dw for bio terrorism surveillance

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Data Warehousing for Bioterrorism

Surveillance

Authors:

Shipra Singal 08BM8055

Piyush Kumar 08BM8048

Ankit Maheshwari 08BM8083

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.

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


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to try to resolve these challenges. The difference

between the health care data warehousing and

bioterrorism data warehousing 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] v 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.

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

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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 previouslyunknown 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

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those exposed to the agents. The authors discuss issues

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.

Buehleret al[6]

in their paper describe that the detectionof 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

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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 and risk

assessment. It also recommends consolidating all

biological defense funding, research, and coordination.

The research paper by Howard Kirk Mardis[9]

discussesthe 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

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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 challenges of evaluation of

early warning of bioterroism. It also discusses what all isrequired 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 stateof 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 surveillancesystem for early detection of disease outbreaks.

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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 conceptsfrom 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.

Section 1: Introduction

Bioterrorism and the Threat

Bioterrorism is terrorism by intentional release or

dissemination of biological agents such as

bacteria, viruses, or toxins which 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

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disease, make them resistant to current medicines, or to

increase their ability to be spread into the environment.

Bioterrorism Agents: A biological agent is a disease-

causing organism or toxin produced from a biological

source. These 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: These include organisms or toxins that

pose the highest risk to the public and national security

because of:

Ease of their spread or transmission from person

to person

Result in high death rates and potential for major

public health impact

May cause public panic and social disruption

Require special action for public health

preparedness

Examples:

1) Anthrax: It is a non-contagious disease whose

vaccine does exist but requires many injections

for stable use. When discovered early, it can be

cured by administering antibiotics. Anthrax in

powder form delivered by mail was used in

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http://en.wikipedia.org/wiki/Anthrax_diseasehttp://en.wikipedia.org/wiki/Anthrax_disease


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a series of attacks on the offices of several United

States Senators in late 2001.

2) Smallpox: It is a highly contagious virus

transmitted easily through the atmosphere and

has a high mortality rate.

Category B: These agents are the second highest

priority because:

They are moderately easy to spread

Result in moderate illness rates and low death

rates

Require enhanced disease monitoring

Example: cholera

Category C: These third highest priority agents include

emerging pathogens that could be engineered for mass

spread in the future because of:

Ease of availability, production and spread

Potential for high mortality rates and major health

impact

Example: multiple drug-resistant tuberculosis strains

It is easy and inexpensive to obtain or produce thesebiological agents; can be easily disseminated, and can

also lead to widespread fear and panic. Thus,

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http://en.wikipedia.org/wiki/Virushttp://en.wikipedia.org/wiki/Virus


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bioterrorism has become an attractive weapon as a

threat to civilian populations.

Need for Data Warehousing

Unlike other types of attacks, responsibility for

bioterrorism acts is rarely claimed by terrorist groups.

Because of this, such an attack may take a very long

time to get detected unless some visible symptoms or

usual infection is observed in a large number of patients.

The effects of a bio terrorist attack are visible on a

number of levels:

Physical - actual diseases, unusual or usual

symptoms;

Psychological - fear, mass panic;

Economic - travel restrictions, business shut-

down;

Environmental visible on animals and Plants

There is a difficulty associated with the detection of suchsignals as it requires medical field people to

continuously look around and the general public to be

constantly vigilant. Because of this difficulty in detection,

Data warehousing can be used to facilitate rapid

detection of a future bioterrorist attack. Surveillance

systems based on Data warehousing that can target the

early manifestations of bioterrorism-related diseases

would be helpful. Data Warehousing could help in

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analyzing the situation and collection of data in an error-

free and prompt way. If these surveillance systems are

in place, they can enable earlier detection of bio terrorist

attacks (prevention plan) and more importantly, a

timelier public health response (contingency plan). The

diagnosis obtained from these surveillance systems will

guide the use of vaccinations and medications which are

critical to the public health.

Current response to Bioterrorism

Strengthening its area of bio defence, the US senate had

passed the Bioterrorism Act of 2002 according to

which, 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, India is still lacking any such kind

of law on bioterrorism. Though, the Defence Research

and Development Organization (DRDO), the arm of the

Department of Defence, has put efforts forward by the

way of developing laboratories for research to develop

counter measures against bioterrorism.

The first automated bioterrorism detection system

called RODS (Real-Time Outbreak Disease Surveillance)

was deployed by the University of Pittsburgh's Centre

for Biomedical Informatics in the year 1999. This system

collects data from many data sources and uses it to

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perform detection of possible bioterrorism event at the

earliest possible moment.

Researchers are still experimenting with various devices

to form a system that will monitor infected persons and

also try to find the origin of the outbreak.

Thus, Bioterrorism poses challenges for both the civilian

authorities. To prepare for a biological threat on the

population, there should be co-operation between the

civilian authorities from different sectors like public

health, law enforcement, prosecution and customs. The

health sector also needs to be adequately prepared with

the stock of necessary supplies for treatment i.e.

vaccines and antibiotics and also should be aware ofexisting dangers so as to be able to detect a covert

biological attack.

Section 2: Bioterrorism Surveillance

System

In recent times bioterrorism has emerges as a major

threat to the world and hence a new research area to

develop systems to detect bioterrorism accurately and

swiftly is coming up.

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A surveillance system which can be used for early

detection should include the following

Data Sources:Data sources for the systems will include

the information on web sites of relevant government and

nongovernment agencies.

Data Abstraction: For analyzing and collecting

surveillance data for bioterrorism systems should haveprograms to identify this type of data.

Data Extraction: The system should have data

collection and analytics capabilities which would be used

on surveillance data.

