Speaker: Jeremy D Harris (Georgia Tech)
Time: February 1st at 4 pm (EST)
Title: Individual-level differences in asymptomatic and symptomatic transmission shape population-level dynamics of SARS-CoV-2 outbreaks
Abstract: The transmission of SARS-CoV-2 may vary based on individual disease status, potentially biasing population-level estimates of epidemic strength, speed, and controllability. Here, we use a series of nonlinear epidemic models to study the impact of differences in time scales between asymptomatic and symptomatic transmission of SARS-CoV-2 on the relative contribution of asymptomatic infections to epidemic dynamics. We build on prior work  and show that differences in time scales of transmission may impact estimates of disease severity throughout the course of the epidemic due to changes in the effective proportion of asymptomatic transmission over time. We do so in two parts. First, we examine dynamics when transmission outcomes and disease statuses are correlated: that is, transmission from asymptomatic (symptomatic) individuals is more likely to lead to new, asymptomatic (symptomatic) infections. Second, we examine dynamics given age-dependent assortative mixing coupled with intrinsic differences in symptomaticity with age. In both cases we find that the effective proportion of asymptomatic transmission and realized proportion of asymptomatic incidence increase over time as total incidence decreases. Moreover, when coupling differences in time scales with age-dependent assortative mixing, we find that the age distribution of infections shifts to younger ages as incidence decreases. These results show the importance of considering differences in time scales of transmission when interpreting mechanisms underlying shifts in the effective proportion of asymptomatic transmission during COVID outbreaks.
(1) Park, S. W., Cornforth, D. M., Dushoff, J., & Weitz, J. S. (2020). The time scale of asymptomatic transmission affects estimates of epidemic potential in the COVID-19 outbreak. Epidemics, 100392.