The role of transmission network structure in COVID-19 spread and control

Mathematical models are a key tool used in designing effective responses to COVID-19. Models for infectious disease spread must consider not only biological, clinical, and epidemiological characteristics of a particular pathogen, but also the human behavior that drives transmission. One of the most important manifestations of this is the network of human contacts through which infection can spread. The structure of this network can influence the pattern of disease spread, such as the rate of spread, the degree of super-spreading, the probability of extinction, the herd immunity threshold, and the optimal allocation of vaccines. In this talk I will discuss approaches to building models that account for the heterogeneous nature of human contact networks, and about how these factors specifically relate to the COVID-19 pandemic. I will describe our group's work to understand how transmission network structure impacts COVID-19 dynamics, such as the efficacy of social distancing interventions, the impact of changes in household structure, the shape of epidemics in cities, and selection of new variants.