SEASC2009_AjiPutraPerdana_GeospatialLearninginCombatingDengue

GEOSPATIAL LEARNING IN COMBATING DENGUE FEVER PROJECT STUDY SITE: THE CITY OF YOGYAKARTA

Aji Putra Perdana 1, *, Hilmi Ardiansyah 2, Humam Zarodi1

1 GIS and Data Management Unit Assistant, Tahija Foundation, Project Dengue,

Project office: Jl. Pandega Sakti 159 Kaliurang Street KM 6, 2 Yogyakarta 55281, Indonesia. - [email protected], [email protected]

2 Team Leader GIS and Data Management Unit, Tahija Foundation, Project Dengue, Project office: Jl. Pandega Sakti 159 Kaliurang Street KM 6, 2 Yogyakarta 55281, Indonesia. -

[email protected]

ABSTRACT:

Dengue fever and Dengue Hemorrhagic Fever (DHF) is already endemic in 45 Kelurahan in the City of Yogyakarta yet is the most densely populated. A two years combating dengue fever project started in 2007, the strategy is targeted Aedes aegypti breeding source control using the insect growth regulator. This project involved 262 local peoples and 32 surveyors; they are the main actors in geospatial learning. GIS, Satellite Images and GPS are part dengue fever project in the City of Yogyakarta. This paper described Geospatial Learning in Combating Dengue Fever in Indonesia Phase II Project (study site: The City of Yogyakarta). KEY WORDS: Geospatial, Dengue Fever, GIS, Satellite Images, GPS

* Corresponding author.

1. INTRODUCTION

1.1 Background

Vector borne diseases are the most common worldwide health hazard and represent a constant and serious risk to a large part of the world's population. Among these, dengue fever especially is sweeping the world in majority of the tropical and arid zones. It is transmitted to the man by the mosquito of the genus Aedes and exists in two forms: the Dengue Fever (DF) or classic dengue and the Dengue Haemorrhagic Fever (DHF), which may evolve into Dengue Shock Syndrome (DSS) (Nakhapakorn, K. et al, 2005).

Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) has become a major international public health concern. Many countries/areas in Asia have been experiencing unusually high levels of dengue/dengue haemorrhagic fever activity in 1998. Since 2004 Indonesia reports the highest number of cases from the South East Asia region. In 2006 57 % of the cases were reported from Indonesia alone (Nakhapakorn, K. et al, 2005; Perdana, Aji P. et al, 2009).

Until today, In Indonesia DF/DHF is still the main concern in public health problems on the responsibility of The Indonesian Ministry of Health. Many efforts and strategies to control dengue have being conducted by the government, Non-Government Organization, and society. Strategies to control dengue, is largely through source reduction, health education and

intersectoral coordination with many surveillance methods are used. Source reduction is still the main emphasis in the control of DF/DHF.

Dengue cannot be spread directly from person to person, but the spread of disease is unavoidably spatial (Holmes, 1997). Epidemiologists, public health professionals, medical geographers have traditionally used maps when analyzing associations between location, environment, and disease. Geographic Information Systems (GIS) is particularly well suited for studying these associations because of its spatial analysis and display capabilities. GIS and the value of maps used in public health have a very long history. Dr John Snow is the pioneer in the field. John Snow's now classic maps of cholera cases in relation to the Broad Street pump are a good example.

Recently, Geographic Information Systems (GIS) and Remotely Sensed data has been used in the surveillance and monitoring of vector-borne diseases. A pilot project based on implementation of result from Dengue Project Phase I study site in The City of Yogyakarta had been conducted by the Tahija Foundation (Indonesia) collaborated with Gadjah Mada University. This project was known as Combating Dengue Pilot Project Phase II proposed targeted source reduction strategy/control strategy for dengue control used Geographic Information Systems (GIS) and Remotely Sensed data.

