Online Program

Interactive pandemic exercise toolkit

Monday, November 4, 2013 : 2:50 p.m. - 3:10 p.m.

Samuel Scarpino, PhD, Santa Fe Insitute, Santa Fe, NM
Greg Johnson, Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX
Nedialko Dimitrov, PhD, Operations Research, Naval Postgraduate School, Monterey, CA
Bruce Clements, MPH, Division for Regional and Local Health Services, Texas Department of State Health Services, Austin, TX
Alison Galvani, PhD, School of Medecine, Yale University, New Haven, CT
Lauren Meyers, PhD, Section of Integrative Biology, The University of Texas at Austin, Austin, TX
Background – During a pandemic, public health authorities must make critical real-time intervention decisions, often in the face of considerable uncertainty about the magnitude and severity of the pandemic. Preparedness plans and real-time decision support tools are thus essential to pandemic readiness. In collaboration with the Texas Department of State Health Services, we developed an interactive pandemic toolkit to aid in influenza preparedness and response. The toolkit includes a data-driven, individual-level influenza simulator, as well as decision-support modules for antiviral, vaccine and ventilator distributions. This presentation will demonstrate these tools and address the extendibility of this toolkit to other regions.

Objective – To develop an interactive, real-time environment for simulating pandemic influenza, assessing public health intervention strategies, and designing surveillance networks.

Methods – The Pandemic Exercise Tool has two primary components. The first component is a stochastic, influenza simulator for the state of Texas. This simulator tracks an epidemic as it spreads through Texas, includes realistic travel and demographic information, and incorporates a variety of intervention strategies. Second, we developed an efficient algorithm for designing surveillance networks. This method is able to simulate data that is statistically similar to the existing influenza surveillance data collected by the state.

Results – This tool has proven to be a powerful training resource for state and local public health agencies in Texas.

Conclusions – Our results demonstrate two important features of the simulator: (1) the ability of exercise participants to specify a pandemic scenario, and then, as the simulated pandemic unfolds, interactively make policy decisions (regarding vaccination, antiviral and public health communications), assess the ramifications, and rewind the clock to any point in the pandemic to assess alternative policies, and (2) the benefit of a realistic model of influenza surveillance which forces exercise participants to make decisions based on typical, imperfect epidemiological data

Learning Areas:

Implementation of health education strategies, interventions and programs
Planning of health education strategies, interventions, and programs
Public health or related research

Learning Objectives:
Demonstrate how exercise participants were able to specify a pandemic scenario, and then, as the simulated pandemic unfolds, interactively make policy decisions, (2) assess the ramifications of the policy decisions made in real-time and compare them to alternative policies, and (3) evaluate the benefits of using a realistic model of US influenza surveillance systems which forces exercise participants to make decisions based on typical, imperfect epidemiological data.

Keyword(s): Data/Surveillance, Professional Training

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a PhD Candidate in Integrative Biology and have worked on the application of mathematical and computational methods to public health for five years. I am the first author on a published manuscript describing a method to design surveillance networks and have published 9 additional peer-reviewed papers. I have presented my research on applied public health modeling at eight conferences.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.