Computational Models of Infectious Disease Threats

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DESCRIPTION (provided by applicant): Microbial threats, including bioterrorism and naturally emerging infectious diseases, pose a serious challenge to national security in the United States and to health worldwide. This proposal describes the creation of a center for computational modeling of infectious diseases at the Johns Hopkins Bloomberg School of Public Health, with the collaboration of key experts at the Brookings Institution, the National Aeronautic and Space Administration, the University of Maryland, and Imperial College (London). The overarching aim of this project is to integrate the most advanced and powerful techniques of epidemiological data analysis with those of computer simulation (agent-based modeling) to produce a unified computational epidemiology that is scientifically sound, highly visual and user-friendly, and responsive to biosecurity and public health policy requirements. Data analysis will be guided by the insight that epidemic patterns over space and time can be approached as nearly decomposable systems, in which frequency components of the incidence signal can be isolated and studied. Wavelet transforms, and empiric mode decomposition using Hilbert-Huang Transforms, will be used to sift nonlinear, nonstationary epidemiological data, allowing frequency band patterns to be defined. Isolated frequency modes will then be associated with external forcing (weather, social contact patterns) and internal dynamics (Kermack-McKendrick predator-prey models). Results of the epidemiological data decomposition analysis, along with the knowledge of infectious disease experts, will instruct the creation and development of agent-based models. Such models feature populations of mobile individuals in artificial societies that interact locally with other individuals. Features of the basic model include variable social network structures, individual susceptibility and immunity, incubation periods, transmission rates, contact rates, and other selectable parameters. After the agent-based model is calibrated to generate epidemic patterns consistent with real world epidemiology, preventive strategies including vaccination, contact tracing, isolation, quarantine, and other public health measures will be systematically introduced and their impact evaluated. Methods will be developed for assessing the utility of individual models, and for making decisions based on combined results from more than one model. Infectious diseases to be studied initially include smallpox, SARS, dengue, West Nile, and unknown but hypothetically plausible agents. As part of a Cooperative Agreement, the Center will work with other research groups, a bioinformatics core group, and the NIGMS to develop data sets, software and methods, agent-based models, and visualization tools. In an infectious disease epidemic emergency the Center will redirect its activities to serve the nation's security, as guided by the NIGMS.