Data Warehousing for Bio Terrorism Surveillance

8/9/2019 Data Warehousing for Bio Terrorism Surveillance

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Data Warehousing for Bioterrorism

Surveillance

Authors:

Shipra Singal 08BM8055

Piyush Kumar 08BM8048

Ankit Maheshwari 08BM8083

Vinod Gupta School of Management

IIT Kharagpur


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Abstract

This paper introduces the reader to the term Bioterrorism and its

threat on civilian populations. Further, it delves into the need, usage

and application of data warehousing in Bioterrorist attacks and its

surveillance. It also describes the features and technical challenges in

developing an effective bioterrorism surveillance system.A demonstration of a Bioterrorism surveillance system in the State of

Florida further showcases these ideas.


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Survey of Literature

Donald J. Berndt et al[1]

in their paper have discussed several technical

challenges in the development of an effective bioterrorism

surveillance system. They have used health care data warehousing

research as the basis to try to resolve these challenges. The difference

between the health care data warehousing and bioterrorism datawarehousing as described in this paper is that surveillance systems for

bioterrorism require more timely data and real-time data warehousing

approaches. They have introduced the concept of flash data

warehousing to compare real-time healthcare data with historical

patterns of key surveillance indicators.

Carol C. Diamond et al[2]

in their paper on Health IT systems

emphasize that Technology should enable researchers, practitioners,

and public health officials to share data across networks, while

protecting patients privacy. Health information technology (IT) has

great potential to transform health care and inform population health

goals in clinical research, quality measurement, and public safety. But

to fully realize the benefits of health IT for population health, focus

must be on new models that maximize efficiency, encourage rapid

learning. In this paper the authors explore the advantages of a

networked model for analysing population health information and

provide several examples.


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Lori Uscher-Pines et al[3]

in their research on public health surveillance

systems studied 8 US states. Their objective was to describe current

syndromic surveillance system response protocols and develop a

framework for health departments to use as a guide in initial design

and/or enhancement of response protocols. The research was carried

out by conducting in depth interviews with health department staff.

The conclusion from the research was that health departments had

not prioritized the development and refinement of response protocols

due to reasons like lack of guidance, limited resources for

development of response protocols, and few examples of syndromic

surveillance detecting previously unknown events of public health

significance. The authors have proposed a framework which can guide

health departments in creating protocols that will be standardized,

tested, and relevant given their goals with such systems.

Pascal Crepey et al[4]

in their paper develop a method of detecting

correlations between epidemic patterns in different regions that are

due to human movement and introduce a null model in which the

travel-induced correlations are cancelled. This method is then applied

to cases of seasonal influenza outbreaks in the United States and

France. This paper basically tells how to interpret data statistically.

Madjid et al[5]

in their paper elaborate that natural outbreak of

emerging infections or release of biologic agents during a bioterrorism

attack could have a considerable impact on the cardiovascular systems

of those exposed to the agents. The authors discuss issues


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surrounding basic, clinical, and population science research and

training needs with regards to emerging infectious diseases and

biological threats. They describe the need for surveillance systems

that might increase our ability to quickly identify disease outbreaks

and track their course.

Buehler et al[6]

in their paper describe that the detection of a

bioterrorism-related epidemic depends on population characteristics,

availability and use of health services, the nature of an attack,

epidemiologic features of individual diseases, surveillance methods,

and the capacity of health departments to respond to alerts. The

authors emphasize that understanding their effect on epidemic

detection should help define the usefulness of syndromic surveillance

and identify approaches to increasing the likelihood that clinicians

recognize and report an epidemic.

The article by Arnold F. Kaufmann et al[7]

covers the economic impact

of a bioterrorist attack. It estimates the cost assumes a suburban city

of population 100,000 when attacked by Bacillus anthracis, Brucella

melitensis, and Francisella tularensis. The paper takes into account

the cost of hospitalization based on various parameters like days a

patient need to be in the hospital etc. It also evaluates the economic

preparedness to fight bioterrorism.

