Mathematical models serve as vital computational tools in exploring infectious diseases across various scales, from population dynamics to within-host phenomena.

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At the within-host level, these models meticulously delineate viral replication, clearance, and immune responses within individual hosts. However, they fall short in directly assessing the population-level impact of detailed individual response to infection. On the contrary, between-host models are extensively employed to delineate transmission dynamics between individuals, study disease epidemiology, and evaluate intervention strategies at a broader scale. Nonetheless, between-host models lack the granularity to account for individual-level biological processes.

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In our laboratory, we not only delve into within-host responses for scientific exploration but also bridge the gap between individual and population scales, leveraging cutting-edge biological insights to inform bedside practice and societal strategies through integrative mathematical modeling. This multiscale approach to infectious disease modeling promises a holistic understanding of disease dynamics, offering avenues to simulate the impact of targeted interventions across different population strata.