The combating dengue fever project needs geospatial data of the city of Yogyakarta as treatment area and also three Villages in Sleman District and three villages in Bantul District as control areas; the Base Maps (Municipality, Villages, Administrative Boundaries, River, Roads) and Satellite Images for determine of working area, survey, distribution and monitoring activities. But there was geospatial data problem related to the needs of geospatial data until Rukun Warga (RW)/Rukun Tetangga (RT) or neighbourhood’s level. It causes several changes in the strategies of collecting the tabular data from the field. GIS and Data Management Unit, which has responsibility in geospatial data management was suggested the project to use GPS and printed Quickbird Images to do participatory mapping.

This project involved 262 field workers called Pemantau DBD was recruited from 2523 Jumantik’s RT by Dinas Kesehatan Kota Yogyakarta and 32 surveyors from Faculty of Medicine, Gadjah Mada University. They are the main actors in collecting data from the field to be linked in to geospatial data. Geospatial training was given to them in order to get the right coding in field-collected data, which will be linked into the Map Layers in GIS. Geospatial learning of the field workers and surveyors in this project helps us in combating dengue fever in the City of Yogyakarta.

1.2 Aims

The aim of this paper is to describe and seeks to show how geospatial learning from field workers and surveyors during the combating dengue fever project in the City of Yogyakarta. The paper also aims to see the potential and the limitations of geospatial learning with GPS training and participatory mapping as a method to extract information for the combating dengue fever project. This case study will be the basis for a more general discussion on how the method might be applied and improved for the future when it comes to be continued in the next phase.

2. THE CITY OF YOGYAKARTA, DENGUE, CONTROL METHOD, AND GEOSPATIAL DATA

2.1 The City of Yogyakarta and Dengue

Yogyakarta, a city of about 506-522 thousand people, is the provincial capital of the Province or Special Region (Daerah Istimewa Yogyakarta, or DIY) of Yogyakarta located in south central Java. The Province is divided into 5 administrative districts with each district divided into progressively smaller units beginning with sub-districts (Fig. 1), and these, in turn, divided into kelurahans, and further divided into rukun warga (RW, ca. 250 residences each), and finally into

rukun tetangga (RT), the smallest administrative unit composed of approximately 50-80 residences.

Figure 1. Map of the Municipality of Yogyakarta

The City of Yogyakarta is the fourth largest

(32.5 km2) kabupaten in DIY yet is the most densely populated (ca. 16,000 per square kilometre); this variability in density explains much of the variability in the incidence for severe dengue within the Province. At an incidence rate (IR) of 17.7 cases per 10,000, the City has twice- to three-times higher incidence than that neighbouring Sleman (7.6) or Bantul (6.3). Dengue fever and Dengue Hemorrhagic Fever (DHF) is already endemic in 45 Kelurahan in the City of Yogyakarta. Table 1. Population size, number and incidence rate (IR,

per 10,000) of dengue cases by kabupaten for the Province of Yogyakarta in 2006.

Kabupaten Popu- lation Residences No.

cases IR

Yogyakarta 506,000 105,417 888 17.7

Sleman 826,558 172,200 626 7.6

Bantul 780,177 162,537 493 6.3

Kulonprogo 443,819 92,462 71 1.6 Gunung Kidul 746,457 155,512 106 1.4

Totals 3,303,011 688,127 2,184 6.6 Source: Focks, Dana A., 2007 2.2 Control Method

A two years combating dengue fever project started in 2007, the strategy was targeted Aedes aegypti breeding source control using an insect growth regulator (IGR), pyriproxyfen (Fig. 2) that prevents successful emergence of adult mosquitoes from the pupal stage. Distribution and monitoring of the insect growth regulator being conducted by 262 Pemantau DBD’s, each day 20-25 houses coordinated by Operational units. Independently assessment of the prevalence of IGR in

targeted water container by 32 Surveyors from Quality Control Research & Serology (QCRS) Unit. This team was also had two main activities, namely Serology and Entomology.