The article by Brian C Lein [8] has drawn the attention towards the risk

assessment of bioterrorism. It discusses the detection and prevention

of the population from bioterrorism. It discusses evaluation of threat


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and risk assessment. It also recommends consolidating all biological

defense funding, research, and coordination.

The research paper by Howard Kirk Mardis[9]

discusses the threat of

bioterrorism and how to make the system more dynamic and efficient

to cater to threats of Bioterrorism. It covers the need to adopt better

information management and human resources systems to fight

bioterrorism. It mentions the trends in bioterrorism and how the

bioterrorist group is different from the rest of the groups. It focuses on

information management and Information structure and how they

help in countering terrorism. The paper mentions the need of special

information managers and information broker to manage information

related to bioterrorism. The paper mentions about analytics and the

human resources also.

The article by Dana A Shea and Sarah A Lister[10]

discusses the

biowatch program. It gives insight as what the program is and which

all US cities are covered under it. It discusses the technical issues

about the issues regarding sensors which can detect bioterrorism. It

also stated bioterrorism analytical issues. The paper also covers the

future of biowatch program and also the concerns regarding the policy

which is in place. It mentions the distributed detection networks to be

used under the biowatch program.

The paper by Farzad Mostashari and Jessica Hartman[11]

covers the

early warning for bioterrorist attack and bio surveillance. The paper

highlights new uses of analytical techniques. It highlights the


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challenges of evaluation of early warning of bioterroism. It also

discusses what all is required to make surveillance to reach its full

potential data standardization, data flow, data security etc.

The paper by Amanda Hodges and Rick Sapp covers the threat of bio

terrorism and agroterrorism to the state of floirda. The paper

examines vulnerability of various industries to bio attacks with special

focus on plant and animal industries. The paper further examines the

national diagnostic network.

The paper by Donald J. Berndt, Sunil Bhat, John W. Fisher, Alan R

Hevner and James Studnicki discusses use of data analytics for

bioterrorism surveillance. The paper also explains the use of catch

data warehouse. Further the paper examines the surveillance system

at the state of florida using data analytics.

The Paper by Fu Chiang Tsui, Jeremy U Espino, Virginia M. Dato, Per

H. Gesteland, Judith Hutman, and Michael M. Wagner defines the

design and implementation of the Real time outbreak and disease

surveillance (RODS) system, a computer based public health

surveillance system for early detection of disease outbreaks.

The Paper by Parsha Mirhaji examines the current state of the

conceptualization, design, analysis, and implementation of PHS

systems from a translational informatics perspective. The paper

applies concepts from cognitive science and knowledge engineering to

suggest directions for improvement and further research.

The book by Ray R. Arthur, James W. Leduc, James M. Hughes looks

into the various infectious diseases which spread rapidly. It examines

various surveillance and response networks. It also examines the

critical role of the laboratory in surveillance of bio terrorism.


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Section 1: Introduction

Bioterrorism and the Threat

Bioterrorism is terrorism by intentional release or dissemination

of biological agents (bacteria, viruses, or toxins); these may be in a

naturally-occurring or in a human-modified form.

According to the US-based Centres for Disease Control and

Prevention:

A bioterrorism attack is the deliberate release of viruses, bacteria, or

other germs (agents) used to cause illness or death in people, animals,

or plants. These agents are typically found in nature, but it is possible

that they could be changed to increase their ability to cause disease,

make them resistant to current medicines, or to increase their ability

to be spread into the environment. Biological agents can be spread

through the air, through water, or in food. Terrorists may use

biological agents because they can be extremely difficult to detect and

do not cause illness for several hours to several days. Some

bioterrorism agents, like the smallpox virus, can be spread from

person to person and some, like anthrax, cannot.

Bioterrorism Agents: A biological agent (or pathogen) is a

disease-causing organism or toxin produced from a biological


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source. These can include a bacterium, virus, fungus, or

biological toxin.

