29 25 61 41

Ash/soil 2 3 67 0 0 0 0 0 0

Nothing 52 85 62 6 30 20 35 55 64

(j) Water Quality: In this study, quantitative analysis of water has been done

using microbiological qualities‟ results i.e. presence of faecal coliform as an

indicator. Table 4.41 shows overall health impacts with respect to faecal coliform

concentration (cfu/100ml).

77

Table 4.41: Overall health impacts based on water quality (FC concentration)

Water Quality (cfu/100ml)


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0-100 18 39 47 3 13 24 4 15 27

100-200 29 46 64 2 6 34 22 32 69

200-300 47 79 60 5 25 20 35 57 62

300-400 7 10 70 0 0 0 4 12 34

(k) Sanitary Inspection (SI): According to the methods described in the Section

3.3.4, a detail risk grading done based on the risk score of each water point and has

been given in Table H.1 of Appendix H. The overall grading of the selected areas,

communities and urban water supply system based on SI risk score have been

given in Table H.2 to Table H.4 of Appendix H. Table 4.42 shows the overall

incidences with respect to SI risk grade.

Table 4.42: Number of waterborne diseases’ incidences with respect to SI

risk grade.

SI Risk Grade


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Medium 37 57 65 3 10 30 18 36 50

High 52 105 50 7 34 21 37 65 57

Very High 12 12 100 0 0 0 10 15 67

4.4.4 Economic Valuation of Diseases

It was revealed that the surveyed population expended the most for diarrhoea,

typhoid and eye infections. Hence for economic valuation, these three waterborne

78

diseases have been considered. During economic valuation, “Cost of illness

approach” of Market based methods has been considered in the calculation.

Accordingly the direct and indirect costs involved were explored as it can be seen in

the Table 4.43 to Table 4.45.

Table 4.43: Cost of waterborne disease- Diarrhoea

Serial No

Description Observation

(No)

Cost of Diarrhoea (Taka)

Mean Std.Dev. Min Max

1. Home treatment 33 227.27 211.86 30.00 1000.00

Transportation 27 107.41 108.93 50.00 600.00

Doctor‟s fee 28 180.71 135.04 30.00 500.00

Medical expenses 33 278.79 146.32 100.00 600.00

Direct cost of Diseases 33 759.39 438.26 230.00 1850.00

2. Parent‟s work lost (when both/either of them is patient)

17 446.61 349.57 131.00 1313.00

Parent‟s work lost due to child disease

33 356.71 253.78 66.00 1225.00

Parent‟s leisure lost due to child disease

32 181.19 140.62 33.00 591.00


33 762.48 479.06 175.00 1772.00

3. Total cost: 1521.88

4. No of Days to suffer: 33 5.03 2.02 3 10

Table 4.44: Cost of waterborne disease- Typhoid

Serial No


(No)

Cost of Typhoid (Taka)

Mean Std.Dev. Min Max

1. Home treatment 7 1107.14 497.01 500.00 2000.00

Transportation 7 235.71 124.88 100.00 500.00

Doctor‟s fee 6 291.67 162.53 150.00 500.00



2. Parent‟s work lost (when both/either of them is patient)

2 1969.20 0.00 1969.00 1969.00


5 805.18 358.66 459.00 1313.00


5 312.88 199.58 153.00 656.00


7 1361.25 715.60 613.00 2626.00

3. Total cost (Taka): 4982.68


Detail calculation of estimated health impact valuation of waterborne diseases has

been given in Appendix K.

79

Table 4.45: Cost of waterborne disease- Eye infections

Serial No


(No)

Costs of Eye Infections (Taka)

Mean Std. Dev.

Min Max

1. Home treatment 14 47.14 21.00 25.00 100.00

Transportation 7 32.86 16.04 20.00 50.00

Doctor‟s fee 8 81.25 54.10 30.00 200.00



2.

Parent‟s work lost (when both/either of them is patient)

20 559.03 327.74 109.00 1072.12


13 279.39 141.84 109.00 459.48


14 110.96 52.35 44.00 229.74

Indirect cost of Diseases 23 711.58 427.98 131.00 1531.60

3. Total cost (Taka): 916.58


4.4.5 Analysis of Prevalence Rate

It has already been discussed in Section 2.10.2 that PR values differ basing on the

value of denominator i.e. total population surveyed. Hence different PR value of

same group could be found out if different denominator value is used. In this study,

prevalence rate for all three major diseases of vulnerable people of different age-

groups and genders have been considered. Moreover attempt has been made to

show the prevalence rate of those diseases among the different communities, areas

and urban water supply options also. The basic data for prevalence rate has been

given in the following tables as Table 4.46 to Table 4.49.

Table 4.46: Basic data for prevalence rate of different age-groups

Age Group (Years)

Gender Surveyed

Population (Number)



Infections

<5 F 16 10 2 3

M 17 5 1 7

5-14 F 20 9 1 8

M 26 18 1 9

>15 F 60 26 3 14

M 71 33 2 24

F 96 45 6 25

M 114 56 4 40

For Entire Sample 210 101 10 65

80

Table 4.47: Basic data for prevalence rate of different community

Community Surveyed

Population



Infections

Slum 117 61 8 42

Low-income 93 40 2 23

Total 210 101 10 65

Table 4.48: Basic data for prevalence rate of different selected areas

Selected Areas Surveyed Population



Gulshan 56 30 3 36

Tejgaon 48 21 2 11

Badda 42 20 3 12

Mirpur 64 30 2 6

Total 210 101 10 65

Table 4.49: Basic data for prevalence rate of different urban water supply

options

Urban Water Supply Options Surveyed

Population



Infections




Total 210 101 10 65

The detail calculation of prevalence rate has been given in Table L.1 through L.6 of

Appendix L, where Table L.1 through L.3 show the prevalence rates of different age-

groups of different genders and Table L.4 to Table L.6 show the prevalence rates of

the different communities, areas and urban water supply options respectively.

81

4.5 Development of Correlation Between Diarrhoea Patient Reproting

Cases and Climatic Factors

4.5.1 Identification of Correlation

Since the diarrhoeal diseases are major concerned as per as waterborne diseases

incidences; hence the monthly average data of 11 years (2000 to 2010) have been

used as given in the Table M.1 of Appendix M. Here, Appendix M has been

developed from the data given in Appendix D and Appendix F. Taking data (from

2000 to 2010) from Appendix D to identify the average state of diarrhoeal incidences

for the selected areas and Dhaka as a whole following Figure 4.12 can be

generated:

Figure 4.12: Trend of diarrhoeal patients of sample area and Dhaka

This 11 years result shows that the surge of patients start from March and ends

around 1st week of June (taking 600 patients as base line) and again starts from

mid of July and ends on October. Following figures i.e. Figure 4.13 through Figure

4.15 show the pattern of both factors.

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Average representative data of Selected Areas

82

Figure 4.13: Diarrhoeal patients of sample area and average rainfall

Figure 4.14: Diarrhoeal patients of sample area and average temperature

Figure 4.15: Diarrhoeal patients of sample area and average humidity

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83

Basing on the figures above, it can be seen that Figure 4.18 i.e. figure representing

diarrhoeal patients of sample area and average temperature is the best suiting.

Now if the climatic factors are plotted against diarrhoeal patients of selected areas

of Dhaka city on scatter chart, following Figure 4.16 through Figure 4.18 will be

found. On the other hand using formula of correlation coefficient in Section 2.11.5

same can be found out for each selected areas of Dhaka city as given in Table 4.50.

Figure 4.16 Diarrhoeal patients-rainfall correlation (2000-2010)

Figure 4.17 Diarrhoeal patients-temperature correlation (2000-2010)

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Figure 4.18 Diarrhoeal patients-humidity correlation (2000-2010)

Hence it is obvious that temperature has better correlation than rainfall and humidity

and hence has direct impact on the diarrhoeal diseases. Calculations of correlation

Table 4.50: Correlation coefficient of climatic parameters and diarrhoeal

incidences of the selected areas

Selected Areas Correlation Coefficient(Cr)

Rainfall Temperature Humidity

Tejgaon 0.306613 0.716571 0.037387

Badda 0.461451 0.712855 0.38716

Gulshan 0.241612 0.633132 0.085564

Mirpur 0.508958 0.81561 0.311589

factor for the generalized data of selected areas and Dhaka city have been given in

the Table M.3 and Table M.4 of Appendix M respectively.

4.5.2 Development of Correlation Equation

After identification of correlation, the correlation equations for temperature with the

selected areas and Dhaka as a whole have been developed. Basing on the data as

given in the Table M.1 of Appendix M, following table shows the acceptance of

equation as developed using Microsoft Excel software:

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Table 4.51: Selection of correlation equation based on correlation

coefficients

Area Linear Non-linear (Logarithmic)

Equation R2 Cr Equation R

2 Cr

Tejgaon y =25.131x - 225.92 0.5135 0.71659 y =10^(0.0292x + 1.8517) 0.6186 0.78651

Badda y = 43.126x - 519.99 0.5082 0.71288 y =10^(0.0346x + 1.8506) 0.6275 0.79215

Gulshan y = 18.794x + 51.775 0.4009 0.63317 y =10^(0.0152x + 2.3295) 0.4548 0.67439

Mirpur y = 77.364x - 1116.6 0.6652 0.8156 y =10^(0.0428x + 1.8067) 0.8249 0.90824

Avg. Study Areas

y = 41.083x - 451.88 0.6393 0.79956 y =10^(0.032x + 1.9392) 0.7507 0.86643

Dhaka y = 19.002x - 136.98 0.5544 0.74458 y =10^(0.0244x + 1.9045) 0.6387 0.79919

From above correlation coefficients, it is understood that the non- linear equations

are better suited than linear equation. As such Figure 4.19 shows result of the

exponential equations of selected areas and Dhaka- developed in terms of equation

lines on the scatter chart using MS Excel software.

Figure 4.19: Average diarrhoeal patients-temperature correlation for study

areas and Dhaka as a whole (2000-2010)

y = 0.032x + 1.9392 R² = 0.7507

y = 0.0244x + 1.9045 R² = 0.6387

2.00

2.20

2.40

2.60

2.80

3.00

3.20

17 19 21 23 25 27 29 31

Log(

Ave

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Temperature (°C)

Avg No. of Patients(Selected Area) Avg No. of Patients(Dhaka)

EQ Line(Selected Area) EQ Line (Dhaka)

86

Equation for the Average Number of Patients of Selected Areas: From the

above figure, Equation 4.1 can be shown for the average number of patients

of selected areas and temperature.

Ysa = 10(0.032x + 1.9392) (4.1)

Where x stands for the temperature in degree and Ysa stands for average

number of patients of the selected areas affected by diarrhoea with a

standard deviation of 183 numbers of patients. Here Ysa has been rounded

up to the next higher number in case of decimal.

Equation for the Average Number of Patients of Dhaka: Again the Equation

4.2 can be shown for the average number of patients of Dhaka and

temperature.

Ydk = 10(0.0244x + 1.9045) (4.2)

Where x stands for the temperature in degree and Ydk stands for average

number of patients of Dhaka affected by diarrhoea with a standard deviation

of 91 numbers of patients. Here Ydk has been rounded up to the next higher

number in case of decimal value.

87

CHAPTER 5

RESULTS AND DISCUSSIONS

5.1 Introduction

In this chapter, the results of the thesis paper have been presented. Initially an

attempt was made to identify the most affected administrative areas of Dhaka city as

per as waterborne diseases are concerned. From there only top four were selected

and data collected from those localities as such. During questionnaire survey the

questions were so chosen in order to ascertain the qualitative assessment of urban

water supply, sanitation and hygiene. Here the qualitative assessment was based

on the number of HH responded to a specific issue. These results are presented in

terms of charts and tables. On the other hand quantitative assessment denotes

health impacts as a result of those factors were counted in terms of number of

incidences taking place last one year. Basing on these results the prevalence rates,

economic valuation were done and presented in charts and tables. It has to be

remembered that selection of administrative areas of Dhaka city were based on the

reported cases/incidences of waterborne diseases; whereas the result based on the

field survey, it was mostly non reporting to hospital and clinic cases- relating with

most common waterborne diseases like diarrhea, typhoid and eye infections .

5.2 Qualitative Assessment

5.2.1 Urban Water Supply Options

This study has identified three types of urban supply options (Table 3.3) mainly

connected by two types of sources. From Table 4.6 it is seen that maximum number

of HHs (65%) had their supplied water of DWASA through private connections and

the rest 35% had their supplied water of DWASA through public connections. No

shallow tubewells were noticed during survey. These public connections also

included some conventional public stand-posts. On the other hand, most of the

private connections were made with unreliable materials like flexible rubber, leaky

PVC or GI pipes for collection of drinking water from DWASA line to their point of

distribution. The photographed images (Image 4.1 to 4.3) showed the extent of

vulnerabilities of visited communities and their state of awareness about health

education or hygiene. Figure 5.1 shows the overall state of the urban water supply

options where it has been revealed that about 47% of HHs are having hand pump

88

connected to supply line, 38% of HHs are having piped water supply without

reservoir and rest 15% HHs are having piped water supply with reservoir. So it was

about 85% of the total HHs those were to rely on uncertain water availability.

Moreover due to poor materials used in hand pump option for connection, there are

more likelihood of various contamination en-route than usual.

Figure 5.1: Overall state of different water supply options

Figure 5.2 shows the overall state of community wise water supply options

Figure 5.2: Community wise state of different water supply options

It shows that slum community is having more percentages of hand pumps

connected to supply line; whereas low-income groups are having piped water supply

15%

37% 48%

Piped water supply with reservoir Piped water supply without reservoir


0%

20%

40%

60%

80%

100%

Supplied waterthrough private

connection.

Supplied waterthrough public

connection

Supplied waterthrough private

connection.

Supplied waterthrough public

connection/Tapwater

Slum Low in-comePiped water supply with reservoir Piped water supply without reservoir


89

without reservoir. This also shows the state of vulnerability in terms of contamination

associated with slum community using hand pump option and in terms of non-

availability of water with slum and low-income communities.

5.2.2 Distance of Water Source and Time Require to Fetch Water

From Table 4.9 and 4.10, it can be seen that maximum percentage (77%) of the

surveyed HHs were residing very close (<50 m) to the sources thus taking very less

time (around 5 minutes) to fetch water. On the other hand, basing on the urban

water supply options, it can be seen that 79% hand pumps connected to supply line

were located closer to <50m distance. The slum community was to travel maximum

distance to fetch water than that of low-income and spending longer time for this

case. Taking longer time includes journey time, queue time and collection time of

water from the source. When large number of populations sharing the same water

point then the time spent in queue was more than that of journey time. This was

observed for slum community residing at Gulshan area. The Figure 5.3 to 5.5 shows

the state of community type, urban water supply options and overall condition

against the distance from HH to source.

Figure 5.3: Community wise different distance range between households and

water source.

0%

20%

40%

60%

80%

100%

Slum Low-income

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(%

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Community Type

<50m <100 (50-100)m <250 (100-250) m

90

Figure 5.4: Urban water supply options wise different distance range between

households and water source.