© Dengue Project Documentations Copyright 2008

Figure 2. An insect growth regulator (IGR),

pyriproxyfen in three kinds of sachet

Based on dengue IR, serosurvey and entomologic surveys was conducted only in 12 kelurahans, 6 in the City and 3 each in Sleman and Bantul on the basis of similar dengue incidence rates (IRs). Serology used to measure of the impact of dengue control effort. Entomologic surveys consist of pupal counts and emergence, adult aspirations, pupal/demographic surveys to determine the reduction of Ae. aegypti populations due to targeted intervention.

Knowledge, attitudes, and practices (KAP) regarding targeting, the utility and safety of the insect growth regulator being conducted in sampling area. We also used case reported from Dinas Kesehatan of the Municipality of Yogyakarta to monitor the suppression of dengue cases.

All project data compiled in Data Management Unit, which has responsibility to create and maintain the repository of all project data that is spatially explicit, conversion of paper-based data from the other Units into digital data (data entry) and also summarizing data and creating maps. 2.3 Geospatial Data

Starting dengue control project requires information about the condition of the study area and for the determination of cluster area (treatment and control area), so that the existence of spatial data are absolutely needed. Tahija Foundation in collaboration with Faculty of Geography, Gadjah Mada University as Spatial Data Provider since the Dengue Control Phase I and also for this project phase II. Geospatial data included satellite images (Quickbird, Ikonos, and Digital Aerial Photos from previous project) and base maps Layer.

Dengue control project need to be able to effectively use information, manage project information, combined with spatial dataset to build data integration for the purposes of supporting the dengue project. In this project, GIS facilitate the integration of geospatial data and all data collected into Geodatabase. The dengue project geodatabase contains three primary dataset types are shown below:

− Feature classes: Base Map Layers; Municipality, Villages, Administrative Boundaries, River, Roads, Survey Location (GPS measurements), etc.

− Raster datasets: Quickbird Imagery, Ikonos Imagery, digital aerial photos

− Tables: Dengue Cases Report, Demographic Data, IGR Distribution and Monitoring Data, pupal counts and emergence, adult aspirations, pupal/demographic surveys, serology surveys. There were limitations in spatial data and

tabular data, such as the smallest mapping unit is villages, we have no baselines, the exact or detailed data related to the number of houses, targeted water container in the City of Yogyakarta, etc. Therefore, we needed the participation from the field for gathering those information and learned how to combating dengue fever with geospatial data.

3. GEOSPATIAL LEARNING IN COMBATING DENGUE FEVER PROJECT

Geospatial learning was also part of the capacity building and enriches local knowledge in order to think spatially, do more effective and efficient in their survey, distribution and monitoring activities. 3.1 Human Resources

Human resources of geospatial learning in this project consist of core team, data entry persons, field workers, and surveyor team. In the core team, three persons as GIS and data management who deals with geospatial information and data management. Data entry persons (25-30 persons) helped GIS and data management unit in conversion of paper-based data into digital data. The main actors are 262 field workers and 32 surveyors, because they learned about the use of geospatial data for themselves and also this project.

On daily based, the field workers were distribution IGR, monitoring the prevalence of IGR, checked larvae and pupal in the targeted water container, reported data on paper-based form and submitted to the office. They were working in the City of Yogyakarta; especially in their own neighbourhoods for more than 5 RT and it’s depended on the numbers of RT and Pemantau DBD in their own villages. But, the surveyors conducted entomologic surveys only in 12 kelurahans, 6 in the City and 3 each in Sleman and Bantul. Sometimes

the surveyor also met with the field worker when conducted survey in 12 Kelurahans in the City of Yogyakarta (Fig. 3).

The field workers and surveyors had capacity building of geospatial learning in order to collect information from field to be correlated to geospatial data.

