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Computational and Statistical Methods for Modeling the Spread of Plant and Animal Diseases


The introduction and subsequent spread of foreign animal diseases such as foot and mouth disease (FMD) and high pathogenicity avian influenza (HPAI) present significant threats to national security because of the potential for severe economic disruption. In most likely scenarios, these dislocations would certainly involve extended embargo of agricultural products, restriction of interstate commerce and costs associated managing the outbreak itself (e.g., diagnosis, testing, culling, quarantine and vaccination). In addition, some diseases such as HPAI pose an unpredictable threat to public health. The high socio-economic impact of an outbreak of a foreign animal disease makes it essentially impossible to conduct designed experiments to validate epidemiological models in real-world settings. In the absence of data from controlled experiments to test specific hypotheses and predictions, it is common to rely on endorsements by trusted subject matter experts or by fitting to extant observational data. (In contrast, other infectious diseases, including plant diseases such as late blight of potato and tomato, offer the opportunity to conduct extensive validation of models and thereby to gain better insight into disease processes generally.) <P>

In developing models of foreign animal disease, it is important to address not only specific, low-level questions regarding any particular disease, but also more generic, high-level questions relating to commonalities among diseases and methodologies for constructing quantitative, predictive models. By first addressing some more general, high-level questions in the context of particular well-characterized model systems, we propose to identify and address generic statistical and methodological problems, and then to test solutions to these problems in the context of specific models. <P>This knowledge can then be used to guide the development, implementation and testing of models for specific animal diseases, despite the differences in the details of the models and biology of the organisms involved.

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APPROACH: The initial focus of this work will be on several generic aspects of epidemiological models: (a) identification and examination of existing models and datasets as case studies; (b) analysis of models to examine dynamics of disease spread, parameter estimation, and contact network structure in models of interest; (c) analysis of statistics of extreme events and first passage times in models of interest. Related issues arise in essentially all epidemiological models for epidemics on a national scale.

USDA - Agricultural Research Service
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