Figure 5.5: Overall state of different distance range between households and

water source.

5.2.3 Quantity and Accessibility to Water

From Table 4.12 and Figure 5.6, it is evident that slum community had less quantity

and less accessibility to water. On the other hand, Figure 5.7 shows that the HHs

having hand pump connected to WASA lines got less water than their expected

demand. Other options i.e. piped water supply with and without reservoir had mixed

demand mitigation. However Figure 5.8 shows the overall condition of the state of

the quantity of water the communities were having every day. It is seen that 95% of

HHs never had their demand fulfilled out of which only 55% could mitigate their daily

need by just half of their demand. Only 5% showed their fulfillment of their demand

as per as water availability are concerned.

02468

101214161820

Piped water supply withreservoir

Piped water supplywithout reservoir

Hand pump connectedto supply line

Nu

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of H

H


<50m <100 (50-100)m <250 (100-250) m

77%

8% 15%

<50m <100 (50-100)m <250 (100-250) m

91

Figure 5.6: State of different water demand against community type

Figure 5.7: State of different water demand against urban water supply options

Figure 5.8: Overall state of different water demand fulfillment

0%

20%

40%

60%

80%

100%

Slum Low-income

Num

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of

HH

s

Community Type

Full/As per demand 75% of demand 50% of demand

0%

20%

40%

60%

80%

100%


Piped water supply withoutreservoir

Hand pump connected tosupply line

Nu

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)

Water Demand


5%

40% 55%


92

5.2.4 Water Boiling Practices

During interview it was found that though the communities were aware of boiling of

water and its effect in maintaining good health but due to economic reason

especially the slum people avoid boiling of water. Based on such information of

Table 4.14, the Figure 5.9 clearly shows the state of boiling practices among the

communities. Again the low-income community has mixed proportion of boiling

water. Figure 5.9 shows that 76% of low-income HHs boil water for drinking

purpose. Since duration of boiling of water plays a vital role in ensuring proper home

treatment of water. The Table 4.15 shows the distribution of this group (13 HHs)

against different time range used for boiling purpose. It shows that there were about

31% of low-income HHs who boiled water for 5-15 minutes and rest 69% of HHs

who boiled water for 15-30 minutes. No HHs were found boiling water more than 30

minutes. Table 4.17 and Figure 5.10 show area wise distribution of HHs practicing

boiling. It shows that more than 90% of HHs residing at Gulshan area, 80% of HHs

at Tejgaon, 50% of HHs at Badda and 40% of HHs at Mirpur did not boil water.

Figure 5.9: Community wise percentages of HHs having water boiling

practices

Figure 5.11 shows the overall state of the water boiling practices as prevailing within

the community. It is evident from this state that large number of people (68%) do not

boil their water for drinking purpose though they already aware about the

consequences. However because of the economic reason they avoid doing that

practices at home.

0%

20%

40%

60%

80%

100%

Slum Low-income

Nu

mb

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of

HH

s (%

)

Community Type

Yes No

93

Figure 5.10: Sample area wise state of water boiling practices by HHs.

Figure 5.11: Overall state of water boiling practices observed in the study area

5.2.5 Storage of Water

As it has been discussed that this study identified mainly 4 types of storage

container like drum, kolosh, patil and water bottle. From Table 4.16 it was shown

55% of HHs alone accounted for kolosh type storage system as it can be seen in

the Figure 5.12 below also. Figure 5.13 shows the pattern of water storage system

maintained by the vulnerable communities. It shows that low-income community

(82%) stored their water mostly in kolosh but slum community stored their water

equally in drum (35%), kolosh (35%) and water bottle (30%).

0%

20%

40%

60%

80%

100%


HH

Nu

mb

er

Sample Areas

Yes No

32%

68%

Yes No

94

Figure 5.12: Overall state of different water storage system

During survey, it was observed that though the containers were covered by the lids

but drums and water bottle were maintained poorly. Slums were often found putting

the utensils like mug, jug etc. inside their drums without washing those properly in

order to take water. Those practices could be detrimental in keeping good health.

Figure 5.13: Community wise number of HHs for different water storage

system

Figure 5.14 shows the sample area wise distribution of HHs for different water

storage system. It shows that in Gulshan, the use of drum, Kolosh and water bottle

were more or less equal in proportion. But for the rest 3 areas, it was the Kolosh

which were used extensively in their respective areas.

22%

55%

3%

20%

Drum Kolosh Patil Water Bottle

0%

20%

40%

60%

80%

100%

Slum Low-income

Nu

mb

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of

HH

s

Community Type


95

Figure 5.14: Sample area wise number of HHs for different water storage

system

5.2.6 Sanitation Systems

Table 4.19 shows the type of sanitary practices observed within the communities of

the study areas. It is evident from the table that slum community had more pit latrine

system (64%) where low-income community based on septic tank system (67%).

However a substantial number of slum HHs were found to be using hanging and

unsanitary latrines. On the other hand Figure 5.15 shows area wise distribution of

Figure 5.15: Distribution of HHs according to sample area based on sanitation

system in use.

0%

20%

40%

60%

80%

100%


Nu

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Hs

Sample Area

Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary

0%

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100%


Nu

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s

Sample Area


96

sanitation system. It shows that 92% of HHs at Gulshan, 30% of HHs at Tejgaon

and 40% at Mirpur used pit latrine system. On the other hand, there were almost

equal percentage of HHs using septic tank system in Tejgaon (50%), Badda (50%)

and Mirpur (40%). There were about 25% HHs of Badda found defecating in the

field (unsanitary system). Figure 5.16 shows the overall state of sanitary practices in

the sample area. It shows that about 45% of the population depended on community

based pit latrine sanitation system followed by septic tank system (32%). On the

other hand, about 13% of surveyed population went for unsanitary system and very

small portion (5%) were using sanitary sewer and hanging latrine system.

Figure 5.16: Overall state of sanitary practices in the sample area.

5.2.7 Hygiene Practices-Use of Hand Wash Medium

Table 4.21 and Figure 5.17 show that a large number of people (48%) used nothing

after defecation which shows the lack of hygiene education among the community

members. Again Figure 5.18 shows the community wise state of the hygiene

practices. It shows that 83% of slum HHs did not use any media to wash their

hands, on the contrary 100% low-income HHs were found very much aware about

use of media (in this case soap). Figure 5.19 shows the area wise state of the

hygiene practices. It was found that 83% of HHs of Gulshan and 50% of Badda did

not use any medium to wash their hands in order to maintain good health.

5%

32%

45%

5% 13%


97

Figure 5.17: Overall state of hygiene practices

Figure 5.18: Community wise distribution of HHs based on hand wash media.

Figure 5.19: Sample area wise distribution of HHs based on hand wash

medium.

0%

20%

40%

60%

80%

100%


Nu

mb

er

of

HH

s

Sample Area

Soap Ash/Soil Nothing

50%

2%

48%

Soap Ash/Soil Nothing

0%

20%

40%

60%

80%

100%

Slum Low-income

Nu

mb

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of

HH

s

Community Type

Nothing Ash/Soil Soap

98

5.2.8 Water Quality of Collected Samples

(a) Aesthetic Water Quality: From Table 4.13 it is seen the communities of

different areas were facing different kind of aesthetic water qualities. While

communities at Tejgaon (70%) and Badda (75%) complained their water to be

odorous but the communities at Gulshan (50%) and Mirpur (40%) were experiencing

water mixed with foreign materials. Again from Figure 5.20, it is seen that the water

collected by slum community was often contained dirt/foreign materials but the

water collected by low income group were often odorous water. As per as urban

water supply options, the 67% of hand pumps connected to supply line provided

occasional odorous water to the community; whereas 61% of .piped water supply

without reservoir provided water with dirt/foreign materials. Figure 5.21 shows the

overall state of aesthetic quality of water of study area. It shows that 44% of the HHs

were experiencing occasional odorous water and 33% of the HHs were

experiencing dirt/foreign materials.

Figure 5.20: Community wise percentages of households reporting the

aesthetic quality of water.

0%

20%

40%

60%

80%

100%

Slum Low-income

Nu

mb

er

of

HH

Re

po

rtin

g (%

)

Community Type

Clean and fresh Odorous Turbid Contains dirts and other foreign matterials

99

Figure 5.21: Overall state of aesthetic quality of water of study area

(b) Physical Parameters:

Turbidity

The turbidity of all water samples tested was within the Bangladesh Standard of

10 NTU, with a median value of 1.00 NTU and maximum value of 2.91 NTU.

pH

From the Appendix I, it can be seen that pH of the tested water samples varied

from 6.10 to 7.84. There are about five samples (21%) have pH value less than

6.5. The mean value, median value and standard deviation are 6.82, 6.78 and

0.45 respectively. These standard values were nearly satisfying the Bangladesh

Standard of 6.5 to 8.5. pH distribution of the water points are given in the Figure

5.22 and 5.23.

Figure 5.22: pH distribution of the water sample of different communities

17%

45%

5%

33%

Clean and fresh Odorous Turbid Contains dirts and other foreign matterials

0%

10%

20%

30%

40%

50%

60%

<6.0 6.0-6.5 6.5-7.0 7.0-7.5 7.5-8.0 8.0-8.5

% o

f Fr

eq

ue

ncy

pH Range

Slum Low-income

100

Figure 5.23: pH distribution of the water sample of different areas

(c) Chemical Parameter:

Chlorine (Residual)

The concentration of chlorine was tested to check the adequacy of the chlorine

level to safeguard against potential microbial contamination in the distribution

network. If the chlorine level is more than 0.05 mg/l for a contact period of 10-20

minutes, it would be effective in killing pathogen (Ahmed and Rahman, 2000).

There are about eleven samples (46%) those have chlorine values less than

0.05mg/l and there are fourteen samples (58%) those have chlorine value less

than the Bangladesh Standard i.e. 0.2 mg /l. Improper chlorination done at deep

tubewell pump locations could be the major reasons for these large percentage

of non-availability of chlorine at the delivery end. It can be seen from Appendix I

that chlorine of the tested water samples varied from 0.01 mg/l to 1.02 mg/l. The

mean value, median value and standard deviation are 0.30, 0.16 and 0.35 mg/l

respectively.

(d) Microbiological Quality: As discussed in Section 4.4.2. that excluding

DWASA pump house water samples, other samples contained varying degree FC

concentration and maximum (67%) shown in the range of 100-300 cfu/100ml. Figure

5.24 shows the percentage exceeding the stated values for the different

communities. It shows, e.g. at the FC concentration of 100 cfu/100ml, while the slum

has 77% of its samples exceeding the given concentration; low-income group has

0%

20%

40%

60%

80%

100%

<6.0 6.0-6.5 6.5-7.0 7.0-7.5 7.5-8.0 8.0-8.5

% o

f Fr

eq

ue

ncy

pH Range


101

91% of its samples exceeding the stated concentration. Figure O.3 of Appendix O

shows the FC concentration in selected areas.

Figure 5.24: Microbial water qualities of water supply in different communities

5.2.9 Sanitary Inspection (SI)

From H.1 of Appendix H, the overall condition of the water point including the

WGWSPs can be seen in the Figure 5.25. It is clearly understood that more than

50% of the water points were not sanitarily in sound condition, indicating poor

maintenance, a very low level hygiene awareness and a very high level potential

threat of water related diseases to the communities using those. Again from the

Figure 5.25: State of overall SI risk grading of water points of study area.

Table 4.25 and Figure 5.26, it is seen that slum water points were more vulnerable

and susceptible to source related contamination than low-income community and

likely to have more incidences of waterborne diseases. Figure 5.27 generated from

Table H2 of Appendix H shows the overall SI grading of the community.

11%

37% 45%

7%

Low Medium High Very High

0

20

40

60

80

100

0 100 200 300 400

% E

xcee

din

g th

e st

ate

d F

C

cou

nt

FC Count (cfu/100ml)

Slum Low-income

102

Figure 5.26: Comparative state of communities based on SI risk grading.

Figure 5.27: Overall state of communities based on SI risk grading.

Similarly Figure 5.28 shows that it was Gulshan area which is the most vulnerable

area followed by Mirpur, Tejgaon and Badda respectively. This was also seen in the

Figure 5.29 shows the overall SI grading of the selected areas.

Figure 5.28: Comparative state of vulnerable areas based on SI risk grading.

0%

20%

40%

60%

80%

100%

Slum Low-income

Wat

er

Po

int

Co

vera

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Community Type

Medium High Very High

7

5.7

0

2

4

6

8

10

Slum Low-income

Gra

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Community Type

0%

20%

40%

60%

80%

100%


Wat

er

Po

int

Co

vera

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Sample Area


103

Figure 5.29: Overall state of selected areas based on SI risk grading.

On the other hand, in Figure 5.30 shows the water points having both urban water

supply options like hand pump connected to supply line and piped water supply

without reservoir possess high percentage of high grade coverage indicating low

level maintenance at the source by the user group. Both the options have very little

differences in risk grading as can be seen in the Figure 5.31.

Figure 5.30: Comparative state of urban water supply options based on SI risk

grading.

7.50

6.10 5.80 6.30

0

1

2

3

4

5

6

7

8

9

10


Gra

de

d R

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Sco

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Sample Area

0%

20%

40%

60%

80%

100%




Wat

er

Po

int

Co

vera

ge

Urban Water Supply Options Medium High Very High

104

Figure 5.31 Overall state of urban water supply options based on SI risk

grading.

5.3 Quantitative Assessment

In the Figure 5.32 shows the overall state of the affected and non-affected persons

of the study area. It was found out that about 58%, 23% and 56% of HH members

were affected by diarrhoea, typhoid and eye infections respectively. Figure 5.33

shows the gender distribution of the affected persons. It represents that male were

more vulnerable to the waterborne diseases. This could be that male were away

from houses and consumed water and food from unreliable sources.

Figure 5.32: Overall state of waterborne diseases of interviewed households

4.78

6.65 6.71

0

1

2

3

4

5

6

7

8

9

10




Gra

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0%

10%

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30%

40%

50%

60%

70%

80%

90%

100%


Nu

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Inci

de

ncs

Affected Not Affected

105

Figure 5.33: Gender distributions of the affected persons

Figure 5.34 shows gender wise age-group diarrhoeal incidences. Here it is seen that

female children <5 years suffer from diarrhoea just double than male percentage.

Gender difference in the family could be one of the main reasons where female

children (<5 years) are not equally taken care by their parents of vulnerable

communities. On the contrary male group of age more than 5 years had more

Figure 5.34: Comparison between male and female diarrhoeal incidences

vulnerability than female of same age group. This could be that male children are

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


% o

f In

cid

en

ces

Diseases

Female (F) Male (M)

10%

9%

26%

5%

18%

32%

Female (45%) Male (55%)

<5 Years 5-14 Years >15 Years

106

more susceptible than female due to their nature of activities/works and had more

contact with external food and contaminated environment.