Bioterrorism agents can be separated into three categories, depending

on how easily they can be spread and the severity of illness or death

they cause. Category A agents are considered the highest risk and

Category C agents are those that are considered emerging threats for

disease.

Category A: These high-priority agents include organisms or toxins

that pose the highest risk to the public and national security because:

They can be easily spread or transmitted from person toperson

They result in high death rates and have the potential formajor public health impact

They might cause public panic and social disruption They require special action for public health preparedness.

Examples:

1) Anthrax: Anthrax is a non-contagious disease. An anthraxvaccine does exist but requires many injections for stable use.

When discovered early anthrax can be cured by

administering antibiotics. Anthrax was used in a series of

attacks on the offices of several United States Senators in late
http://en.wikipedia.org/wiki/Anthrax_diseasehttp://en.wikipedia.org/wiki/Anthrax_vaccineshttp://en.wikipedia.org/wiki/Anthrax_vaccineshttp://en.wikipedia.org/wiki/Antibiotichttp://en.wikipedia.org/wiki/2001_anthrax_attackhttp://en.wikipedia.org/wiki/2001_anthrax_attackhttp://en.wikipedia.org/wiki/2001_anthrax_attackhttp://en.wikipedia.org/wiki/2001_anthrax_attackhttp://en.wikipedia.org/wiki/2001_anthrax_attackhttp://en.wikipedia.org/wiki/Antibiotichttp://en.wikipedia.org/wiki/Anthrax_vaccineshttp://en.wikipedia.org/wiki/Anthrax_vaccineshttp://en.wikipedia.org/wiki/Anthrax_vaccineshttp://en.wikipedia.org/wiki/Anthrax_disease


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2001. The anthrax was in a powder form and it was delivered

by the mail.

2) Smallpox: Smallpox is a highly contagious virus. It istransmitted easily through the atmosphere and has a

high mortality rate (20-40%). Smallpox was eradicated in the

world in the 1970s. However, some virus samples are still

available in Russian and American laboratories. As a biological

weapon smallpox is dangerous because of the highly

contagious nature of both the infected and their pox. Also, the

infrequency with which vaccines are administered among the

general population since the eradication of the disease would

leave most people unprotected in the event of an outbreak.

Smallpox occurs only in humans, and has no external hosts or

vectors.

Category B: These agents are the second highest priority because:

They are moderately easy to spread They result in moderate illness rates and low death rates They require specific enhancements of CDC's laboratory

capacity and enhanced disease monitoring.

Example: typhus, brucellosis, cholera

Category C: These third highest priority agents include emerging

pathogens that could be engineered for mass spread in the future

because:
http://en.wikipedia.org/wiki/Smallpoxhttp://en.wikipedia.org/wiki/Virushttp://en.wikipedia.org/wiki/Mortality_ratehttp://en.wikipedia.org/wiki/Smallpox#Eradicationhttp://en.wikipedia.org/wiki/Russiahttp://en.wikipedia.org/wiki/United_Stateshttp://en.wikipedia.org/wiki/United_Stateshttp://en.wikipedia.org/wiki/Russiahttp://en.wikipedia.org/wiki/Smallpox#Eradicationhttp://en.wikipedia.org/wiki/Mortality_ratehttp://en.wikipedia.org/wiki/Virushttp://en.wikipedia.org/wiki/Smallpox


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They are easily available They are easily produced and spread They have potential for high morbidity and mortality rates and

major health impact

Example: multiple drug-resistant tuberculosis strains

Bioterrorism has become an attractive weapon because biological

agents are relatively easy and inexpensive to obtain or produce, can

be easily disseminated, and can cause widespread fear and panic

beyond the actual physical damage they can cause.

, even though biological warfare itself is as old as the human race.

Over the centuries, there have been many attempts to initiate the

spread of infectious diseases. Recently, the phenomenon of

bioterrorism has gained momentum and bioweapons have become a

threat to civilian populations.