© Dengue Project Documentations Copyright 2008

Figure 3. Surveyors QCRS and Pemantau DBD 3.2 GPS, Satellite Images, and Maps

Geospatial learning in this project were conducted with training method; learn by doing and do by learning. GIS and Data Management Unit in coordination with other units conducted several training for the field workers and surveyors. Introduction about GPS only for the surveyors, but geospatial training about the use of satellite images, tabular data, and maps for this project were conducted for both of them. 3.2.1 GPS (Global Positioning System): A constellation of twenty-four satellites, developed by the United States Department of Defence, that orbit the earth at an altitude of 20,200 kilometres (10,900 nautical miles, 12,544 miles). Each satellite orbits the earth every 12 hours and transmits radio signals that allow a GPS receiver anywhere on earth to calculate its location. Exact location is determined by trilateration (determining the position of a point by measuring the distance between three points). That introduction was given to the surveyors in training. GPS receivers are relatively easy to operate, many users are not aware of the technology's complexities. We were used 6 GPS Garmin 76csx for 32 surveyors divided into six groups.

3.2.2 Satellite Images: Satellite images in this dengue project were Quickbird, Ikonos, and Digital Aerial Photos from previous project (only for Terban and Klitren). All images were covered 45 Kelurahan in the City of Yogyakarta and 3 kelurahan each in Sleman and Bantul. At first project plan that satellite images would be used as basic data to determining the locations for surveys and as guidance also dividing working area for Pemantau DBD. 3.2.3 Maps: Creating maps was one of the responsibilities GIS and Data Management Unit. Input for maps were from Dinas Kesehatan for dengue cases, principal investigator for determined cluster area, but the most important things; information from field workers and surveyors. That was why they should knew about what is map and how important the information they were collected and to be coded in the right way in order to be linked into geospatial data. 3.3 The GPS application and Participatory Mapping

3.3.1 The GPS Application: Use the GPS Garmin 76csx was easy operating, the surveyors should marked the visited houses in coded number. Even though, all surveyors were trained in using GPS usually only one or two persons that used the GPS. Without surveyor' participation in the application GPS in mapping the visited houses, the accuracy cannot always be assured on the one hand, while on the other, the information cannot be properly utilized.

© Dengue Project Documentations Copyright 2008

Figure 4. Surveyor marked house location with GPS

3.3.2 Participatory Mapping: The use of participatory mapping with the first aim was in order to get RT/RW level boundaries from 45 Kelurahan in the City of Yogyakarta. Printed Quickbird images were distributed for Pemantau DBD and also 45 Kelurahan. Since participatory mapping was new method in combating dengue fever, the reactions of the peoples involved from the field are an important part. They were learned to see images that captured houses from the sky, to know their own location, survey and try to delineate the boundaries until RW/RT level, the roads, and rivers (Fig. 5).

© Dengue Project Documentations Copyright 2008

Figure 5. Pemantau DBD prepared for participatory

mapping Their results then digitized by GIS and Data Management Unit into several layers (Fig. 6) and edited using GIS software to be display, visualize and also for analysis needs.

Figure 6. Administrative Map (RT Boundaries) of

Kelurahan Terban, the City of Yogyakarta 3.4 Lesson Learned

Geospatial activities have been conducted by the field workers and surveyors made both of them as the main actors of geospatial learning in combating dengue fever in the City of Yogyakarta. Geospatial capacity-building lesson-learned

Surveyors were learned new knowledge, geospatial data and tools and increase their skill or capacity, namely:

1. Ability to read satellite images maps for survey activities

2. Generally able to interpret the information in the maps and try to match with the real world (field condition), such as: building schools, mosques, houses.

3. They know and get the benefits of using GPS and Maps for entomology survey

4. They can use and operate GPS Handheld; waypoint, track and route.

5. Understand and know their working area spatially

Pemantau’s DBD were learned geospatial knowledge and also increases their skill or capacity, namely:

1. Learned about Maps: how to make map from delineate boundaries, roads, rivers, creating legend for the map; reading the map, etc.

2. Understand the importance of Maps in monitoring their activities in the working area.

3. At the beginning, maybe they only knew their nearest neighbourhood, but now they knew more than before and think spatially in their work activities, such as determine visited area.

