Interactive pandemic exercise toolkit
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
Implementation of health education strategies, interventions and programs
Planning of health education strategies, interventions, and programs
Public health or related research
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
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.