Within the age-groups of both genders, it is seen that the elderly people (> 15 years)

suffer much. These can be seen in the following Figure 5.35 (a-1,a-2 and a-3):

Figure 5.35 State of different gender age-groups for waterborne diseases

a-2

a-3

a-1

107

Health impacts with respect to each factor as described in the Section 4.4.3 have

been given in Appendix N in details. Basing on the assessment following overall

evaluation can be made:

5.3.1 Overall Evaluation on Health Impacts

(a) Community Wise: From the Table J.1 of Appendix J, the combined

vulnerability score as found for the community can be seen in the Figure 5.36. It

shows that the state of vulnerability for slum is more than that of low-income

community. Figure 5.37 points out that incase of diarrhoea incidences, the slum

community entered into the high vulnerability zones (≥ 6 to <8) due to the SI risk,

Figure 5.36: Overall vulnerability of communities

water quality and time duration to fetch water from the source. It means that these

are the most critical issues those needed to be addressed by improving water point

5.83 5.61

1.42 1.67

6.67

4.34

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

Slum Low-incomeCo

mb

ine

d V

uln

era

bil

tiy S

co

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Community


108

R² = 0.9831

R² = 0.9838

0

10

20

30

40

50

0% 25% 50% 75% 100%

Nu

mb

er

of

Inci

de

nce

s

Demand to meet

Slum Low-income Linear (Slum) Linear (Low-income)

Figure 5.37: State of vulnerability of communities based on diarrhoea

incidences

sanitation, replacing of illegal connection between sources and WASA lines with

authorized lines, making easily accessible and adequate water supply to the

community. Same way for the low-income community, sources of water, urban

water supply options, demand of water, boiling practices including time and storage

practices etc. are to be taken care to improve their health and sanitation. It is

evident that slum community had less quantity and less accessibility to water. As a

result when supplied water quantity increased, the diarrhoea incidences were found

to be decreased and their negative correlations for both slum and low-income

community have been given in Figure 5.38. On the other hand, a positive correlation

Figure 5.38: Correlation between demand and number of diarhoea incidences.

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Criteria

Slum Low-income

109

(r2 = 0.7419) was found between FC count and diarrhoea incidences in percentage

as shown in the Figure 5.39.

Figure 5.39: Correlation between FC count and diarrhoea incidences in percentage.

For typhoid, in Figure 5.40, the slum community vulnerability score is low but still

needed to stress the following points like connections of sources of water,

Figure 5.40: State of vulnerability of communities based on typhoid

incidences

accessibility of water, storage practices, hand wash practices and sanitation of

water points. On the other hand low-income community needs to be very careful

about connections of water of sources, accessibility of water, boiling of water

R² = 0.7419

0

20

40

60

80

100

0 100 200 300 400 500

% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

0.5

1

1.5

2

2.5

Vu

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Criteria

Slum Low-income

110

practices, hygiene practices and water point sanitation. Figure 5.41 shows the

vulnerability for eye infections for both communities. It clearly indicates that slum

Figure 5.41: State of vulnerability of communities based on eye infections

incidences

community was at the very disadvantageous stage. Due to water sources‟

connection, vulnerable water supply option used, distance between source and HH,

demand, water quality and water point sanitation all these factors pushed this

community into the high vulnerability zones. Apart from personal contact, since eye

infection is depended on the quantity and quality of water used by an individual,

hence those critical issues to be improved in order to reduce the disease. Figure

5.42 shows such correlation (Cr = 0.99) between FC concentration and number of

Figure 5.42: Correlation between SI risk score and percentage of eye

infections’ incidences against exposures.

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Slum Low-income

R² = 0.9897

20

40

60

80

0 1 2 3 4

% o

f in

cid

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gain

st

Exp

osu

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Grade on Risk Score

111

eye infections‟ incidences. On the other hand low-income community was exposed

to medium vulnerability range mostly due to high incidence rate of eye infections

with respect to urban water supply system. Now, if all the scores are summed up

then the cumulative vulnerability scores will be as Figure 5.43.

Figure 5.43: The order of community based on cumulative vulnerability scores

(b) Selected Areas Wise: From the Table J.2 of Appendix J, the combined

vulnerability score as found for the areas can be seen in the Figure 5.44.

Figure 5.44: Overall vulnerability of selected areas of Dhaka city

0.00

5.00

10.00

15.00

Slum Low-incomeCu

mu

lati

ve V

uln

erab

ility

Sc

ore

s


6.55 7.01

3.64

5.57

0.94 0.68 0.80 1.67

8.93

5.38

2.51 2.19

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112

It shows that the state of vulnerability for Tejgaon and Gulshan are more than those

of Mirpur and Badda. Figure 5.45 points out that incase of diarrhoea incidences,

Tejgaon and Gulshan entered into the high vulnerability zones (≥ 6 to <8) due to

various reasons like water source‟s connection, urban supply options, distance and

Figure 5.45: State of vulnerability of selected areas based on diarrhoea

incidences

time to fetch water, boiling practices, hand wash practices, water quality and SI risk.

While Gulshan was having problem related with accessibility and adequacy of

water, storage and water point sanitation related issues; Tejgaon suffered more

importantly with demand, boiling practices and water quality. Again the state of

MIrpur was different as the community living there, having problem related with

urban water supply options, storage systems and water point sanitation. Again for

typhoid, Mirpur was suffering much due to inadequate boiling practices, poor

personal hygiene and water point sanitation as it can be seen Figure 5.46.

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113

Figure 5.46: State of vulnerability of selected areas based on typhoid

incidences

For eye infections, the communities residing at Gulshan were extremely exposed to

the vulnerable state. The Figure 5.47 shows very high vulnerability score for

Figure 5.47: State of vulnerability of selected areas based on eye infections

incidences

Gulshan while high for Tejgaon. Figure O.7 to Figure O.9 of Appendix O shows

vulnerability state of selected areas according to waterborne diseases. If all the

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1.5

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114

vulnerability were summed up the results became Figure 5.48 which indicates the

order of vulnerability for the selected areas.

Figure 5.48: The order of selected areas based on cumulative vulnerability

scores

(c) Urban Water Supply Options Wise: From the Table J.3 of Appendix J, the

combined vulnerability score as found for the urban water supply options can be

seen in the Figure 5.49.

Figure 5.49: Overall vulnerability of urban water supply options

It shows that the combined vulnerability scores for diarrhoea with respect to „Hand

pump connected to supply line‟ and „Piped water supply with reservoir‟ are in the

high range. Figure 5.50 points out causes of those increases in details. It is clearly

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

Gulshan Tejgaon Badda MirpurCu

mu

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6.05 5.65

6.45

2.00 1.29

7.04

5.04 5.29

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00




Co

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115

evident that for „Piped water supply with reservoir‟, time to fetch water, demand,

boiling practices, sanitary practices and water quality etc. are major concerns as per

Figure 5.50: State of vulnerability of urban water supply options based on

diarrhoea incidences

as diarrhoea is concerned. On the other hand for „Piped water supply without

reservoir‟, demand, storage practices, sanitary practices, water quality and SI risk

Figure 5.51: State of vulnerability of urban water supply options based on

typhoid incidences

are the major concerned. Again the community using „Hand pump connected to

supply line‟ system, distance and time to fetch water, boiling practices with certain

0

0.5

1

1.5

2

2.5

3

3.5

Vu

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rab

ility

Sco

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Piped water supply with reservoir Piped water supply without reservoir


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Piped water supply with reservoir Piped water supply without reservoirHand pump connected to supply line

116

duration, hand wash practices , water quality and water point related SI risk etc. are

the major concerned. Figure 5.52 clearly indicating the case of eye infections for

Figure 5.52: State of vulnerability of urban water supply options based on eye

infections incidences.

those who are using “Piped water supply with reservoir‟. Poor maintenance of the

reservoir could be another cause of such results. Now, if all the vulnerability were

summed up then results can be shown in Figure 5.53.

Figure 5.53: The order of urban water supply system options based on

cumulative vulnerability scores

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00




Cu

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Vu

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Criteria

Piped water supply with reservoir Piped water supply without reservoirHand pump connected to supply line

117

5.4 Evaluation on Estimated Health Impact Valuation of Waterborne

Diseases

From Table 4.43 it is seen that out of forty HHs, thirty three HHs (83%) had suffered

from diarrhoea. Each non-reported diarrhoea incidence remains on average for 5.03

days with standard deviation of 2.02 days. The direct, indirect and total costs were

Tk. 759.4, Tk. 762.48 and Tk. 1521.88 respectively. During survey, it was found that

minimum and maximum numbers of days suffered by the population were 3 days

and 10 days respectively. On the other hand, Table 4.44 shows that out of forty

HHs, only seven HHs (18%) had suffered from typhoid. Each incidence remains on

average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and

total costs were about Tk. 3621.43, Tk. 1361.25 and Tk. 4982.68 respectively. In

case of Typhoid, it was found that minimum and maximum numbers of days

suffered by the population were 7 days and 30 days respectively. It was observed

that the home treatment and medical expenditure of typhoid incidence were the

most expensive and higher than both diarrhoea and eye infections.

Table 4.45 shows that out of forty HHs, twenty three HHs (58%) had suffered from

eye infections. Each incidence remains on average for 6.3 days with standard

deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 711.58

and Tk. 916.58 respectively. The indirect cost is about 2.5 times more than that of

direct cost and it is because the individual remain absent from his work place due to

contagious nature of the disease. During survey, it was found that minimum and

maximum numbers of days suffered by the population were 3 days and 10 days

respectively.

Hence the total cost of diseases for last one year found from Table K.1 of Appendix

K for the selected areas are 149,892,036.19 Tk. (using incidence rate against

exposure) and 87,138,383.05 Tk. (using prevalence rate of community type). This

difference has come from very high incidence rate at smaller HHs size.

According to LGED (2005) report, the estimated total cost of non-reporting

waterborne diseases of slum areas of entire Dhaka city was 1,756,718,564 Tk. or

26,188,410 USD (exchange rate 1$ = 67.08 Tk. for 2005-06). But now, according to

BBS (2011) census and media report those amount is expected to be more than

5,653,819,097 Tk. or 81,726,208 USD (exchange rate 1$ = 69.18 Tk. for 2009-

10). Figure 5.54 shows the comparison between the cost of non-reporting selected

118

waterborne diseases and revised Gross Domestic Product (GDP) at current price

and GDP at constant price for the year 2009-10 (BBS 2010).

Figure 5.54: Comparison between the cost of non-reporting waterborne

diseases, GDP at current price and GDP at constant price (2009-10).

5.5 Evaluation of Prevalence Rate

It has already been discussed in Section 3.3.5 about the different use of formulas.

From Appendix L, following results can be shown in Figure 5.55:

Figure 5.55: Prevalence rate of waterborne diseases.

Above figure shows that vulnerable people are more susceptible to the diarrhoea

than those of eye infections and typhoid. This could be because of diarrhoea takes

6,923,795 3,600,465

5,653

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

GDP in current price(2009-10)

GDP in constant price(2009-10)

Estimated SelectedDisease Cost

Mill

ion

Tak

a

480.95

47.62

309.52

0

100

200

300

400

500

600


Pre

vale

nce R

ate

(in

1000)

Waterborne Diseases

119

place not only as a result of water usage but also due to contaminated food intake.

On the other hand Figure 5.56 shows the state of PR values of different genders:

Figure 5.56: The state of PR values of different genders

It shows that males are more vulnerable to diarrhoea and eye infections than those

of female. It is because of rate of involvement by male with outside environment is

more than that of female counter part. If the data is further analyzed according to

age-groups than it can be seen in Figure 5.57 that the PR values of female children

under five are much higher than those of male children. It gives us an insight that

female children are more neglected due to gender issue at this level. On the other

Figure 5.57: The State of PR values of different age-groups of different

genders suffering from diarrhoea.

214.29

28.57

119.05

266.67

19.05

190.48

1

10

100

1000


PR

TP

Female(F) Male(M)

625.00 294.12

450.00 692.31 433.33 464.79

104.17

43.86

93.75 157.89

270.83 289.47

47.62 23.81

42.86

85.71 123.81 157.14

1

10

100

1000

F M F M F M

<5 5-14 >15

Pre

vale

nce

Rat

e

Age-Group

PRIG PRGT PRTP

120

hand, for children between 5-14 years, male children suffer more than female. This

is because at this stage male children of vulnerable community start involving

themselves in various unhygienic activities like scavenging in order to help their

respective family. However the PR for elderly male people (15 years) is little more

than female thus signifies about their same state of vulnerability in their job. Figure

5.58 shows the different age-groups suffering typhoid. Here the female prevalence


genders suffering from typhoid

rates against total population (PRTP) below 5 years and above 15 years were more

than those of males. On the other hand, Figure 5.59 shows the different age-groups

suffering eye infections. Here male prevalence rates were more than female.


genders suffering from eye infections

125.00

58.82 50.00 38.46 50.00 28.17

20.83

8.77 10.42 8.77

31.25 17.54

9.52 4.76 4.76 4.76

14.29 9.52

1

10

100

1000

F M F M F M

<5 5-14 >15

Pre

va

len

ce

Ra

te

Age-Group

PRIG PRGT PRTP

187.50

411.76 400.00 346.15 233.33

338.03

31.25 61.40

83.33 78.95 145.83

210.53

14.29

33.33 38.10 42.86 66.67

114.29

1

10

100

1000

F M F M F M

<5 5-14 >15

Pre

va

len

ce R

ate

Age-Group PRIG PRGT PRTP

121

Table L.4 to Table L.6 show the different PR values for community, selected areas

and urban water supply options respectively. Very high PR values for slum, Gulshan

area and “Hand pump connected to supply line” are found.

5.6 Correlation Between Diarrhoea Patient Reproting Cases and Climatic

Factors

Basing on the Equation 4.1 and 4.2 as developed in the Section 4.5.2, projected

data of diarrhoeal patients for both selected areas and Dhaka have been given in

the Table M.5 of Appendix M and presented in the Figure 5.60 and Figure 5.61.

Figure 5.60: Projected average diarrhoeal patients of study areas based on temperature

Figure 5.61: Projected average diarrhoeal patients of Dhaka based on temperature

0

100

200

300

400

500

600

700

800

900

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40Av

era

ge N

um

ber

of

Pati

en

ts

Temperature (°C)

Average Nos. Lower bound Higher bound

0

500

1000

1500

2000

18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Av

era

ge

Nu

mb

er

of

Pati

en

ts

Temperature (°C)

Average Nos. Lower bound Higher bound

122

Figure 5.62 shows that during surge periods the record of average “monthly average

maximum temperature” of 21 years (1990-2010) and 11 years (2000-2010) both

were same i.e. 33.8°C (in April) and 32.0°C (in September). It was found that during

2000-2010, the average patients reported in those two months were within the

bound drawn. It was again observed from 21 years‟ (1990-2010) records that the

monthly average maximum temperature raised up to 36.4 °C in April of 1995 and up

to 33.8 °C in September of 1996 respectively.

