Estimating key parameters for infectious disease outbreaks and implications for control
Two epidemiological parameters that are of paramount importance in assessing the epidemic potential of a novel pathogen are the early epidemic growth rate and the reproductive number R0. In this talk, I will present our efforts to estimate these two parameter values during early SARS-CoV-2 outbreaks and how we reached the conclusion in early Feb. 2020 that early, strong social distancing efforts are necessary to stop the spread of the virus. More specifically, we estimated that the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.7 days) and the reproductive numbers are likely between 3.9 and 7.1. This means that a large fraction of the population (between 74% and 86%) needs to be immune to achieve herd immunity. I will discuss lessons learned for understanding and controlling future outbreaks of novel pathogens.
Ruian Ke is currently a staff scientist at Los Alamos National Laboratory (LANL). His research group focuses on developing mathematical/quantitative theories and tools to understand the spread of viruses, viral-immune interactions and viral evolutionary dynamics across multiple scales of biological organization, i.e. at intracellular, cellular and population scales. Since January 2020, he has been working on modeling the transmission dynamics of SARS-CoV-2 across the globe. More recently, his work focused on characterizing within-host dynamics and immune responses to SARS-CoV-2 infection. Before joining LANL, he was a tenure-track assistant professor of mathematics at North Carolina State University between 2015 and 2018. He did his PhD at Imperial College London followed by post-docs at University of California, Los Angeles and LANL.