Welcome, Program Overview,

Greeting from the International Society for Disease Surveillance

       Plenary Session: Opening Remarks and Keynote Speeches

Opening Remarks

Virginia Caine, MD

Director, Marion County Public Health Department

Associate Professor of Medicine, Indiana University School of Medicine

Past President, American Public Health Association

Keynote Speakers

William Karesh, DVM

Director, Field Veterinary Program (FVP) of the Wildlife Conservation Society

David Blazes, MD

Director of the Emerging Infections Program at the Naval Medical Research Center Detachment, Lima, Peru

       Plenary session: “Best of the conference: Novel Applications” Incorporating Water Security into Syndromic Surveillance – Steve Babin
Surveillance of Extreme Urban Heat Events Using Satellite Imagery and Geographical Information Systems – Daniel Johnson

Early Detection of Tuberculosis Outbreaks among the San Francisco Homeless – Mojdeh Mohtashemi


T rack 2: Analytical Methods: Spatial Detection Methods – Grand 2 – Second Floor

Modifications to Spatial Scan Statistics for Estimated Probabilities at Fine-Resolution in Highly Skewed Spatial Distribution – James Edgerton

An Outbreak Detection Algorithm that Efficiently Performs Complete Bayesian Model Averaging Over All Spatial Clusters of Disease – Yanna Shen

Dual Graph Spatial Cluster Detection for Syndromic Surveillance in Networks –        Luiz Duczmal

A Scan Statistic based on Anscombe’s Variance Stabilization Transformation –    Kunihiko Takahashi  

A Spatial Scan Statistic Scanning Only the Regions with Elevated Risk – Toshiro Tango


Track 3: Public Health Practice: Expanding the use of surveillance systems

Emergency Department Syndromic Surveillance and Population-Based Health Monitoring in Los Angeles County –  Emily Kajita

Increasing the Return-on-Investment from Syndromic Surveillance – Shandy Dearth

Detection of Carbon Monoxide Poisoning in Chief Complaint Data – Jian-Hua Chen

Improving Rabies Surveillance Using Syndromic Data – Michael Wade

Using Syndromic Surveillance Data for Enhanced Case-Capture of Conditions of Public Health Interest – Jeffrey Johnson  


Track 4: Evaluation and Performance: Evaluation of data sources

Is Crude Mortality Data Suitable for Real Time Surveillance? – Liselotte van Asten

High-Performance, EMR-Based Detection Of Acute Infectious Respiratory Illnesses – Sylvain DeLisle

Comparing the Utility of Ambulatory Care and Emergency Room Data for Disease Outbreak Detection – Marcelo Costa

Combining Laboratory Test Orders and Outpatient Visits to Monitor Respiratory Illness – Cara Olsen 

Correlation between Alerts Generated from Electronic Medical Record (EMR) Data Sources and Traditional Data Sources – Michael Thompson


Track 5: Novel Applications: Novel Health Outcomes –

Detecting and Preventing Emerging Epidemics of Crime – Daniel Neill

A Novel Application of Surveillance Algorithms in Childhood Immunization Program Monitoring – Laura McDonald

Health Impact of the 2006 Heat Wave Based on Syndromic Surveillance in Gironde, France – Gaelle Gault

The Association Between Temperature and 911 Calls for Heat-Illness: Potential for Surveillance – Kate Bassil

Identifying Fractures in BioSense Radiology Reports – Achintya Dey

Track 1: Data Acquisition and Processing: Approaches to System Architecture and Data Capture

Services Oriented Architectures and Just in Time Deployment of Ad-Hoc Health Surveillance Systems – Parsa Mirhaji

Electronic Support for Public Health (ESP): Automated Detection and Reporting of Notifiable Diseases – Michael Klompas

SurvNet – Electronic Surveillance System for Infectious Disease Outbreaks in Germany – Karl Schenkel

The Snow Agent System: A Peer-to-Peer System for Disease Surveillance and Diagnostic Assistance – Johan Bellika

Experimental Fully Automatic Syndromic Surveillance in Japan – Yasushi Ohkusa


Track 2: Analytical Methods: Multivariate Detection Methods

Nonparametric Scan Statistic for Multivariate Disease Surveillance – Daniel Neill