Figure 5.62: Average maximum temperature profile at different time range

Hence using the correlation formula, the results of likely diarrhoeal incidences and

actually reported have been given in the Table 5.1. Since there were no monthly

Table 5.1: Number of likely and actual diarrhoeal Incidences with respect

to temperature

Temperature (°C)

Selected Areas Dhaka

Number of Likely Diarrhoeal Incidences

Actual Avg.

Reported (2000-2010)

Number of Likely Diarrhoeal Incidences

Actual Avg.

Reported (2000-2010)

Average Nos.

Lower bound

Higher bound

Average Nos.

Lower bound

Higher bound

32.0 919 736 1102 763 485 394 576 400

33.8 1050 867 1233 975 537 446 628 550

36.4 1271 1088 1454 - 621 530 712 -

data available before 2000, hence actual average reported cases have been kept

blank.

26.9

31.2

34.8

36.4 35.1

34.5 32.8

32.7

33.8

33.1

30.7

28.0

24.0

26.0

28.0

30.0

32.0

34.0

36.0

38.0


Tem

pera

ture

(°C

)

Month

Max Avg. (1990-2010)

Max Avg. (2000-2010)

Max Temperature Recorded (1990-2010)

123

5.7 GIS Representation of Relevant Data In Thematic Maps

Thematic maps based on different themes provide quick planning tools for decision

makers and planners. In this thesis paper, the relevant data has been collected from

Appendix G through Appendix J and processed those data using GIS software like

ArcGIS Catalogue and ArcGIS Map and finally representing them in different

thematic maps in Appendix O.

In Figure O.1 of Appendix O, the distribution of DTWs and water bodies around the

selected areas of Dhaka city have been shown which otherwise will allow to identify

the available water sources and their relative impacts on neighborhood habitats.

Figure O.2 has shown the distribution of 27 water sample points from where water

were collected and tested and Figure O.3 has shown the FC concentration at the

respective sources thus pin pointing the most vulnerable source in the selected

areas. Again the sample point wise incidences‟ state of waterborne diseases have

been shown in Figure O.4 to Figure O.6 and the vulnerability state of the

communities at different selected areas have been shown in Figure O.7 through

Figure O.9 of Appendix O.

124

CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

6.1 Conclusions

Due to Rapid urbanization and unplanned population growth of Dhaka city, the

facilities of an ideal metropolitan city are declining every day; environmental

degradation notably water pollution is taking place too fast to cope with. The

evidence from the literature consistently points to use of water as being important to

controlling disease and the fact that lack of access to water may impede its use and

thereby adversely affect health. But at present the only public water providing

organization - DWASA is facing various challenges both for quantity and quality of

water. Moreover it could hardly provide adequate and wholesome water to the

vulnerable communities who are human capital greatly contributing to the economy

and work force of Dhaka city.

The main objective of this thesis was to find out the health impacts of urban water

supply on the vulnerable communities of selected areas of Dhaka city. Major

conclusions from this study are summarized below:

The vulnerable community composed of people (73%) mainly from other districts

coming for economic reason.

There is a bimodal distribution of the patients of waterborne diseases for Dhaka city

with maximum number of patients reported immediate before and during the wet

season.

It was found that about 58%, 23% and 56% of HH members were affected by

diarrhoea, typhoid and eye infections respectively for last one year. According to

gender, it was seen that male were more vulnerable to the waterborne diseases

than those of female. It was also seen that female children <5 years (10%) suffer

from diarrhoea just double than male percentage (5%). Gender difference in the

family could be one of the main reasons.

125

It was seen that maximum number of HHs (65%) of vulnerable communities had

their supplied water of DWASA through private connections and the rest 35% had

their supplied water of DWASA through public connections. A high percentage of

diarrhoeal (74%), typhoid (60%) and eye infections (77%) incidences in case of

private connections were reported. This was because of the most of the private

connections (mostly for slum community) were made with sub-standard materials

and connecting pipes were leaky and drawn over the waste and wet lands.

Majority of vulnerable communities‟ HHs (47%) were having “Hand pump connected

to supply line”, 38% of HHs were having “Piped water supply without reservoir” and

rest 15% HHs were having “Piped water supply with reservoir”. So it was about 85%

(47%+38%) of the total HHs those were to rely on unsecured water availability.

Maximum slum community (61%) had hand pump connected to supply line with

private connection using sub-standard material. On the other hand maximum low-

income community (53%) had piped water supply without reservoir. It was found

that 53% of the total diarrhoeal incidences, 60% of the total typhoid incidences and

51% of the total eye infections incidences were alone from “Hand pump connected

to supply line” urban water supply option. But when percentage of exposure was

taken in consideration then it was seen that 91% of eye infections and 65% of

diarrhoeal incidences had come from “Piped water supply with reservoir”. Low level

maintenance of the reservoir could be one of the main reasons of such result.

Maximum percentage (77%) of the surveyed HHs were residing very close (<50 m)

to the sources thus taking very less time (around 5 minutes) to fetch water. On the

other hand, basing on the urban water supply options, 79% hand pumps connected

to supply line were located closer to <50m distance. The slum community (35%)

was to travel maximum distance to fetch water than that of low-income (6%).

Community residing at Gulshan, Tejgaon and Mirpur were to travel more. As per

exposure, for the longer the distance and time for collecting water, the more the

possibilities to be affected by the waterborne diseases. This could be conservative

use of water due to longer distance of water source from the HHs.

Overall 95% of HHs never had their demand fulfilled out of which only 55% could

mitigate their daily need by just half of their demand. Only 5% showed their

fulfillment of their demand as per as water availability are concerned. Slum people

126

had never their demand fulfilled rather maximum of them (74%) had 50% of their

demand fulfilled. On the other hand low-income community had better accessibility

of water (only 29% HHs had 50% demand of water fulfilled). Maximum HHs (55%)

having hand pump connected to supply line received only 50% of their demand of

water. Gulshan area (31%) faced maximum water scarcity, followed by Tejgaon and

Mirpur. However a negative correlation found between the quantities (demand) of

water with the number of diarrhoea incidences. Less accessibility to water might

force users to use contaminated water.

Overall 68% of HHs did not boil water for drinking purpose. However there was 76%

of low-income HHs who boiled water for drinking purpose but nil for slum. There

were about 31% of low-income HHs who boiled water for 5-15 minutes and rest

69% of HHs who boiled water for 15-30 minutes. No HHs were found boiling water

more than 30 minutes. 90% of HHs residing at Gulshan area, 80% of HHs at

Tejgaon, 50% of HHs at Badda and 40% of HHs at Mirpur did not boil water. Even

after boiling, poor hygiene practices in regard to storing, maintaining and even

associated with other factors like taking outside food from unhygienic places etc.

might be involved for high percentages of incidences.

This study identified mainly 4 types of storage container like drum, kolosh, patil and

water bottle. It was shown 55% of HHs alone accounted for kolosh type storage

system. The low-income community (82%) stored their water mostly in kolosh but

slum community stored their water equally in drum (35%), kolosh (35%) and water

bottle(30%). As per as storage of water was concerned, patil was not a good choice

for storing water since it produced the highest (80%) diarrhoeal incidences against

exposure. It was because it remained open and method of using water to and from it

was not hygienic.

Overall 45% of the population depended on community based pit latrine sanitation

system followed by septic tank system (32%). On the other hand, about 13% of

surveyed population went for unsanitary system and very small portion (5%) were

using sanitary sewer and hanging latrine system. The slum community had more pit

latrine system (64%) where low-income community based on septic tank system

(67%). 92% of HHs at Gulshan, 30% of HHs at Tejgaon and 40% at Mirpur used pit

latrine system. There were about 25% HHs of Badda found defecating in the field

127

(unsanitary system). High percentages of diarrhoeal and eye infections incidences

even after using sanitary options indicated low level personal hygiene and lack of

awareness about the consequences.

A large number (48%) of people of vulnerable community used nothing after

defecation which showed the lack of hygiene education among the community

members. It showed that 83% of slum HHs did not use any media to wash their

hands, on the contrary 100% low-income HHs were found very much aware about

use of media (in this case soap). It was found that 83% of HHs residing at Gulshan

and 50% at Badda did not use any medium to wash their hands in order to maintain

good health. Moreover a good number of people being affected by diarrhoea (55%)

and eye infections (41%), though they used the medium like soap. This could be the

result of improper rubbing of hands with medium used and/or effect of other

associated factors.

Overall state of aesthetic quality of water showed that 44% of the HHs were

experiencing occasional odorous water and 33% of the HHs were experiencing

water mixed with dirt/foreign materials. Communities at Tejgaon (70%) and Badda

(75%) complained their water to be odorous but the communities at Gulshan (50%)

and Mirpur (40%) were experiencing water mixed with foreign materials.

The physical parameters like turbidity was found within the Bangladesh Standard.

The pH values of samples were nearly satisfying the Bangladesh Standard of 6.5 to

8.5.

There were about 46% of samples those have chlorine values less than 0.05mg/l

and there were 58% of samples those have chlorine value less than the Bangladesh

Standard i.e. 0.2 mg /l.

Overall 89% samples were containing varying degree FC concentration and

maximum (67%) shown in the range of 100-300 cfu/100ml. A high level

concentration of FC found in “Piped water supply without reservoir” and followed by

“Hand pump connected to supply line”. A linear correlation (r2 = 0.7419) was found

between FC count and diarrhoea incidences in percentage against exposure.

Percentage of incidences for slum was high at higher level of FC concentration

128

(>200 cfu/100ml) whereas low-income community was found at lower concentration

(<200 cfu/100ml). Faecal coliform concentration was relatively more than that of

low-income community because the water carrying pipes by latter did not pass over

the wasteland and again the back ground level of immunity could be another reason

of this kind of result. Percentage of incidences for Gulshan and Mirpur were high at

higher level of FC concentration (>200 cfu/100ml) whereas Tejgaon and Badda

were high at lower concentration (<200 cfu/100ml). Percentage of incidences for

“Piped water supply with reservoir” was high at higher level of FC concentration

(>200 cfu/100ml) whereas “Piped water supply without reservoir” and “Hand pump

connected to supply line” were found high at lower concentration (<200 cfu/100ml).

During sanitary inspection it was found 7% very high, 45% high, 37% medium and

11% low risk grade associated with the water points. Based on SI Risk Grading, it

was clearly evident that slum water points were more vulnerable (SI risk score=7)

and susceptible to source related contamination than low-income community (SI risk

score=5.7). A linear correlation (r2= 0.9897) has been found between SI risk grade

and eye infections incidences against exposure in percentage. Again it was Gulshan

area (SI risk score=7.50 ) which is the most vulnerable area followed by Mirpur (SI

risk score=6.30), Tejgaon (SI risk score=6.10)and Badda(SI risk score=5.80)

respectively. As per as urban water supply options were concerned, the order

showed here are hand pumps connected to supply line(SI risk score=6.71), Piped

water supply without reservoir (SI risk score=6.65), Piped water supply with

reservoir(SI risk score=4.78).

Overall vulnerability of communities indicate that slum (Cumulative score =13.95)

had higher combined vulnerability scores for diarrhoea (CVSdiarrhoea = 5.86) and eye

infections (CVSeye infections = 6.67) than those of low-income community (Cumulative

score =11.59 ; CVSdiarrhoea = 5.58 and CVSeye infections = 4.34). However low-income

community had higher typhoid (CVStyphoid = 1.67) score than those of slum

community (CVStyphoid = 1.42).

Overall vulnerability of selected areas indicate that Gulshan area (Cumulative score

=16.42; CVSdiarrhoea = 6.55, CVStyphoid = 0.94 and CVSeye infections = 8.93) is the most

vulnerable area, followed by Tejgaon (Cumulative score =13.07; CVSdiarrhoea = 7.01,

129

CVStyphoid = 0.68 and CVSeye infections = 5.38), Mirpur (Cumulative score =9.43;

CVSdiarrhoea = 5.57, CVStyphoid = 1.67 and CVSeye infections = 2.19), and Badda

(Cumulative score =6.95; CVSdiarrhoea = 3.64, CVStyphoid = 0.80 and CVSeye infections =

2.51).

Overall vulnerability of urban water supply options indicate that high vulnerability

score against diarrhoea (CVSdiarrhoea = 6.45) for „Hand pump connected to supply

line‟, against typhoid (CVStyphoid = 2.00) for „Piped water supply without reservoir‟

and against eye infections (CVSeye infections = 7.04) for „Piped water supply with

reservoir‟. However overall „Piped water supply with reservoir‟ was the most

vulnerable option (cumulative score =13.09) followed by „Hand pump connected to

supply line‟ (cumulative score =13.03) and „Piped water supply without reservoir‟

(cumulative score =12.69).

Each non-reported diarrhoea incidence remains on average for 5.03 days with

standard deviation of 2.02 days. The direct, indirect and total costs were Tk. 759.39,

Tk. 762.48 and Tk. 1521.88 respectively. Again each typhoid incidence remains on

average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and

total costs were about Tk. 3621.43, Tk. 1361.25 and Tk. 4982.68 respectively.

Finally eye infections‟ incidence remains on average for 6.3 days with standard

deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 711.58

and Tk. 916.58 respectively. The indirect cost is about 2.5 times more than that of

direct cost and it is because the individual remain absent from his work place due to

contagious nature of the disease. The total cost of diseases for selected areas is

from 87,138,383.05 Tk. to 149,892,036.19 Tk. and for slum areas of whole Dhaka

city is 5,653,819,097.66 Tk. or 81,726,208.41 USD.

There is an exponential correlation (CrSA= 0.866; CrDC=0.799) exist between number

of diarrhoea incidences of reporting cases with temperature of Dhaka city.

The thesis has pointed out that vulnerable people are more susceptible to the

diarrhoea (PRdiarrhoea = 480.95) than those of eye infections (PReye infections = 309.52)

and typhoid (PRtyphoid = 47.62). This could be - because of diarrhoea takes place not

only as a result of water usage but also due to contaminated food intake. Again it

was the males who were more vulnerable to diarrhoea (PRdiarrhoea = 266.67) and eye

130

infections (PReye infections = 190.48) than those of female. It is because the rate of

involvement by male with outside environment is more than that of female counter

part. The PR values of female children (PRdiarrhoea = 47.62 and PRtyphoid = 9.52) under

five are much higher than those of male children (PRdiarrhoea = 23.81 and PRtyphoid =

4.72). It gives us an insight that female children are more neglected due to gender

issue at this level. Moreover very high value of PR found for slum (PRdiarrhoea =

290.48, PRtyphoid = 38.10, PReye infections = 200.00) than low-income (PRdiarrhoea = 190.48,

PRtyphoid = 9.52, PReye infections = 109.52) community; for Gulshan area (PRdiarrhoea =

142.86, PRtyphoid = 14.29, PReye infections = 171.43) than other areas and “Hand pump

connect to supply line” (PRdiarrhoea = 257.14, PRtyphoid = 28.57, PReye infections = 157.14)

than other supply options.