Need for Data Warehousing

Responsibility for bioterrorism acts is rarely claimed by terrorist

groups, as is usually the case with other types of attacks. A covert

attack may thus take a long time to be detected. As the first visible

indication that a bioweapon had been used would be a great number


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of patients with similar symptoms and/or presence of an unusual

infection.

The effects of the attack will be visible on a number of levels like:

Physical - actual diseases; Psychological - fear, mass panic; Economic - travel restrictions, business shut-down; Environmental visible on humans, animals, Plants

To detect warning signs for Bioterrorism attacks, the medical

community should look out for unusual diseases not typically seen in

the area and the general public should constantly be vigilant for

bioterrorism.

Because of the difficulty in detection, Data warehousing can be used

to facilitate rapid detection of a future bioterrorist attack. Data

warehousing Surveillance systems that target the early manifestations

of bioterrorism-related disease are required. The surveillance efforts

and preparedness towards biowar would be fool-proof if the DWtechnique is used and methods of analyzing the situation and data

collection are error-free and prompt.

The goal of these surveillance systems will be to enable earlier

detection of epidemics and a more timely public health response,

hours or days before disease clusters are recognized clinically, or

before specific diagnoses are made and reported to public health

authorities. Establishing a diagnosis is critical to the public health


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response to a bioterrorism-related epidemic, since the diagnosis will

guide the use of vaccinations, medications, and other interventions.

Current response to Bioterrorism

To strengthen the area of biodefence, the US senate has passed the

Bioterrorism Act of 2002. According to this law, there is an essential

element of national preparedness against bioterrorism and the focus

is on safety of drugs, food and water from biological agents and toxins.

However, in India such law on bioterrorism is still lacking. In India,

efforts have been put forward by the Department of Defence, through

its arm called the Defence Research and Development Organisation

(DRDO) to develop counter measures against bioterrorism. A few

laboratories of the DRDO are active in this area of research. To

prepare for nuclear, biological and chemical warfare these

laboratories have developed protective systems and equipment for

troops.

In 1999, the University of Pittsburgh's Centre

for Biomedical Informatics deployed the first automated bioterrorism

detection system, called RODS (Real-Time Outbreak Disease

Surveillance). RODS is designed to draw collect data from many data

sources and use them to perform signal detection, that is, to detect a

possible bioterrorism event at the earliest possible moment.


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In Europe, disease surveillance is beginning to be organized on the

continent-wide scale needed to track a biological emergency. The

system not only monitors infected persons, but attempts to discern

the origin of the outbreak. Researchers are experimenting with

devices to detect the existence of a threat:

Tiny electronic chips that would contain living nerve cells towarn of the presence of bacterial toxins (identification of

broad range toxins)

Fiber-optic tubes lined with antibodies to light-emittingmolecules (identification of specific pathogens, such as

anthrax, botulinum, ricin)

Thus, Bioterrorism poses obvious challenges for civilian authorities.

Such a situation calls for close local co-operation between civilian

authorities from different sectors (public health, law enforcement,

prosecution and customs), national leadership to hold all sectors

together, and international co-operation within the areas concerned.

These could include intelligence services, medicine, the fight against

terrorism and implementation of international conventions.

The health sector should be adequately prepared, that is, not only

stocked with necessary supplies for treatment (vaccines, antibiotics)

but also aware of existing dangers so as to be able to detect a covert

biological attack.


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Section 2: Bioterrorism Surveillance System

Developing accurate and reasonable specific surveillance systems

capable of identifying bioterrorism accurately and swiftly is one of the

most active areas of development and research relating to

bioterrorism.

A surveillance system which can be used for early detection shouldinclude the following

Data Sources:Web sites of relevant government and nongovernment

agencies.

Data Abstraction: Reports that described or evaluated systems for

collecting, analyzing, or presenting surveillance data for bioterrorism-

related illnesses or syndromes.

Data Extraction: Method of collection, analysis, and presentation of

surveillance data; and outcomes of evaluations of the system

Data Synthesis: The data gathered is reviewed. The systems collecting

syndromic surveillance data and detection system data were designed.