4. Generally able to interpret the information in the maps and try to match with the real world (field condition), such as: building schools, mosques, houses.

Based on lesson learned from geospatial learning in dengue control, Geographic Information Systems (GIS) and Remotely Sensed data has been used effectively to get the information needed for the project goal. The GIS needs assessment was a critical initial step in the capacity-planning process.

4. CONCLUSION

The geospatial learning in combating dengue fever still needs improvement. Meanwhile, we can conclude that combating Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) in the City of Yogyakarta with geospatial learning to get geospatial understanding for the team and also community is very important, because the disease spread is unavoidably spatial.

GIS, Satellite Images and GPS are part dengue fever project in the City of Yogyakarta and geospatial learning. These lessons learned will be valuable as the centre moves to next phase project to build Geospatial capacity.

For the future project, we need to explore the potential of participatory mapping as a tool to be used in order to capture the local perspectives on public health in combating dengue fever. The possibility to integrate participatory mapping with consultations or empowerment of the locals of the combating dengue process are also interesting issues for future research.

5. REFERENCES

Focks, Dana A. 2007. Combating Dengue Fever in Indonesia Phase II Project Description. Tahija Foundation, Indonesia. Holmes EE. 1997. Basic epidemiological concepts in a spatial context. In: Tilman D, Kareiva P, eds. Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions. Princeton, NJ: Princeton University Press; pp. 111-136. Isaksson et al, 2008. Participatory mapping as a tool for capturing local perspectives on cultural landscape – case study of Ostlänken. Report on “Include - Integration of ecological and cultural dimensions in transport infrastructure”, KTH – School of Architecture and the Built Environment Urban Planning and Environment, Stockholm. http://www.mistra.org/download/18.87749a811cbd4c4fb4800010902/Participatory+mapping+as+a+tool.pdf (accessed 29 May 2009) Law, DCG et al, 2008. Mapping for Surveillance and Outbreak Investigation. The North Carolina Center for Public Health Preparedness, the University of North Carolina, Chapel Hill. http://nccphp.sph.unc.edu/focus/vol5/issue2/5-2Mapping_issue.pdf (accessed 29 May 2009) Lilienfeld AM, Lilienfeld DE. John Snow, 1984. The Broad Street pump and modern epidemiology. International Journal of Epidemiology 13(3):376-7. http://www.ph.ucla.edu/epi/snow/injepidemiology13_376_378_1984.pdf (accessed 24 June 2009) Nakhapakorn, K. and Tripathi, N.K., 2005. An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence. International Journal of Health Geographics 2005, 4:13. BioMed Central Ltd. Perdana, Aji P. and Zarodi, H., 2009. The Use of GIS (Geodatabase) in Combating Dengue Fever in Indonesia Phase II Project (Study Site: The City of Yogyakarta). Paper submitted in Map World Forum 2009, Hyderabad, India. http://www.gisdevelopment.net/proceedings/mapworldforum/2009/emergingTT/mwf09_AjiPutraP.pps (accessed 6 March 2009) Yun, G., 2008. GIS in Health, Western Australia Government Department of Health, Australia. http://www.walis.wa.gov.au/forum/past_forum/assets/2008/proceedings/gis-in-health-new.ppt (accessed 24 June 2009)

6. ACKNOWLEDGEMENTS

This paper is derived from experience in implementation of Research and Pilot Project in Yogyakarta to control dengue haemorrhagic fever in Indonesia. Preparation of paper, presentation and participation in the Conference is possible by support from the Tahija Foundation of Jakarta, Indonesia and The Claire and Scobie MacKinnon Trust of Melbourne, Australia. We would like to express our sincere thanks to Focks, Dana A. Infectious Disease Analysis, LLC, Gainesville, FL 32604, USA. Aprillya, Sukma Tin. Project Manager of Dengue Project - Tahija Foundation for reviewing this manuscript.