6.2 Recommendations

In this study, due to high authenticity and rich data availability, the selection of areas

of Dhaka city was done based on the data of ICDDR,B only. However data from

other sources like DSH, Dhaka Medical College etc. could be synthesized in order

to find out exact state of Dhaka city.

Primary data collection time was from July 2010 to October 2010 (2nd peak) basing

on the bimodal distribution curve as developed using secondary data of ICDDR,B.

Data collected round the year would augment the analysis in future.

A suitable water safety plan could be developed according to geographical locations

and implemented on the communities and urban water supply systems based on the

findings of 12 factors used.

A comprehensive study can be made in future to check the correctness of the

correlation found between the demands of water with the number of non-reporting

diarrhoea incidences and between SI risk grades with eye infections incidences.

In future, a feasibility study can be undertaken to develop a forecasting tool using

correlation equation found between diarrhoea incidences of reporting cases with

temperature of Dhaka city.

131

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Appendix A: QUESTIONNAIRES SURVEY FORM

Household Information Date:

Name: Sex: F M

Age: -----------Yrs. -------------months Occupation:

Address:

House No: Street: Ward (DCC) No:

Thana/Zone:

1. Are you from Dhaka City?

Yes No

2. If no, from where and when (please mention year) did you come to Dhaka? 3. What is the source of your water?

Supplied water through private connection.

Supplied water through public connection/Tape water.

Pond/lake/river water.

Well

4. What is the distance of water point from your house?

<50 metre

<100 (50-100) metre

<250 (100-250) metre

<500 (250-500) metre

>500 metre

5. How much time do you take to collect water from the source? 6. How much water do you receive everyday?

Full/As per demand 75% of Demand 50% of Demand 25% of Demand

Other ( _____% of Demand)

7. What is the general condition of supplied water?

Clean and fresh Odorous Turbid

136

Contains dirts and other foreign matterials

Other (mention):

8. Do you boil your drinking water?

Yes Partial No

9. How much time you boil your drinking water?

5-15 minutes 15-30 minutes > 30 minutes

10. Where do you store your drinking water? 11. What is the cost of your container to store the water? 12. Do you use lid to cover your container? If so what is the price of the lid? 13. What do you use to boil water?

Gas (Sufficient supply/ At par/ Not sufficient)

Electricity (Sufficient supply/ At par/ Not sufficient)

Tree wood/leaves (Sufficient supply/ At par/ Not sufficient)

Other (mention)(Sufficient supply/ At par/ Not sufficient):

14. How much hours you get electricity round the day?

3-4 hrs

11-15 hrs

5-10 hrs

>15 hrs

15. What do you use to wash your hands after defecation and before having main

meals?

Soap Soil Ash Nothing

16. How many family members do you have?

Member’s Age range Sex Number

< 5 Years F

M

5-14 years F

M

> 15 years F

M

Total:

17. What type of Sanitation System you use?

Sanitary sewer Septic tank system Pit

latrine

Unsanitar

yHanging latrine

137

18. How many members of your family suffered from following diseases last one yr:

Member’s Age

range Sex Dysentery

Diarrhoea /Cholera

Typhoid

Other waterborne diseases(skin rash, eye rash, stomach ache

etc.)

< 5 Years F

M

5-14 years F

M

> 15 years F

M

19. What is the general incidence rate of following diseases?

Dysentery Diarrhoea /Cholera

Typhoid

Other waterborne diseases

Every day / week / month/ year




20. Did anybody die due to the above diseases last five years (mention the year)? 21. How many family members were hospitalized during last one yr?

Member’s Age range

Sex

Number of Family Members Hospitalized


Typhoid Other

waterborne diseases

< 5 Years

F

M

5-14 years

F

M

> 15 years

F

M

22. Where do you hospitalize (name the hospital/clinic/health complex etc) your family members during aforesaid diseases.

ICDDR,B DSH PG/BSMMU DMC Other (mention):

138

23. How much money (average) you are to expend for each time?

Home treatment:_________________Tk. (These are for extra fooding and/or

nursing)

Transportation Cost:_______________________Tk. (For

doctor/clinic/hospital/purchasing medicine at a long distance etc.)

Doctor's Fees:____________________Tk. ( Single doctor visit

charge:___________Tk)

Medical Expenses:____________________Tk. (These are expended after

visiting doctor)

Hospitalization Expenses:____________________Tk.(if any)

24. How many days (average no of days) required recovering from each case?


Typhoid

Other waterborne diseases

25. How much parents’ work-time are lost (i.e. if both/either of them is sick)? 26. How much parents’ work-time are lost in each case (i.e. parents are away from

work place due to look after of family members)? 27. How much parents’ leisure-time are lost in each case (i.e. parents could not take

rest for the diseases)? 28. How much money does your family earn per month altogether?

<3,000 Tk. 3,000-6,000 Tk. 6,000-10,000 Tk. >10,000 Tk.

139

Appendix B: SANITARY INSPECTION FORMS

(Piped water supply with reservoir)

Date of Survey:

Water Supply Option:

Community Type:

Ward No:

Water Point No: Water samples taken? …….. Sample Nos. ………

Lat: Long:

RISK QUESTIONS

Ser Risk Questions Risk

1. Is there any hanging/pit latrine within 10m of the water supply option?

Y/N

2. Is there any other source of faecal pollution 10m of the water supply option?

Y/N

3. Is there any visible leak in the water supply system from street main to underground reservoir near the collection point?

Y/N

4. Is there any visible leak in the water supply system from UGR to OHR?

Y/N

5. Is the tape loose /missing/faulty at the connection point? Y/N

6. Is there any visible crack on the underground reservoir? Y/N

7. Is there drainage system near the water points faulty inundating the area?

Y/N

8. Is there any way to contaminate the UGR from septic tank? Y/N

9. Is there any collection of water on the UGR from faulty drainage?

Y/N

10. Is there any visible sign of dirt, insects in the UGR/OHR? Y/N

Total Score of Risks ..../10

Comments:

140

SANITARY INSPECTION FORMS (Piped water supply without reservoir)

Date of Survey:


Community Type:

Ward No:


Lat: Long:

RISK QUESTIONS



Y/N


Y/N

3. Is there any visible leak in the water supply system from street main to underground reservoir near the collection point?

Y/N

4. If water is collected by flexible rubber, PVC pipes does it go over dirty areas (waste dump, wasteland etc)?

Y/N

5. Is the tape loose /missing/faulty at the connection point? Y/N


Y/N

7. Is the platform slope not properly designed facilitating poor drainage?

Y/N

8. Are the water collecting containers seen dirty? Y/N

9. Does the community lack hygiene practices? Y/N

10. Do the people reserve water temporarily in containers like drums?

Y/N

Total Score of Risks ..../10

Comments:

141

SANITARY INSPECTION FORMS (Hand pump connected to supply line/STW)

Date of Survey:


Community Type:

Ward No:


Lat: Long:

RISK QUESTIONS



Y/N


Y/N

3. Are there cracks in the platform supporting infiltration of dirty water?

Y/N

4. Is the platform slope not properly designed facilitating poor drainage?

Y/N

5. Is the handpump loose /missing/faulty at the connection point? Y/N


Y/N

7. Does the pump water go down and the community use dirty water for priming?

Y/N

8. Are the water collecting containers seen dirty? Y/N

9. Does the community lack hygiene practices? Y/N

10. Do the people reserve water temporarily in containers like drums?

Y/N

Total Score

Comments:

142

Appendix C: 15 YEARS (1996-2010) AVERAGED DIARROHEAL PATIENTS REPORTED

Table C.1: Average Number of Diarrhoeal Patients Reported to ICDDR,B (1996-2010)

Serial DMPA Thana Count Original Numbers

<5 Yrs 5-14 Yrs 15+ Yrs Total <5 Yrs 5-14 Yrs 15+ Yrs Total

1 Kotawali 23 5 28 56 1150 250 1400 2800

2 Sutrapur 34 7 29 70 1700 350 1450 3500

3 Motijheel 60 9 40 109 3000 450 2000 5450

4 Ramna 24 3 22 49 1200 150 1100 2450

5 Lalbag 51 10 48 109 2550 500 2400 5450

6 Shyampur 30 6 27 63 1500 300 1350 3150

7 Demra 102 17 62 181 5100 850 3100 9050

8 Shabujbag 37 5 24 66 1850 250 1200 3300

9 Dhanmondi 16 2 15 33 800 100 750 1650

10 Hazaribag 13 3 10 26 650 150 500 1300

11 Kamrangirchar 16 3 12 31 800 150 600 1550

12 Khilgaon 42 8 33 83 2100 400 1650 4150

13 Tejgaon 50 7 45 102 2500 350 2250 5100

14 Mohammadpur 46 10 43 99 2300 500 2150 4950

15 Badda 73 10 57 140 3650 500 2850 7000

16 Gulshan 83 13 62 158 4150 650 3100 7900

17 Kafrul 21 4 22 47 1050 200 1100 2350

18 Mirpur 99 18 102 219 4950 900 5100 10950

19 Uttara 35 6 30 71 1750 300 1500 3550

20 Cantonment 18 3 13 34 900 150 650 1700

21 Pallabi 10 3 15 28 500 150 750 1400

Source: ICDDR,B (2010) Notes:

1 x Count = 50 X patients reporting. So, 0 in any year does not necessarily mean “No(Nil)” patients reporting that year.

Upto 59 months = “<5 Yrs”, 60 to 179 months = “ 5-14 Yrs” and from 180 months = “15+ Yrs” have been considered.

Report based on earlier 21 thanas; No data on new divisions of thanas were maintained by ICDDR,B during the study time.

143

Appendix D: 11 YEARS MONTHLY AVERAGE (2000-2010) DIARRHOEAL PATIENTS REPORTED Table D.1: 11 Years’ Monthly Average (2000-2010) Diarrhoeal Patients Reported to ICDDR,B

Year Ser DMPA Thana Month Total


11 Y

ears

(20

00-2

010)

Avera

ge

1 Kotawali 150 200 200 400 300 150 200 250 250 350 200 150 2800

2 Sutrapur 150 200 300 450 350 300 300 250 300 300 200 200 3300

3 Motijheel 200 200 350 450 300 250 200 350 350 200 200 150 3200

4 Ramna 150 100 250 400 300 200 200 200 250 200 150 100 2500

5 Lalbag 250 250 450 550 450 250 400 450 400 300 350 200 4300

6 Shyampur 100 150 350 450 350 300 350 300 300 250 150 200 3250

7 Demra 500 450 800 1000 800 500 650 800 600 650 500 450 7700

8 Shabujbag 100 200 250 300 250 250 400 600 350 250 200 200 3350

9 Dhanmondi 100 100 150 250 150 200 150 150 100 150 100 100 1700

10 Hazaribag 100 50 100 200 150 100 200 100 150 150 100 50 1450

11 Kamrangirchar 100 100 200 150 200 150 100 150 100 150 150 150 1700

12 Khilgaon 250 250 450 450 350 300 350 650 500 300 250 250 4350

13 Tejgaon 250 300 600 650 400 350 450 550 500 450 400 250 5150

14 Mohammadpur 250 200 550 650 600 300 400 600 600 550 300 250 5250

15 Badda 300 350 600 800 700 450 550 1100 800 600 600 400 7250

16 Gulshan 450 450 550 800 600 450 500 650 600 550 500 400 6500

17 Kafrul 150 100 250 350 300 200 200 200 250 250 150 200 2600

18 Mirpur 450 500 850 1650 1150 950 850 1200 1150 900 650 500 10800

19 Uttara 250 200 300 400 400 350 300 300 300 400 250 350 3800

20 Cantonment 100 100 100 100 150 100 100 100 100 100 100 50 1200

21 Pallabi 50 100 150 150 200 150 150 200 100 100 150 100 1600

Average representative data of Dhaka City

250 250 400 550 450 300 350 450 400 350 300 250 4300

Average representative data of Selected Areas

363 400 650 975 713 550 588 875 763 625 538 388 7425

Source: ICDDR,B (2010)

144

Appendix E: THANAWISE ESTIMATED POPULATION OF DHAKA CITY FOR THE YEAR OF 2010 Table E.1: For the year of 2010

Serial Name Area

(Sq Km)

*BASE YEAR- 2001 Estimated Population

Pf=Pp(1+r)n Male Population

Female Population

Total Population (Pp)

1 Badda 49.85 198000 161000 359000 606523

2 Cantonment 14.36 70000 48000 118000 199359

3 Demra 31.1 238000 190000 428000 723097

4 Dhanmondi 6.23 147000 106000 253000 427439

5 Gulshan 10.29 107000 83000 190000 321002

6 Hazaribag 5.89 71000 57000 128000 216254

7 Kafrul 8.85 157000 133000 290000 489949

8 Kamrangirchar 3.68 76000 67000 143000 241596

9 Khilgaon 20.26 185000 152000 337000 569355

10 Kotawali 1.93 162000 92000 254000 429128

11 Lalbag 4.08 206000 140000 346000 584560

12 Mirpur 14.22 301000 250000 551000 930903

13 Mohammadpur 12.14 251000 205000 456000 770403

14 Motijheel 4.95 162000 108000 270000 456160

15 Pallabi 17.96 232000 200000 432000 729855

16 Ramna 7.71 149000 109000 258000 435886

17 Shabujbag 6.74 318000 131000 449000 758577

18 Shyampur 10.94 211000 165000 376000 635245

19 Sutrapur 3.99 206000 147000 353000 596387

20 Tejgaon 8.89 174000 128000 302000 510223

21 Uttara 58.85 188000 157000 345000 582871

*Source: BBS (2010)

145

Appendix F: DATA OF SELECTED CLIMATIC FACTORS FOR DHAKA STATION Table F.1: Average monthly data of climatic factors

Climatic Factors

Month


Average Rainfall (mm ) (2000-2010)

6 17.2 61.6 120.9 258.4 379.1 415.4 307.2 357.4 193.0 26.5 5.5

Average Humidity ( % ) (2000-2010)

69.4 61.0 59.0 69.0 72.9 80.0 81.0 80.0 81.0 77.0 71.0 71.0

Average Temperature (0C) (1990-2010)

Max 24.7 28.2 32.2 33.8 33.3 32.5 31.7 32.0 32.0 31.6 29.5 26.4

Avg 18.5 22.0 26.2 28.5 28.8 29.0 28.7 29.0 28.6 27.4 24.0 20.1

Min 13.2 16.4 20.8 23.8 24.8 26.1 26.2 26.4 25.8 23.9 19.5 14.9

Average Temperature (0C ) (2000-2010)

Max 24.5 28.2 32.1 33.8 33.6 32.4 31.8 32.1 32.0 31.4 29.4 26.3

Avg 18.7 22.3 26.4 28.7 29.0 28.9 28.8 29.1 28.7 27.5 24.2 20.5

Min 13.6 16.9 21.1 24.1 24.8 26.0 26.1 26.3 25.7 24.0 19.6 15.7

Max. Temperature (0C) Recorded (1990-2010)

26.9 31.2 34.8 36.4 35.1 34.5 32.8 32.7 33.8 33.1 30.7 28.0

Source: BMD (2010)

146

Appendix G: RELEVANT DATA FROM QUESTIONNAIRES SURVEY

Table G.1: Relevant data of QSF

Seri

al o

f H

ou

seh

old

(H

H)

No

of

Fam

ily M

em

be

rs p

er

HH

No

of

pers

on

s i

n a

clu

ste

r

bein

g d

ire

ctl

y e

xp

osed

fo

r ea

ch

sam

ple

No

of

pers

on

s b

ein

g e

xp

osed

co

veri

ng

wh

ole

are

a f

or

sam

e

kin

d o

f w

ate

r

Th

an

a

Co

mm

un

ity t

yp

e

Ho

w m

uch

wate

r o

f d

em

an

d d

o

yo

u r

ec

eiv

e e

very

day?