Syndromic surveillance systems have been deployed for both event-

based and continuous bioterrorism surveillance.


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Data Sources: The data is gathered from databases of peer-reviewed

articles, government reports, and web sites of relevant government

and commercial entities. Social media sites data is also incorporated.

Government agencies most likely to fund, develop, or use bioterrorism

systems should be identified.. We searched the Web sites of these

government agencies and other academic and commercial sites.

Finally, we identified additional articles from the bibliographies of

included articles and from conference proceedings. Data can also be

gathered from programs like MATRIX (Multi-state Anti-terrorism

Information Exchange system) in USA. . This program helps to facilitate

collaborative information sharing and factual data analysis.

Data Abstraction: System should reviewed titles, abstracts, and full-

length articles to identify potentially relevant articles. An example of

diagnostic decision support systems can be - If we recorded whether

bioterrorism-related illnesses were included in the system's

knowledge base, how the system enabled updates of the probability

of bioterrorism-related illness as epidemic progresses.

Data Extraction: Extraction is the operation of extracting data from a

source system for further use in a data warehouse environment. This

is the first step of the ETL process. After the extraction, this data can

be transformed and loaded into the data warehouse. The source

systems for a data warehouse are typically transaction processing

applications and in this case would be the data source system which

gives the input of the terrorists.


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Data Synthesis:

The data gathered from the various sources should be analyzed

through various tools and techniques and appropriate patterns should

be identified. Meaningful conclusions should be derived from the data

gathered for further action.

Surveillance Systems should be installed for monitoring various

scenarios. The systems should be developed for identification of the

scenarios discussed below.

Surveillance Systems for Collecting Environmental Detection Data:

Detection Systems should be deployed which transmit data collected

from environment. These systems differ in the type and location of

sample collected (for example, aerosol samples continuously taken

from locations in fixed sites, such as airports or public buildings If a

peak increase in any chemical is detected, the instrument

automatically collects an sample and alerts the control center.

Surveillance Systems Collecting Clinical Reports: Systems that collect

clinical information from networks of sentinel clinicians. These

systems will keep track of the supplies of some chemicals which can

be used by bioterrorist groups. Monitoring system which will track the

people who are purchasing these chemicals will also be a part of the

surveillance system.

Surveillance Systems Collecting Laboratory Data: Data from the lab

should be collected in order to access what all developments are going


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on and in which direction. Potential people who are doing critical

developments on vaccines and biotechnology should be tracked as

these people can develop certain compounds which might be of use

for bioterrorists.

Surveillance Systems Collecting Illness Data: Systems which collect

the data related to illness relating to food items, chemicals or illness

which have been or have the potential to be widespread should be

kept an eye on. Systems should take into account data related to any

incidence which can be a test incidence for bioterrorist group.

Surveillance Systems Collecting Animal Disease Data: Systems which

collect animal disease data should be under surveillance as these data

can be a test data for bioterrorist testing hazardous chemicals.

Evaluation of Reports of Surveillance Systems: All the surveillance

systems need to be integrated. The reports generated by theses

surveillance systems need to be analyzed and proper meaning from

the data needs to be derived.


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Section 3: Live case example: State of Florida

The state of Florida has its own surveillance system using data

warehousing to detect early signs of bio terrorist attacks. The

demonstration surveillance system in Florida uses the flash data

warehouse architecture.

The following section provides a brief description of the surveillance

system deployed in Florida

Bio Terrorism Threat Indicators

In any bio terrrorism surveillance system it is most important that the

threats are recognised at an early stage. This will help in controlling

the effect of the attack or the threat.The surveillance system in Florida

uses their expertise in CATCH health care data sets and biological

agents to key bio terrorism threat indicators.