Designing Epidemiological Networks for Real-world Surveillance Settings – Ben Reis

Minimizing False Alarms in Syndromic Surveillance – William Peter

A Simple Method of Using Linked Health Data in Syndromic Surveillance – Steve Babin

Incorporating Learning into Disease Surveillance Systems – Daniel Neill

Track 3: Public Health Practice: Surveillance System Sensitivity

Use of Syndromic Surveillance in the Investigation of Salmonella Wandsworth Outbreak – Erin Murray

Use of Surveillance Data to Measure the Impact of Viral Infections among Young Children – Florence Bourgeois

Event Detection in a Vulnerable Population – Erin Murray

Surveillance for Influenza Using the EDSS and HASS Systems, Connecticut, 2004-2007 – Katherine Purviance

Clinical Surveillance Markers of Influenza-like Illness (ILI) at the Veterans Affairs (VA) Hospital – Supriya Rao

Track 4 : Evaluation and Performance: Approaches and Tools for Evaluation

Proposal of a Framework for Evaluating Military Surveillance Systems for Early Detection of Outbreaks – Jean-Baptiste Meynard

The Tradeoffs Driving Policy and Research Decisions in Biosurveillance –

Howard Burkom

Effect of Work-related Mobility in the Simulation of Aerosol Anthrax Releases with BARD – Aurel Cami

Benchmark Data Generation from Discrete Event Contact Network Models – David Bauer

Learning Stable Multivariate Baseline Models for Outbreak Detection — Sajid Siddiqi

Track 5: Novel Applications: Novel Public Health/Epidemiology Applications

Spatial Analysis of an Outbreak of Q Fever – Louise Wilson

Using Electronic Surveillance Systems in Resource-Poor Settings: Why and How –Sheryl Happel Lewis

Tuberculosis Surveillance, Republics of Armenia and Georgia, 2003-2004 –

Daniel Ehlman

Active Fever Surveillance During Malaria Outbreak in Western Jamaica – Maung Aung

Real Time EMS Events as Surrogate Events in Syndromic Surveillance –  Alex Garza

Track 1: Data Acquisition and Processing: Beyond the Chief Complaint

Processes for Data Gathering, Assessment and Disease Event Tracking  — Camilla Kristensen

An Efficient Approach To Map LOINC Concepts To Notifiable Conditions –  Wendy Li

Investigating Syndromic Peaks Using Remotely Available Electronic Medical Records – John Allegra

Automated Detection of GI Syndrome using Structured and Non-Structured data from the VA EMR – Brett South

Automated Detection of Tuberculosis Using Electronic Medical Record Data –

Michael Calderwood


Track 2: Analytical Methods: Spatio-temporal and Temporal Detection Methods

Performance Characteristics of Control Chart Detection Methods – Jerome Tokars

Development and Evaluation of a Data-adaptive Algorithm for Univariate Temporal Biosurveillance Da ta – Yegneniy Elbert

Recursive Least Squares Prediction of Syndromic Data for Surveillance – Amir Najmi

STL and Local Regression for Modeling Disease Surveillance Counts – David Anderson

A Space Time Permutation Scan Statistic with Irregular Shape for Disease Outbreak Detection – Marcelo Costa

Track 3: Public Health Practice: Inter-agency Coordination of Surveillance

Cross Border Syndromic Surveillance: Overview and Recommendations from an ISDS Consultation – Kieran Moore

Super Bowl Surveillance:  An Exercise in Inter-Jurisdictional Public Health Information Sharing – Carol Sniegoski

Increasing Local Access to Syndromic Surveillance Data – Michael Wade

Expert Meeting on Legal and Ethical Issues in Syndromic Surveillance – Mike Stoto

Situational Awareness Using Web-based Annotation and Custom Reporting – Amy Ising


Track 4 : Evaluation and Performance: Applied System Evaluation 

Enhanced surveillance improved timeliness and sensitivity at the FIFA 2006 World Cup in Germany —  Karl Schenkel 

Performance of a Syndromic Surveillance System During a Heat Wave – Loic Josseran

Navy Disease Reporting System Case Validation through Use of HL7 and SADR/SIDR Databases : Chlamydia – Gosia Kubiak

