The National Science Foundation (NSF) awarded a $200,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Virginia to develop data-driven, multimodal methods for behavior-based epidemiological modeling. The key objectives are to:
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Improve techniques for deriving meaningful insights from imperfect, real-world sensor data like mobile phones and search engine logs to capture complex human behaviors in real-time.
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Couple agent-based disease models with behavioral models to better integrate real-world behaviors and enable more realistic forecasting of epidemics.
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Develop new scenario modeling tools and causal inference methods to evaluate the effects of public health decisions on behaviors and epidemic outcomes.
This 3-year project aims to enhance epidemiological modeling and public health decision-making by providing a unified framework to incorporate novel data sources, extended disease models, and rigorous evaluations of policy interventions, with a focus on the COVID-19 pandemic.
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