Mathematical and Computational Predictive Modeling Core

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PROJECT SUMMARY – Mathematical and Computational Predictive (MCP) Modeling Core Reducing the burden of global infectious disease presents a number of stubborn key challenges. Principle among these are 1) to understand the dynamic interface (immunologic, inflammatory, microbiome-related, pathophysiologic) between an infectious pathogen and its human host, particularly in terms of the complex factors that determine host susceptibility to or protection from clinical disease, 2) to understand the dynamics of disease transmission and how they are affected by environmental and behavioral pressures, and 3) to predict and measure the impact of interventions (vaccine, therapeutic, public health) with the goal of working toward global improvements in public health. Meeting these challenges requires not only a broad knowledge base that includes the natural history of the disease, its intra-host mechanism of action, its inter-host mode of transmission, and large sets of complex -omic and demographic data, but also the ability to integrate this knowledge into quantitative predictions of outcomes. This can only be done effectively when the relevant processes are translated into mathematical expressions or algorithms that are implemented computationally so that their predictions can be exhaustively examined. The goal of the Mathematical and Computational Predictive (MCP) Modeling Core is to provide the expertise and resources necessary to bring MCP modeling to the COBRE, with special focus on the junior faculty projects. MCP services include: 1) design, innovation and planning, in consultation with the “Brains Trust,” 2) curation and preparation of final analytic datasets, and 3) predictive model building and testing. By direct interaction with the COBRE faculty, its educational components, and use of the “Innovation and Collaboration” laboratory, the MCP Modeling core will bridge the scientific “culture gap” between the scientists with biomedical backgrounds and those with computational modeling expertise. This will greatly enhance the ability of the TGIR Center to advance the understanding and management of global infectious diseases.