Do

yo

u b

oil y

ou

r d

rin

kin

g

wate

r?

Wh

at

do

yo

u u

se t

o w

ash

yo

ur

han

ds a

fter

defe

cati

on

an

d

befo

re h

av

ing

main

meals

?

Wh

at

typ

e o

f S

an

itati

on

yo

u

use?

TO

TA

L A

ffecte

d b

y D

iarr

ho

ea

To

tal D

ire

ct

Co

st

for

Dia

rrh

oea

per

ep

iso

de

To

tal In

dir

ect

Co

st

of

Dia

rrh

oea

TO

TA

L A

ffecte

d b

y T

yp

ho

id

To

tal D

ire

ct

Co

st

for

Typ

ho

id

per

ep

iso

de

To

tal In

dir

ect

Co

st

of

Typ

ho

id

TO

TA

L A

ffecte

d b

y E

ye

Infe

cti

on

s

To

tal D

ire

ct

Co

st

for

Eye

Infe

cti

on

s p

er

ep

iso

de

To

tal In

dir

ect

Co

st

of

Ey

e

Infe

cti

on

s

1 6 100 100 Badda Slum. 50% N Nothing Unsanitary 2 700 385 1 7601 350 1 100 210

2 6 100 100 Badda Slum. 50% N Nothing Unsanitary 1 900 100 1 2852 175

3 7 35 2500 Badda Low income 75% Y Soap Septic tank 2 1850 150 2 300 250

4 3 40 2500 Badda Low income 50% Y Soap Sanitary sewer 1 1400 140 1 300 180

5 3 25 2500 Badda Low income 75% Y Soap Sanitary sewer 1 700 150 2 170 140

6 4 100 2000 Badda Slum. 50% N Nothing Septic tank 4 300 75 1 4706 300 1 265 30

7 5 100 2000 Badda Slum. 50% N Nothing Septic tank 1 450 125 1 175 50

8 8 100 1000 Badda Low income 50% Y Soap Septic tank 8 830 385 4 135 315

9 6 35 5500 Gulshan Slum. 75% N Nothing Pit latrine 6 850 455 6 200 385

10 3 35 5500 Gulshan Slum. 50% N Nothing Pit latrine 3 300 245

11 3 50 2000 Gulshan Slum. 75% N Nothing Unsanitary 1 650 240 3 125 250

12 6 60 2000 Gulshan Slum. 75% N Soap Pit latrine 6 200 315

13 5 10 1500 Gulshan Low income 50% Y Soap Pit latrine 2 850 120







20 5 100 500 Gulshan Slum. 50% N Nothing Pit latrine 4 650 385 1 4120 210 5 270 210

147

Seri

al o

f H

ou

seh

old

(H

H)

No

of

Fam

ily M

em

be

rs p

er

HH

No

of

pers

on

s i

n a

clu

ste

r b

ein

g

dir

ectl

y e

xp

os

ed

fo

r e

ach

sam

ple

No

of

pers

on

s b

ein

g e

xp

osed

co

veri

ng

wh

ole

are

a f

or

sam

e

kin

d o

f w

ate

r

Th

an

a

Co

mm

un

ity t

yp

e

Ho

w m

uch

wate

r d

o y

ou

receiv

e

every

da

y?

Do

yo

u b

oil y

ou

r d

rin

kin

g

wate

r?

Wh

at

do

yo

u u

se t

o w

ash

yo

ur

han

ds a

fter

defe

cati

on

an

d

befo

re h

av

ing

main

meals

?

Wh

at

typ

e o

f S

an

itati

on

yo

u

use?

TO

TA

L A

ffecte

d b

y D

iarr

ho

ea

To

tal D

ire

ct

Co

st

for

Dia

rrh

oea

per

ep

iso

de

To

tal In

dir

ect

Co

st

of

Dia

rrh

oea

TO

TA

L A

ffecte

d b

y T

yp

ho

id

To

tal D

ire

ct

Co

st

for

Typ

ho

id

per

ep

iso

de

To

tal In

dir

ect

Co

st

of

Typ

ho

id

TO

TA

L A

ffecte

d b

y E

ye

Infe

cti

on

s

To

tal D

ire

ct

Co

st

for

Eye

Infe

cti

on

s p

er

ep

iso

de

To

tal In

dir

ect

Co

st

of

Ey

e

Infe

cti

on

s

21 6 16 2500 Mirpur Low income 100% Y Soap Pit latrine 2 2521 300

22 15 100 1000 Mirpur Low income 50% Y Soap Septic tank 8 450 60

23 5 50 5000 Mirpur Slum. 50% N Nothing Hanging latrine 1 400 420

24 10 10 1000 Mirpur Slum. 50% N Soap Pit latrine 4 650 75 1 50 175


26 4 50 500 Mirpur Slum. 50% N Nothing Pit latrine 3 500 350 1 170 140

27 5 50 500 Mirpur Low income 50% Y Soap Pit latrine 4 450 120



30 6 50 1000 Mirpur Slum. 50% N Nothing Hanging latrine 6 450 120 1 225 100

31 5 20 500 Tejgaon Slum. 50% N Ash Pit latrine 3 800 240

32 6 20 500 Tejgaon Low income 75% N Soap Septic tank 2 200 70

33 8 25 250 Tejgaon Slum. 75% N Soap Pit latrine 2 1500 540 2 1733 450

34 5 20 250 Tejgaon Low income 100% N Soap Pit latrine 5 1300 420 3 200 210

35 6 35 400 Tejgaon Low income 75% Y Soap Septic tank

36 4 35 400 Tejgaon Low income 75% Y Soap Septic tank 4 1200 90 3 200 140



39 5 100 2500 Tejgaon Slum. 50% N Nothing Unsanitary 5 250 150

40 2 100 2500 Tejgaon Slum. 50% N Nothing Unsanitary 1 420 200

210 2651 67500 101 25060 7075 10 26170 2535 65 4715 4095

148

Appendix H: ANALYSIS OF SANITARY INSPECTION (SI) DATA Table H.1: Details of risk scores obtained during SI

Serial Thana

Ward

No

.

Place Name Community

Type Water Supply Option

Total Score of

Risks./10 Grade

1 Badda 2 Pasher Teck, Notun Bazar Slum Hand pump connected to supply line/STW 8 High

2 Badda 6 Shufi Sharoni Low-income Piped water supply without reservoir 6 High

3 Badda 8 Eid Gah Low-income Hand pump connected to supply line/STW 4 Medium

4 Badda 21 shha/60 Shadhinata Sharoni Low-income Hand pump connected to supply line/STW 5 Medium

5 Badda 5 CocaCola Tag Bari Slum Hand pump connected to supply line/STW 4 Medium

6 Badda 6 CocaCola Munshi Bari Low-income Hand pump connected to supply line/STW 6 High

7 Gulshan 20 IPS Bosti Slum Hand pump connected to supply line/STW 9 Very High

8 Gulshan 19 Beltola Bosti Slum Piped water supply without reservoir 8 High

9 Gulshan 19 Korail Bosti Low-income Piped water supply without reservoir 5 Medium

10 Gulshan 14 Gulshan Rd-18 Slum Piped water supply without reservoir 8 High

11 Gulshan 20 IPS Bosti Slum Hand pump connected to supply line/STW 8 High

12 Gulshan 20 T & T Bosti Slum Piped water supply with reservoir 4 Medium

13 Mirpur 12 Kalwalapara WGWSP WASA Ground Water Supply Pump 0 Low

14 Mirpur 12 Kalwalapara Slum Piped water supply without reservoir 4 Medium

15 Mirpur 12 Shalibag Low-income Piped water supply with reservoir 7 High

16 Mirpur 41 Agargaon Bosti Slum Piped water supply with reservoir 3 Medium

17 Mirpur 4 Purba Baishteki, Mirpur-13 Slum Hand pump connected to supply line/STW 8 High

18 Mirpur 7 Section 1 Low-income Piped water supply without reservoir 3 Medium

19 Mirpur 7 Section 1 Low-income Piped water supply without reservoir 6 High

20 Mirpur 7 Section 1 Slum Piped water supply without reservoir 9 Very High

21 Tejgaon 39 East Nakhal Para Slum Hand pump connected to supply line/STW 4 Medium

22 Tejgaon 37 Colony Bazar WGWSP WASA Ground Water Supply Pump 0 Low

23 Tejgaon 37 Lalmat Slum Hand pump connected to supply line/STW 7 High

24 Tejgaon 40 Panthapath WGWSP WASA Ground Water Supply Pump 0 Low

25 Tejgaon 50 South Panthapath Low-income Piped water supply without reservoir 8 High

26 Tejgaon 37 SOB Low-income Piped water supply with reservoir 4 Medium

27 Tejgaon 37 South Begunbari(Master Bari) Low-income Piped water supply without reservoir 6 High

149

Table H.2: Overall grading of vulnerable communities

Serial Community

Type

Total Score of Risks.

(Out of 10)

ix

Grade

Point

iy

Total Grade Point

ii yx

n

i

i

n

i

ii

y

yx

GPA

1

1 Grade

1

Slum

8 3 24

7 High

2 4 2 8

3 9 4 36

4 8 3 24

5 8 3 24

6 8 3 24

7 4 2 8

8 4 2 8

9 3 2 6

10 8 3 24

11 9 4 36

12 4 2 8

13 7 3 21

Total: 36 251

14

Low-income

6 3 18

5.7 Medium

15 4 2 8

16 5 2 10

17 6 3 18

18 5 2 10

19 7 3 21

20 3 2 6

21 6 3 18

22 8 3 24

23 4 2 8

24 6 3 18

Total: 28 159

150

Table H.3: Overall grading of selected areas

Thana Serial Community

Type


(Out of 10)

ix

Grade

Point

iy

Total Grade

Point

ii yx

n

i

i

n

i

ii

y

yx

GPA

1

1 Grade

Badda

1 Slum 8 3 24

5.8 Medium

2 Low-income 6 3 18

3 Low-income 4 2 8

4 Low-income 5 2 10

5 Slum 4 2 8

6 Low-income 6 3 18

Total: 15 86

Gulshan

7 Slum 9 4 36

7.5 High

8 Slum 8 3 24

9 Low-income 5 2 10

10 Slum 8 3 24

11 Slum 8 3 24

12 Slum 4 2 8

Total: 17 126

Mirpur

13 Slum 4 2 8

6.3 High

14 Low-income 7 3 21

15 Slum 3 2 6

16 Slum 8 3 24

17 Low-income 3 2 6


19 Slum 9 4 36

Total: 19 119

Tejgaon

20 Slum 4 2 8

6.1

High

21 Slum 7 3 21


23 Low-income 4 2 8


Total: 13 79

151

Table H.4: Overall grading of urban water supply options

Serial Water Supply Option


(Out of 10)

ix

Grade Point

iy

Total Grade

Point

ii yx

n

i

i

n

i

ii

y

yx

GPA

1

1 Grade

1


7 3 21

4.78 Medium

2 4 2 8

3 3 2 6

4 4 2 8

Total: 9 43

4


4 2 8

6.65 High

5 8 3 24

6 8 3 24

7 5 2 10

8 8 3 24

9 6 3 18

10 6 3 18

11 3 2 6

12 6 3 18

13 9 4 36

Total: 28 186

14


4 2 8

6.71 High

15 7 3 21

16 9 4 36

17 8 3 24

18 4 2 8

19 5 2 10

20 8 3 24

21 8 3 24

22 4 2 8

23 6 3 18

Total: 27 181

152

Appendix I: ANALYSIS OF WATER QUALITY OF SELECTED AREAS Table I.1: Water quality of sample areas water

Th

an

a

Wa

ter

Po

int

No

Co

mm

un

ity

Ty

pe

Water Supply Option Color

(Pt-co) Odor

Turbidity(NTU)

pH Chlorine -Residual

(mg/l)

FC

(cfu

/10

0m

l)

Badda 15 Slum Hand pump connected to supply line 14.8 N 0.48 6.87 0.03 270

Badda 16 Low-income Piped water supply without reservoir 15 N 1.10 7.10 0.02 230

Badda 17 Low-income Hand pump connected to supply line 13.2 N 0.64 6.91 0.02 170

Badda 18 Low-income Hand pump connected to supply line 2 N 0.90 7.00 0.57 120

Badda 23 Slum Hand pump connected to supply line 1 N 1.00 6.67 0.88 80

Badda 24 Low-income Hand pump connected to supply line 2 N 1.00 6.66 0.6 170

Gulshan 10 Slum Hand pump connected to supply line 11 N 1.65 6.64 0.03 275

Gulshan 11 Slum Piped water supply without reservoir 34 N 0.71 6.81 0.18 150

Gulshan 12 Low-income Piped water supply without reservoir 22 N 0.49 6.71 0.94 70

Gulshan 14 Slum Piped water supply without reservoir 15.9 N 0.59 6.75 1.02 70

Gulshan 21 Slum Hand pump connected to supply line 1 N 1.00 6.62 0.01 220

Gulshan 22 Slum Piped water supply with reservoir 1 N 1.00 7.20 0.02 220

Mirpur 2 Slum Piped water supply without reservoir no color N 2.55 6.72 0.26 135

Mirpur 3 Low-income Piped water supply with reservoir no color N 1.05 7.18 0.17 150

Mirpur 13 Slum Piped water supply with reservoir no color N 1.06 7.12 0.28 150

Mirpur 19 Slum Hand pump connected to supply line 4 N 0.95 6.10 0.15 250

Mirpur 25 Low-income Piped water supply without reservoir 1 N 1.00 6.38 0.02 290

Mirpur 26 Low-income Piped water supply without reservoir 2 N 1.00 6.17 0.02 350

Mirpur 27 Slum Piped water supply without reservoir 1 N 1.00 6.10 0.02 300

Tejgaon 4 Slum Hand pump connected to supply line 20.2 N 2.91 7.46 0.81 80

Tejgaon 6 Slum Hand pump connected to supply line no color N 0.87 7.54 0.01 230

Tejgaon 8 Low-income Piped water supply without reservoir no color N 1.34 7.02 0.02 190

Tejgaon 9 Low-income Piped water supply with reservoir no color N 0.63 7.84 0.75 120

Tejgaon 20 Low-income Piped water supply without reservoir 2 N 1.00 6.22 0.27 240