Large Volume of data are collected from the following resources

Air Quality Monitors Water Quality Monitors ER Signs and symptoms Hospital Admissions State Laboratories Pharmacy Data Practitioners office


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Data collected from all the mentioned resources are analysed. They

are coupled with real time data from the hospitals for the

demonstration system. Potential threat indicators that can be defined

based on International Classification of Diseases (ICD) codes and

derived from hospital admission/discharge data.

Real-Time Data Feeds

The initial foci of the demonstration surveillance system will be on

hospital admission discharge data, clinical electronic laboratory

reporting, and existing efforts such as the Merlin and EpiCom

systems. The ongoing community assessment work sup ported by the

CATCH data warehouse already incorporates hospital discharge data

for a variety of health status indicators. In addition, some preliminary

experiments with real-time reporting from local hospitals have been

conducted with great success.

Therefore, the existing hospital admission/discharge data warehouse

components provide a sound foundation for experimentation.

The second area of data collection will focus on electronic laboratory

reporting (ELR).This area of research has received a good deal of

attention, with several successful efforts around the country. The

successful application of the HL7 messaging standards, laboratory test

standards such as Logical Observation Identifiers, Names, and Codes

(LOINC), and vocabularies like the Systematized Nomenclature of

Human and Veterinary Medicine (SNOMED) make this an appropriate

area for the demonstration of surveillance systems.


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Pattern Recognition and Alarm Thresholds

One of the most challenging aspects of the demonstration system will

be developing pattern recognition algorithms and defining the nature

of abnormal patterns in the selected threat indicators. The early

detection of disease outbreaks is an emerging area of research that

demands extreme timeliness of detection for identifying and

responding to public health threats. There has been a surge of interest

in such early warning systems and corresponding attention to some

fundamental questions.

Which data are useful for early detection?

What are the timeliness requirements for outbreaks caused by

different agents?

How do we measure timeliness of a detection system for a specific

type of outbreak and especially for outbreaks such as large-scale

inhalation anthrax that have not occurred in areas monitored by the

new systems?

Solutions to these complex pattern recognition and early detection

problems will only come from sustained research and development.

There is no silver bullet here.


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Section 4: Conclusions

This paper identifies bioterrorism and its threats. It classifies the

agents of bioterrorism and establishes the fact that Bioterrorism has

become one of the major challenges of the 21st century. It identifies

the need for data warehousing to tackle bioterrorism. The paper

covers current response to bioterrorism. Factors incorporated in a

surveillance system used to prevent bioterrorism are identified and

systems needed for collecting various sources of data are identified. A

case of state of Florida is included as a live case study at the end of the

paper.


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References

1. Donald J. Berndt, Alan R. Hevner, and James Studnicki,Bioterrorism Surveillance with Real-Time Data Warehousing,

University of South Florida, Tampa, FL 33620

2. Carol C. Diamond, Farzad Mostashari, and Clay Shirky,Collecting And Sharing Data For Population Health: A New

Paradigm, H e a l t h I T S y s t e m s, Health Aff

(Millwood) March 1, 2009 28:454-466

3. Lori Uscher-Pines, PhD, Corey L. Farrell, MPH, Steven M.Babin, MD, PhD, Jacqueline Cattani, PhD, Charlotte A. Gaydos,

DrPH, Yu-Hsiang Hsieh, PhD, Michael D. Moskal, MBA, and

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Robertson, MD, FACC, FAHA, Cardiovascular Effects of

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9. Howard Kirk Mardis, Lt Col, Counter Bioterrorism USintelligence challenges, USAF

10.The Biowatch by Dana A Shea and Sarah A Lister11.Farzad Mostashari and Jessica Hartman, Syndromic

Surveillance: a Local Perspective

12.Amanda Hodges, Rick Sapp ,The Threat of Agroterrorism andBioterrorism in Florida- Prevention and a Coordinated

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14.Fu Chiang Tsui, Jeremy U Espino, Virginia M. Dato, Per H.Gesteland, Judith Hutman, and Michael M. Wagner , Technical

description of RODS: a real time public health surveillance


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Data Warehousing for Bio Terrorism Surveillance

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