Mathematical Modeling and Scientific Computing for Infectious Disease Research

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Project Summary/Abstract Emerging and reemerging infectious diseases represent a tremendous health and economic burden throughout the world. The COVID-19 pandemic underscores the gap between the complex mechanisms of disease transmission and spread and our current knowledge and intervention strategies. Several critical issues such as the emergence of new variants, the consequence of vaccine hesitancy, the presence of environmental transmission, the impact of underlying health conditions and behaviors, and the prediction of disease spread, which are related to COVID-19 and applicable to a wide variety of infectious diseases, are only partially and inadequately addressed at present. Mathematical and computational studies can provide key insights into these challenges and improve our understanding of disease transmission, spread, and progression. The overall objective of this proposal is to establish a new mathematical and computational modeling framework for infectious diseases, with a focus on COVID-19, that integrates novel mathematical modeling, extensive numerical simulation, and rigorous data validation. To achieve this objective, we will pursue three Specific Aims: (1) Modeling the transmission dynamics of infectious diseases; (2) Modeling the impact of underlying health conditions; and (3) Modeling the spatial spread of infectious diseases. The proposed research is significant because it is expected to substantially advance our current understanding of the complex dynamics associated with COVID-19 and many other infectious diseases, which will potentially improve our current practice in disease control and outbreak management. The approach is innovative in the development of novel mathematical models and advanced computational techniques to address pressing needs for infectious disease research, in the integration of mathematical, computational, and epidemiological methods, and in the involvement of undergraduate students for authentic research through a progressive learning process. The project represents an interdisciplinary collaboration between an applied and computational mathematician and a public health scientist who have worked with each other for several years. A cohort of 5 undergraduate students per year, for a total of 15 over three years, will be supported by the project. The success of this project will build a solid knowledge base for the complex dynamics of infectious diseases, will provide important guidelines for the public health administrations in disease management and policy development, and will create a novel platform for engaging undergraduate researchers and strengthening the institutional research environment.