153

Table I.2: Community wise water quality analysis

Community Description FC Count (cfu/100ml)

0 100 200 300 400

Slum

Number 0 2 4 7 0

Cumulative 0 2 6 13 13

Exceeding 13 11 7 0 0

% Exceeding the stated FC count 100 85 54 0 0

Low-income

Number 0 1 6 3 1




Table I.3: Selected areas wise water quality analysis

Selected Areas

Description FC Count (cfu/100ml)

0 100 200 300 400

Gulshan

Number 0 2 1 3 0


Exceeding 6 4 3 0 0


Tejgaon

Number 0 1 2 3 0


Exceeding 6 5 3 0 0


Badda

Number 0 0 3 3 0


Exceeding 6 6 3 0 0


Mirpur

Number 0 0 3 3 1


Exceeding 7 7 4 1 0


154

Table I.4: Urban water supply options wise water quality analysis

Urban Water Supply Options Description FC Count (cfu/100ml)

0 100 200 300 400


Number 0 0 3 1 0


Exceeding 4 4 1 0 0



Number 0 2 3 4 1





Number 0 2 3 5 0




155

Appendix J: OVERALL GRADING BASED ON VULNERABILITY SCORES Table J.1: Grading of vulnerable communities

Serial Criteria Slum Low-income


Infections Diarrhoea Typhoid

Eye Infections

1 Sources Of Water 5.72 2.20 8.50 6.20 2.27 5.10

2 Urban Water Supply Options 5.90 1.47 7.80 6.54 1.70 6.01

3 Distance from HH to Source 5.80 1.43 9.02 3.66 1.70 3.52

4 Time Required to Fetch Water 7.04 2.13 7.17 3.66 1.70 3.52

5 Demand 5.17 1.50 6.91 7.31 1.73 5.35

6 Boiling Practices 6.00 1.10 4.50 5.20 2.27 5.35

7 Storage Practices 5.23 1.63 5.34 6.11 1.36 2.93

8 Sanitary Practices 5.24 1.30 4.44 4.70 1.13 4.22

9 Hand-wash Practices 5.43 1.50 4.67 3.66 1.70 2.60

10 Water Quality 7.07 1.10 7.02 5.34 1.36 4.78

11 SI Risk 7.62 1.53 6.09 5.19 1.70 4.08

Combined Vulnerability Score (CVS) 5.83 1.42 6.67 5.61 1.67 4.34

LEGEND

Grade Point Average

Grade Color Code

>=8-10 Very high

>=6-<8 High

>=3-<6 Medium

>=0-<3 Low

156

Table J.2: Overall grading of selected areas of Dhaka city

Se

ria

l

Criteria


Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

1 Sources Of Water 6.48 2.15 10.00 6.50 1.25 6.50 3.20 0.95 2.27 5.53 2.27 3.83

2 Urban Water Supply Options 9.16 1.43 10.00 7.90 0.83 6.48 3.33 0.63 2.48 6.00 1.70 1.60

3 Distance from HH to Source 7.80 0.73 10.00 6.57 0.00 4.88 2.40 0.63 1.70 4.12 1.70 0.80

4 Time Required to Fetch Water 7.73 1.43 8.89 6.57 0.83 4.88 2.40 0.63 1.70 4.12 1.70 0.80

5 Demand 6.51 0.73 8.89 7.92 0.83 5.23 3.36 0.63 2.84 4.64 1.70 2.88

6 Boiling Practices 5.62 1.10 8.00 8.63 1.25 6.82 4.85 0.95 3.53 5.84 2.27 3.83

7 Boiling Duration 2.67 0.00 0.00 8.00 0.00 5.63 3.87 0.00 2.87 5.64 2.27 3.33

8 Storage Practices 7.13 1.08 9.23 6.53 0.63 4.19 3.10 0.93 1.84 6.38 1.36 2.06

9 Sanitary Practices 2.60 0.44 7.27 5.86 0.50 4.07 3.53 0.84 2.64 4.64 1.13 2.20

10 Hand-wash Practices 4.68 0.73 8.89 7.11 0.83 3.72 3.88 0.63 2.65 5.18 1.70 1.50

11 Water Quality 5.99 1.08 8.00 7.22 0.63 6.69 5.07 1.05 2.94 5.47 1.36 1.66

12 SI Risk 8.10 0.73 10.00 5.70 0.83 5.42 3.84 1.40 2.72 7.70 1.70 2.23

Combined Vulnerability Score (CVS) 6.55 0.94 8.93 7.01 0.68 5.38 3.64 0.80 2.51 5.57 1.67 2.19

157

Table J.3: Overall grading of urban water supply options of Dhaka city

Se

ria

l

Criteria




Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

Dia

rrh

oea

Typ

ho

id

Ey

e

Infe

cti

on

s

1 Sources Of Water 6.66 0.00 7.28 5.10 3.03 5.30 6.10 2.25 4.35

2 Urban Water Supply Options 6.50 0.00 9.10 4.90 2.70 5.50 6.30 2.10 5.10

3 Distance from HH to Source 5.61 0.00 7.81 3.35 2.28 2.75 7.80 1.37 7.08

4 Time Required to Fetch Water 7.65 0.00 7.81 3.35 2.28 2.75 6.49 1.37 7.23

5 Demand 7.25 0.00 7.81 7.60 2.28 5.07 5.53 1.50 5.15

6 Boiling Practices 6.55 0.00 8.93 4.75 3.03 5.34 6.98 1.05 5.05

7 Boiling Duration 5.30 0.00 5.63 5.20 2.27 2.60 8.80 0.00 3.33

8 Storage Practices 4.76 0.00 5.20 6.74 1.82 7.00 5.46 1.55 4.95

9 Sanitary Practices 6.12 0.00 6.25 5.95 0.54 6.53 5.66 1.32 4.41

10 Hand-wash Practices 5.61 0.00 7.81 3.88 2.28 4.45 6.21 1.50 4.43

11 Water Quality 6.38 0.00 6.94 6.20 1.82 5.15 5.92 1.13 4.47

12 SI Risk 5.55 0.00 6.07 7.37 2.28 4.86 7.60 1.50 7.08

Combined Vulnerability Score (CVS) 6.05 0.00 7.04 5.65 2.00 5.04 6.45 1.29 5.29

Note: “0” does not necessarily mean “No vulnerability” but “No data” observed at the time of survey.

158

Appendix K: ESTIMATED HEALTH IMPACT VALUATION OF WATERBORNE DISEASES OF DHAKA CITY

Table K.1: Estimated health impact valuation of vulnerable communities of selected areas of Dhaka city.

Thana

Co

mm

un

ity t

yp

e

To

tal N

um

ber

of

Fam

ily M

em

be

rs

No

of

pers

on

s b

ein

g

dir

ectl

y e

xp

os

ed

No

of

pers

on

s b

ein

g

ind

irectl

y e

xp

osed

Dis

ea

ses

Typ

e

To

tal M

em

be

rs o

f

aff

ecte

d F

am

ily

No

of

Fam

ily M

em

be

rs

aff

ecte

d

Rate

of

incid

en

ces

( i =

h/g

)

Lik

ely

no

. o

f p

ers

on

s

dir

ectl

y e

xp

os

ed

(j =

d X

i)

Lik

ely

no

. o

f p

ers

on

s

ind

irectl

y e

xp

osed

( k =

e X

i)

Mean

Co

st

of

Dis

ease

s

(Tk.)

Esti

mate

d C

ost

of

Dis

ea

ses

for

the S

ele

cte

d a

reas

( T

k.)

(j+

k)X

l

Pre

vale

nce r

ate

(in

1000)

No

of

pers

on

s l

ike

ly t

o

be e

xp

os

ed

bas

ed

on

Pre

vale

nce r

ate

( o

= n

Xe /1

000)

Esti

mate

d C

ost

of

Dis

ea

ses

bas

ed

on

Pre

vale

nce

rate

(T

k.)

( p

= o

X l)

(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) (m) (n) (o) (p)

Gulshan

Slum 51 1140 25500

Diarrhoea 42 28 0.67 760 17000 1521.88 27,028,567.28 521.37 13295 20,233,378.49

Typhoid 14 3 0.21 245 5465 4982.68 28,451,086.49 68.38 1744 8,689,788.94

Eye Infections

36 36 1 1140 25500 916.58 24,417,575.38 358.97 9154 8,390,333.52

Low-income

5 10 1500

Diarrhoea 5 2 0.4 4 600 1521.88 919,214.79 430.11 646 983,133.70

Typhoid 0 0 0 0 0 4982.68 - 21.51 33 164,428.35

Eye Infections

0 0 0 0 0 916.58 - 247.31 371 340,049.57

Tejgaon

Slum 20 245 5750

Diarrhoea 20 11 0.55 135 3163 1521.88 5,019,156.25 521.37 2998 4,562,592.61

Typhoid 8 2 0.25 62 1438 4982.68 7,474,015.72 68.38 394 1,963,174.80

Eye Infections

0 0 0 0 0 916.58 - 358.97 2065 1,892,728.73

Low-income

28 210 6550

Diarrhoea 28 10 0.36 75 2340 1521.88 3,675,337.28 430.11 2818 4,288,654.43

Typhoid 0 0 0 0 0 4982.68 - 21.51 141 702,557.48

Eye Infections

18 11 0.61 129 4003 916.58 3,787,290.60 247.31 1620 1,484,852.56

Badda

Slum 21 400 4200

Diarrhoea 21 8 0.38 153 1600 1521.88 2,667,853.52 521.37 2190 3,332,914.55

Typhoid 16 3 0.19 75 788 4982.68 4,300,050.38 68.38 288 1,435,011.02

Eye Infections

15 3 0.2 80 840 916.58 843,249.60 358.97 1508 1,382,196.09

Low-income

21 200 8500

Diarrhoea 21 12 0.57 115 4858 1521.88 7,568,303.22 430.11 3656 5,563,988.85

Typhoid 0 0 0 0 0 4982.68 - 21.51 183 911,829.92

Eye Infections

21 9 0.43 86 3643 916.58 3,417,910.61 247.31 2103 1,927,558.60

159

Mirpur

Slum 25 160 7500

Diarrhoea 25 14 0.56 90 4200 1521.88 6,528,860.00 521.37 3911 5,952,067.94

Typhoid 0 0 0 0 0 4982.68 - 68.38 513 2,556,113.38

Eye Infections

20 3 0.15 24 1125 916.58 1,053,145.43 358.97 2693 2,468,338.24

Low-income

39 286 8000

Diarrhoea 39 16 0.41 118 3283 1521.88 5,175,909.76 430.11 3441 5,236,784.91

Typhoid 6 2 0.33 96 2667 4982.68 13,767,136.95 21.51 173 862,003.15

Eye Infections

6 3 0.5 143 4000 916.58 3,797,372.93 247.31 1979 1,813,903.22

Total: 210 2651 67500

149,892,036.19

87,138,383.05

Table K.2a: Estimated health impact valuation of vulnerable community of Dhaka city based on LGED (2005) statistics.

Total HHs HH Size

Estimated Slum

Population (No)

Diseases Type Mean Cost of

Diseases (Tk.)

Prevalence rate

(in 1000)

No of persons likely to be exposed based on Prevalence rate

(No)

Estimated Cost of Diseases based on

Prevalence rate (Tk.)

267,065 5.25 14,02,091

Diarrhoea 1521.88 480.95 674,340 1,026,263,741.82

Typhoid 4982.68 47.62 66,767 332,678,404.80

Eye Infections 916.58 309.52 433,981 397,776,418.11

Total Cost of Diseases In Taka 1,756,718,564.73

In Dollar [Exchange Rate 1 USD = 67.08 Tk. ;BBS (2010) for 2005-06] 26,188,410.33

Table K.2b: Estimated health impact valuation of vulnerable community of Dhaka city based on BBS (2011) statistics.

Estimated Population

(2011)

% of Total Population Living in Slums

Estimated Slum

Population (No)

Diseases Type Mean Cost of

Diseases (Tk.)

Prevalence rate

(in 1000)

No of persons likely to be exposed based on Prevalence rate

(No)

Estimated Cost of Diseases based on

Prevalence rate (Tk.)

1,18,75,000 38% 45,12,500

Diarrhoea 1521.88 480.95 2,170,298 3,302,930,489.58

Typhoid 4982.68 47.62 214,881 1,070,682,647.14

Eye Infections 916.58 309.52 1,396,727 1,280,205,960.94

Total Cost of Diseases In Taka 5,653,819,097.66

In Dollar [Exchange Rate 1 USD = 69.18 Tk.; BBS (2010) for 2009-10] 81,726,208.41

160

Appendix L: CALCULATION OF PREVALENCE RATE OF WATERBORNE DISEASES OF SELECTED AREAS OF DHAKA CITY Table L.1: Prevalence rate of diarrhoea

Definition

Ag

e G

rou

p

(Ye

ars

)

Ge

nd

er

Su

rve

ye

d

Po

pu

lati

on

Nu

mb

er

of

Inc

ide

nce

s

Prevalence Rate (PR) Per 1000 Population

Based on Surveyed Age Group and Gender (PIG)

Based on Surveyed Gender (PGT)

Based on Total Surveyed Population (PTP)

Children < 5 years <5

F 16 10

625.00

104.17

47.62

M 17 5

294.12

43.86

23.81

Children at 5 years to 14 years

5-14

F 20 9

450.00

93.75 42.86

M 26 18

692.31

157.89

85.71

Aging > 15 years >15

F 60 26

433.33

270.83

123.81

M 71 33

464.79

289.47 157.14

Female Prevalence F 96 45

468.75

214.29

Male Prevalence M 114 56

491.23

266.67

For Entire Sample Both

Gender 210 101

480.95

161

Table L.2: Prevalence rate of typhoid

Definition Age

Group (Years)

Gender Surveyed

Population Number of Incidences


Based on Surveyed Age

Group and Gender (PIG)

Based on Surveyed

Gender (PGT)

Based on Total Surveyed Population

(PTP)

Children < 5 years <5 F 16 2 125.00 20.83 9.52

M 17 1 58.82 8.77 4.76


5-14 F 20 1 50.00 10.42 4.76

M 26 1 38.46 8.77 4.76

Aging > 15 years >15 F 60 3 50.00 31.25 14.29

M 71 2 28.17 17.54 9.52

Female Prevalence F 96 6 62.50 62.50

Male Prevalence M 114 4 35.09 35.09

For Entire Sample Both Gender 210 10 47.62

162

Table L.3: Prevalence rate of eye infections

Definition Age

Group (Years)

Gender Surveyed

Population Number of Incidences


Based on Surveyed Age

Group and Gender (PIG)

Based on Surveyed

Gender (PGT)

Based on Total Surveyed Population

(PTP)