Data Synthesis: The data gathered is reviewed. The

systems collecting surveillance data and detection

system data should be designed. Surveillance systems

should be deployed for event-based and for continuous

bioterrorism surveillance.

Data Sources: The data is gathered from various

databases of articles, government reports, and web sites

of government and commercial enterprises. Social media

sites data is also incorporated. Government agencies

most likely to fund, develop, or use bioterrorism systems

should be identified. Data can also be gathered from

programs like MATRIX (Multi-state Anti-terrorism

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Information Exchange system) in USA. It helps in

information sharing and data analysis.

Data Abstraction: To identify relevant articles system

should review titles, abstracts, and full-length articles.

An example of diagnostic decision support systems can

be - If the system has bioterrorism-related illnesses in

the knowledge base, the system updates the probability

of bioterrorism-related illness.

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.

Data Synthesis [17]:

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.

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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). If a peak increase in

any chemical is detected, the instrument automatically

collects a 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 on and in which

direction. Potential people who are doing critical

developments on vaccines and biotechnology should betracked as these people can develop certain compounds

which might be of use for bioterrorists.

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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.

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

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terrorist attacks. The demonstration surveillance system

in Florida uses the flash data warehouse architecture.

The following section provides a brief description of thesurveillance 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

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

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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 system will lay initial focus on the following data to

get readl time data feed

Hostipal Discharge Data

Clinical Electronic Laboratory

Efforts from Merlin and Epicom

The CATCH data warehouse already incorporates the

hospital dischareg data for a variety of health status

indicator, which provides a very good assessment of

health indicators of the community. In addition, somepreliminary experiments with real-time reporting from

local hospitals have been conducted with great success.

It has been proved by various study and research that

the existing hospital admission and discharge data

warehouse components lays a sloide foundation for theexperiments.

Electronic laboratory reporting is the second area of

focus for data collection.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,

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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.

Pattern Recognition and Alarm Thresholds

Development of pattern recognition algorithm will be the

most challenging aspect of the development of the

demonstration system.

Defining the nature of abnormal patterns in the threat

indicator is also a challenging job. Extreme timeliness of

detection is very important for early detection of the

disease outbreak, this area is the most emerging area

for the researchers in the field of medical science. It is of

utmost importance to respond 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

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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.

Section 4: Conclusions

This paper identifies bioterrorism and its threats. Itclassifies 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.

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

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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 Richard E.Rothman, MD, PhD, Framework for the

Development of Response Protocols for Public

Health Syndromic Surveillance Systems: Case

Studies of 8 US States, Disaster Medicine and

Public Health Preparedness, 2009, 3 VOL.

/SUPPL. 1

4. Pascal Crepey and Marc Barthelemy, Detecting

Robust Patterns in the Spread of Epidemics:

A Case Study of Influenza in the United

States and France, American Journal of

Epidemiology, Advance Access publication

October 15, 2007,Vol. 166, No. 11

5. Mohammad Madjid, MD, Russell V. Luepker, MD,

MS, FACC, FAHA, Co-Chairs Kurt J. Greenlund,

PHD, Kathryn A. Taubert, PHD, FAHA, Michael J.

Roy, MD, MPH, FACP, Rose Marie Robertson, MD,

FACC, FAHA, Cardiovascular Effects of

Emerging Infectious Diseases and Biological

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Terrorism Threats, March 27,JACC Vol. 49, No.

12, 2007

6. James W. Buehler, Ruth L. Berkelman, David M.

Hartley, and Clarence J. Peters, Syndromic

Surveillance and Bioterrorism-related

Epidemics, Emerging Infectious Diseases, Vol. 9,

No. 10, October 2003

7. Arnold F. Kaufmann, Martin I. Meltzer, and George

P. Schmid, The Economic Impact of aBioterrorist Attack: Are Prevention and Post

attack intervention Programs Justifiable,

Centers for Disease Control and Prevention,

Atlanta, Georgia, USA

8. Brian C. Lein, A Bioterrorism Prevention

Strategy for the 21st Century

9. Howard Kirk Mardis, Lt Col, Counter

Bioterrorism US intelligence challenges,

USAF

10.The Biowatch by Dana A Shea and Sarah A Lister

11.Farzad Mostashari and Jessica Hartman,

Syndromic Surveillance: a Local Perspective

12.Amanda Hodges, Rick Sapp ,The Threat of

Agroterrorism and Bioterrorism in Florida-

Prevention and a Coordinated

Response,Florida Department of Agriculture and

Consumer Services, October 2006

13.Donald J. Berndt, Sunil Bhat, John W. Fisher, AlanR Hevner and James Studnicki ,Data Analytics for

Bioterrorism Surveillance, University of South

Florida

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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 surveillancesystem , Journal of the American Medical

Informatics Association, Volume 10 issue 5 ,

October 2003

15.Parsa Mirhaji , Public Health Surveillance Meets

Translational Informatics : A Desiderata , Journal

of the Association for Laboratory Automation,

Volume 14 Issue 3, June 2009

16.Ray R. Arthur, James W. Leduc, James M. Hughes,

Surveillance for Emerging Infectious

Diseases and Bioterrorism Threats, Tropical

Infectious Diseases , 2006

17.Dena M. Bravata, Kathryn M. McDonald, Wendy M.

Smith, Chara Rydzak, Herbert Szeto, David L.

Buckeridge, Corinna Haberland, Douglas K.

Owens, Systematic Review: SurveillanceSystems for Early Detection of Bioterrorism-

Related Diseases
http://www.annals.org/search?author1=Chara+Rydzak&sortspec=date&submit=Submithttp://www.annals.org/search?author1=Chara+Rydzak&sortspec=date&submit=Submit

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