Preliminary Findings from the BioSense Evaluation Project – James Buehler

Syndromic Surveillance for Influenza in Washington State: A Local and Regional Perspective – Nicola Marsden-Haug

Track 5: Novel Applications: Novel Data Sources

Incorporating Geographical Contacts into Social Network Analysis for Contact Tracing in Epidemiology: A Study on Taiwan SARS Data – Cathy Larson

Implementation of a Syndromic Surveillance System Using a General Practitioners House Calls Network – Claude Flamand

Arizona’s Near Real Time School-based Syndromic Surveillance Program –  Lea Trujillo

Death Certificate Surveillance in New Hampshire – Christopher Taylor

North Dakota Electronic Animal Health Surveillance System – Julie Goplin

Track 1: Analytical Methods/Data Acqu isition and Processing Joint Se ssion: Syndrome Definition and Classification

Syndromic Surveillance Case Definition Development Using Recursive Partitioning Techniques – Nicholas Soulakis

Exploring Syndrome Definition by Applying Clustering Methods to Electronic Health Records Data – Samantha DeLeyon

The Performance of Sub-Syndrome Chief Complaint Classifiers for the GI and RESP Syndromes – Hwa-Gan Chang

Detection of Pneumonia Using Keywords in the Radiology Text Reports: Experience from BioSense – Armen Asatryan

Exception Reporting Systems for Flu Like Syndromes in Scotland – James McMenamin

Track 2: Analytical Methods: Agents, Visualization, and Decision Support

A Nationwide Geo-Referenced Synthesized Agent Database for Infectious Disease Models – William Wheaton

Distributed Multi-agent Architecture for Decision Support in Public Health Networks – Zahrui Mnatsakanyan

Bayesian Network Data Fusion Visualization – Charles Hodanics

Delineating Spatial Clusters with Artificial Neural Networks – Luiz Duczmal

Structured Information Sharing in Disease Surveillance Systems – Wayne Loschen

Track 3: Public Health Practice: System Design and Alert Analyses

A Model-Based Architecture for Supporting Situational Diagnosis in Real-Time Surveillance Systems – Herve Chaudet

Criteria for Prioritizing Statistical Anomalies Identified in BioSense – Colleen Martin

Could Syndromic Surveillance Data Be Used Effectively with Other Data Sources? A Transposable Local View – Sarah Winn

Can Telehealth Ontario Respiratory Call Volume be Used as a Proxy for Emergency Department Respiratory Visit Surveillance by Public Health ? – Adam van Dijk 

Utilizing a Patient Tracking System for Public Health Emergencies – Laura Williams

Track 4 : Evaluation and Performance: Evaluation of Detection Algorithms

Empirical Comparison of Spatial Scan Statistics for Outbreak Detection – Daniel Neill

Evaluation of Spatial Estimation Methods for Cluster Detection – Jian Xing

A Pilot Study of Aberration Detection Algorithms with Simulated Data –

Hwa-Gan Chang

Performance of an Adaptive Anomaly Detection Algorithm for a Low Incidence Syndrome Before and After a Major Outbreak – Sylvia Halasz

Characterization of Patients with Clinical Features Consistent with Inhalational Anthrax in an ED – Nicholas Soulakis

Track 5: Novel Applications: Novel use of On-line Data Sources

Use of Google Earth to Facilitate GIS-based Decision Support Systems for Arthropod-borne Diseases – Lars Eisen

Automatic Foot-and-Mouth Disease (FMD) News Monitoring and Classification – Cathy Larson

Detecting Web Rumours with a Multilingual Ontology Supported Text Classification System – Nigel Collier

Evaluation of Online Media Reports for Global Infectious Disease Intelligence – John Brownstein

Argus: A Global Detection and Tracking System for Biological Events – James Wilson

Plenary Session: MIDAS, an NIH program to model infectious diseases

The MIDAS (Models of Infectious Disease Agent Study) program is an international consortium of scientists who develop models of the emergence and spread of infectious diseases; MIDAS research has informed public policy in the United States and internationally.  As part of its ongoing work, MIDAS has generated data and tools that are available to the research community.  This plenary session will introduce these resources and focus on MIDAS research relevant to disease surveillance.

        Plenary Session: Remarks from Dr. Leslie Lenert, Director of the National Center for Public Health Informatics, CDC