Children < 5 years <5 F 16 3 187.50 31.25 14.29

M 17 7 411.76 61.40 33.33


5-14 F 20 8 400.00 83.33 38.10

M 26 9 346.15 78.95 42.86

Aging > 15 years >15 F 60 14 233.33 145.83 66.67

M 71 24 338.03 210.53 114.29

Female Prevalence F 96 25 260.42 119.05

Male Prevalence M 114 40 350.88 190.48

For Entire Sample Both Gender 210 65 309.52

163

Table L.4: Prevalence rate of waterborne diseases of community

Community Surveyed

Population



PRGT PRTP Number of Incidences


PRGT PRTP

Slum 117 61 521.37 290.48 8 68.38 38.10 42 358.97 200.00

Low-income 93 40 430.11 190.48 2 21.51 9.52 23 247.31 109.52

Total: 210 101 10 65

Table L.5: Prevalence rate of waterborne diseases at different selected areas

Selected Areas

Surveyed Population

Diarrhoea

Typhoid

Eye Infections




PRGT PRTP

Gulshan 56 30 535.71 142.86 3 53.57 14.29 36 642.86 171.43

Tejgaon 48 21 437.50 100.00 2 41.67 9.52 11 229.17 52.38

Badda 42 20 476.19 95.24 3 71.43 14.29 12 285.71 57.14

Mirpur 64 30 468.75 142.86 2 31.25 9.52 6 93.75 28.57

Total: 210 101 10 65

Table L.6: Prevalence rate of waterborne diseases with respect to urban supply options


Surveyed Population





PRGT PRTP


37 20 540.54 95.24 0 0.00 0.00 10 270.27 47.62


77 27 350.65 128.57 4 51.95 19.05 22 285.71 104.76


96 54 562.50 257.14 6 62.50 28.57 33 343.75 157.14

Total: 210 101 10 65

164

Appendix M: CORRELATION BETWEEN DIARRHOEAL INCIDENCES AND CLIMATIC FACTORS Table M.1: Data of diarroheal incidences and climatic factors for both selected areas and Dhaka (2000-2010)

Item Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Std Dev

Rainfall(mm) 6 17.2 61.6 120.9 258.4 379.1 415.4 307.2 357.4 193.0 26.5 4.5 152.10

Temperature(°C) 18.7 22.3 26.4 28.7 29 28.9 28.8 29.1 28.7 27.5 24.2 20.5 3.56

Humidity (%) 69.4 61.2 59.4 68.5 72.9 80.2 81.2 80.0 81.0 77.3 70.9 70.9 7.17 No. of

Patients Tejgaon 250 300 600 650 400 350 450 550 500 450 400 250 124.93 Badda 300 350 600 800 700 450 550 1100 800 600 600 400 215.50

Gulshan 450 450 550 800 600 450 500 650 600 550 500 400 105.74 Mirpur 450 500 850 1650 1150 950 850 1200 1150 900 650 500 337.89

Avg No. of Patients (Selected areas)

363 400 650 975 713 550 588 875 763 625 538 388 183.03

Avg No. of Patients (Dhaka)

250 250 400 550 450 300 350 450 400 350 300 250 90.91

Table M.2: Data conversion for Microsoft Excel output using regression analysis formula for exponential/logarithmic growth

Item Values Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Avg No. of Patients (Selected areas)

Ysa 363 400 650 975 713 550 588 875 763 625 538 388

y = Log10(Ysa) 2.56 2.60 2.81 2.99 2.85 2.74 2.77 2.94 2.88 2.80 2.73 2.59

Avg No. of Patients (Dhaka)

Ydk 250 250 400 550 450 300 350 450 400 350 300 250

y = Log10(Ydk) 2.40 2.40 2.60 2.74 2.65 2.48 2.54 2.65 2.60 2.54 2.48 2.40

165

Table M.3: Correlation between temperature and diarrhoeal patients of selected areas

n

Temperature

(°C)

Average No. of Patients

(Selected areas)

x

y

1 18.7 7.37 54.3169 2.56 0.21 0.0451 1.5648

= 0.8665

2 22.3 3.77 14.2129 2.60 0.17 0.0290 0.6415

3 26.4 -0.33 0.1089 2.81 -0.04 0.0017 0.0134

4 28.7 -2.63 6.9169 2.99 -0.22 0.0470 0.5701

5 29.0 -2.93 8.5849 2.85 -0.08 0.0065 0.2369

6 28.9 -2.83 8.0089 2.74 0.03 0.0010 -0.0902

7 28.8 -2.73 7.4529 2.77 0.00 0.0000 -0.0078

8 29.1 -3.03 9.1809 2.94 -0.17 0.0288 0.5144

9 28.7 -2.63 6.9169 2.88 -0.11 0.0122 0.2901

10 27.5 -1.43 2.0449 2.80 -0.02 0.0006 0.0338

11 24.2 1.87 3.4969 2.73 0.04 0.0017 0.0775

12 20.5 5.57 31.0249 2.59 0.18 0.0336 1.0215

∑

312.8

152.2668 33.27

0.2071 4.8662

26.07

2.77 x

22),(

)()(

))((

yyxx

yyxxCr yx

166

Table M.4: Correlation between temperature and diarrhoeal patients of Dhaka city

n

Temperature

(°C)

Average No. of Patients (Dhaka)

x

y

1 18.7 7.37 54.3169 2.40 0.14 0.0203 1.0513

= 0.7992

2 22.3 3.77 14.2129 2.40 0.14 0.0203 0.5378

3 26.4 -0.33 0.1089 2.60 -0.06 0.0038 0.0203

4 28.7 -2.63 6.9169 2.74 -0.20 0.0399 0.5254

5 29.0 -2.93 8.5849 2.65 -0.11 0.0127 0.3300

6 28.9 -2.83 8.0089 2.48 0.06 0.0040 -0.1796

7 28.8 -2.73 7.4529 2.54 0.00 0.0000 0.0095

8 29.1 -3.03 9.1809 2.65 -0.11 0.0127 0.3412

9 28.7 -2.63 6.9169 2.60 -0.06 0.0038 0.1617

10 27.5 -1.43 2.0449 2.54 0.00 0.0000 0.0050

11 24.2 1.87 3.4969 2.48 0.06 0.0040 0.1187

12 20.5 5.57 31.0249 2.40 0.14 0.0203 0.7946

∑

312.8

152.2668 30.49

0.1420 3.7158

26.07

2.54

x

22),(

)()(

))((

yyxx

yyxxCr yx

167

Table M.5: Projected data for diarrhoeal patients of selected areas and Dhaka city basing on temperature

Temperature(°C)

x

Selected Areas ( y = 0.032x + 1.9392 ) Dhaka (y = 0.0244x + 1.9045)

Ysa = 10y

Likely to be Affected

( YSA± 183) Ydk = 10

y

Likely to be Affected (YDK± 91)

Monthly Average Lower bound Higher bound Monthly Average Lower bound Higher bound

18 328 145 511 221 130 312

19 353 170 536 234 143 325

20 380 197 563 247 156 338

21 409 226 592 262 171 353

22 440 257 623 277 186 368

23 474 291 657 293 202 384

24 510 327 693 310 219 401

25 549 366 732 327 236 418

26 591 408 774 346 255 437

27 636 453 819 366 275 457

28 685 502 868 387 296 478

29 737 554 920 410 319 501

30 793 610 976 434 343 525

31 854 671 1037 459 368 550

32 919 736 1102 485 394 576

33 990 807 1173 513 422 604

34 1065 882 1248 543 452 634

35 1147 964 1330 574 483 665

36 1234 1051 1417 607 516 698

37 1329 1146 1512 642 551 733

38 1430 1247 1613 679 588 770

39 1539 1356 1722 718 627 809

40 1657 1474 1840 760 669 851

168

Appendix N: CRITERIA WISE HEALTH IMPACTS OF THE SELECTED COMMUNITIES, AREAS AND URBAN WATER SUPPLY OPTIONS

Figure N.1: State of health impacts of selected community based on water source’s connection

Figure N.2: State of health impacts of selected areas based on water source’s connection

0

10

20

30

40

50

60

70

80

90

100

Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections

private connection public connection/Tap water

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Slum Low-income

0

10

20

30

40

50

60

70

80

90

100


private connection public connection

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Source Connection


169

Figure N.3: State of health impacts of urban water supply options based on water source’s connection

Figure N.4: State of overall health impacts of water sources’ connection

0

10

20

30

40

50

60

70

80

90

100


private connection public connection

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line

0

10

20

30

40

50

60

70


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Private Connection Public Connection/Tap Water

170

Figure N.5: State of health impacts of selected community based on urban water supply options

Figure N.6: State of health impacts of selected areas based on urban water supply options

0

20

40

60

80

100

Diarrhoea Typhoid EyeInfections



Piped water supply with reservoir Piped water supply withoutreservoir

Hand pump connected to supplyline

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Slum Low-income

0

10

20

30

40

50

60

70

80

90

100






% o

f in

cid

en

ce a

gain

st E

xpo

sure


171

Figure N.7: Overall state of health impacts based on urban water supply options

Figure N.8: State of health impacts of selected community based on distance between HHs and sources

of water

0

10

20

30

40

50

60

70

80

90

100



% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

10

20

30

40

50

60

70

80

90

100




<50m <100 (50-100)m <250 (100-250) m

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Distance between HH and Source of Water

Slum Low-income

172

Figure N.9: State of health impacts of selected areas based on distance between HHs and sources of water

Figure N.10: State of health impacts of urban water supply options based on distance between HHs and sources of water

0

20

40

60

80

100




<50m <100 (50-100)m <250 (100-250) m

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Distance between HH and Source of Water


0

10

20

30

40

50

60

70

80

90

100




<50m <100 (50-100)m <250 (100-250) m

% o

f in

cid

en

ce a

gain

st E

xpo

sure


173

Figure N.11: Overall state of health impacts of urban water supply options based on distance between

HHs and sources of water

Figure N.12: State of health impacts of selected community based on time required fetching water from

its source.

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure

<50m <100m (50m-100m) <250m (100m-250m)

0

20

40

60

80

100




5 minutes 5-15 minutes 15-30 minutes

% o

f in

cid

ence

aga

inst

Exp

osu

re

Time to Fetch Water from Source

Slum Low-income

174

Figure N.13: State of health impacts of selected areas based on time required fetching water from its source.

Figure N.14: State of health impacts of urban water supply options based on time required fetching water

from its source.

0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure


175

Figure N.15: Overall state of health impacts of urban water supply options based on time required

fetching water from its source.

Figure N.16: State of health impacts of selected community based on demand of water

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

10

20

30

40

50

60

70

80

90

100





% o

f in

cid

ence

aga

inst

Exp

osu

re

Slum Low-income

176

Figure N.17: State of health impacts of selected areas based on demand of water

Figure N.18: State of health impacts of urban water supply options based on demand of water

0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure

Demand to meet


0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure

Demand to meet


177

Figure N.19: State of overall health impacts due to demand of water

Figure N.20: State of health impacts of selected community based on boiling practices

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

10

20

30

40

50

60

70

80


Yes No

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Boiling Practices

Slum Low-income

178

Figure N.21: State of health impacts of selected areas based on boiling practices

Figure N.22: State of health impacts of urban water supply options based on boiling practices

0

20

40

60

80

100


Yes No

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Boiling Practices


0

20

40

60

80

100


Yes No

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Boiling Practices


179

Figure N.23: Overall state of overall health impacts due to boiling practices

Figure N.24: State of health impacts of selected community based on boiling duration

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Yes No

0

10

20

30

40

50

60

70

80



% o

f in

cid

en

ce a

gain

st E

xpo

sure

Boiling Duration

Slum Low-income

180

Figure N.25: State of health impacts of selected areas based on boiling duration

Figure N.26: State of health impacts of urban water supply options based on boiling duration

0

20

40

60

80

100



% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100



% o

f in

cid

en

ce a

gain

st E

xpo

sure


181

Figure N.27: State of overall health impacts due to boiling duration

Figure N.28: State of health impacts of selected community based on storage practices

0

10

20

30

40

50

60


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Storage Practices

Slum Low-income

182

Figure N.29: State of health impacts of selected areas based on storage practices

Figure N.30: State of health impacts of urban water supply options based on storage practices

0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Storage Practices


0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Storage Practices


183

Figure N.31: Overall state of health impacts based on storage practices

Figure N.32: State of health impacts of selected community based on sanitary practices

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Slum Low-income

184

Figure N.33: State of health impacts of selected areas based on sanitary practices

Figure N.34: State of health impacts of urban water supply options based on sanitary practices

0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns


% o

f in

cid

en

ce a

gain

st E

xpo

sure


185

Figure N.35: Overall state of health impacts based on sanitary practices

Figure N.36: State of health impacts of selected community based on hand-wash practices

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100




Nothing Ash Soap

% o

f in

cid

en

ce a

gain

st E

xpo

sure

Slum Low-income

186

Figure N.37: State of health impacts of selected areas based on hand-wash practices

Figure N.38: State of health impacts of urban water supply options based on hand-wash practices

0

20

40

60

80

100




Nothing Ash Soap

% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100




Nothing Ash Soap

% o

f in

cid

en

ce a

gain

st E

xpo

sure


187

Figure N.38: Overall state of health impacts based on hand-wash practices

Figure N.39: State of health impacts of selected community based on water quality

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure

Nothing Ash/soil Soap

0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

0-100 100-200 200-300 300-400

% o

f in

cid

en

ce a

gain

st E

xpo

sure


Slum Low-income

188

Figure N.40: State of health impacts of selected areas based on water quality

Figure N.42: State of health impacts of urban water supply options based on water quality

0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

0-100 100-200 200-300 300-400

% o

f in

cid

en

ce a

gain

st E

xpo

sure



0

20

40

60

80

100

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

Dia

rrh

oe

a

Typ

ho

id

Eye

Infe

ctio

ns

0-100 100-200 200-300 300-400

% o

f in

cid

en

ce a

gain

st E

xpo

sure



189

Figure N.43: Overall state of health impacts based on water quality

Figure N.44: State of health impacts of selected community based on SI risk grade

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure

0-100 100-200 200-300 300-400

0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure

Slum Low-income

190

Figure N.45: State of health impacts of selected areas based on SI risk grade

Figure N.46: State of health impacts of urban water supply options based SI risk grade

0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure


0

20

40

60

80

100





% o

f in

cid

en

ce a

gain

st E

xpo

sure


191

Figure N.47: Overall state of health impacts based SI risk grade

0

20

40

60

80

100


% o

f in

cid

en

ce a

gain

st E

xpo

sure


192

Appendix O: THEMATIC MAPS OF DHAKA CITY

Figure O.1: Water bodies and distribution DWASA DTWs in selected areas of DMPA

Figure O.2: Distribution of water points

Figure O.3: Distribution of FC concentration to the sample points

193

Figure O.4: Sample point wise diarrhoeal incidences

Figure O.5: Sample point wise typhoid incidences

Figure O.6: Sample point wise eye infections’ incidences

194

Figure O.7: Vulnerability state of selected areas according to diarrhoea

Figure O.8: Vulnerability state of selected areas according to typhoid

Figure O.9: Vulnerability state of selected areas according to eye infections’ incidences

040404124P-Main Thesis Paper

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