Speaker
Description
SARS-CoV-2 infection is a leading cause of death by infectious disease and continues to be a pressing public health issue due to ongoing emergence of novel variants. One factor that affects variant emergence is the transmission bottleneck size, which refers to the number of unique genetic variants from a donor host that transmit and establish the population in a recipient (defined as a pair). Because a transmission event is not observed and sampled, the size of the bottleneck is inferred using sequence data collected from both members of a pair. For SARS-CoV-2, influenza, and other viral infections, the bottleneck is estimated to be 1-3 virions. Mechanisms underlying the observed tight bottleneck are unclear, but it is hypothesized that intrinsic receptor availability, stochastic loss during viral transit across distinct regions of the respiratory tract, and/or viral clearance by innate immune cells may be strong drivers. In this study, we construct a multi-scale agent-based model of mechanisms pertinent for representing person-to-person transmission of SARS-CoV-2. Our model details processes at four distinct scales: viral-scale evolution, tissue-scale target cell availability and immunity, within-host-scale bottlenecks, and between-host-scale bottlenecks. We link each scale by using summary outcomes from one scale to inform processes in higher scales. Using this multi-scale approach, we assess how mechanisms at lower scales impact the between-host bottleneck size. We will calibrate our model to both viral and host datasets from animal models and human observational cohorts. We expect our model sufficiently captures key dynamics of viral and within-host cellular populations and expect to have preliminary data at time of presentation. Once validated, this model will allow us to determine major mechanistic contributors to transmission bottleneck size and inform targets for future transmission-modulating therapeutics.
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