Michael Li, PhD

Wednesday 7 July, Interactive Session 8b

Abstract: The generation interval is the time between the moment a focal individual is infected and the moment that they infect another. Its distribution provides insight into understanding the relationship between the reproduction number and the exponential rate of growth, which often characterizes infectious disease dynamics. Since infection events are difficult to observe for many infectious diseases, many researchers often use the serial interval (the time between symptom onset in primary and secondary cases, or observation of clinical signs for wildlife diseases) as a proxy for the generation interval; there are theoretical and intuitive arguments why these should be approximately the same. However, our work with data from heterogeneous populations shows that there can be important differences between generation intervals and serial intervals, particularly when the incubation period, infectious period, and infectiousness can be correlated. We explore these differences through simulations and by using data from rabies contact tracing.

About: Michael is a scientist in the Public Health Risk Science division at the Public Health Agency of Canada (PHAC). He is a theoretical/computational infectious disease modeler. He focuses on human-related diseases (COVID-19, influenza, and HIV) and some wildlife diseases (canine rabies), especially in forecasting epidemic outbreaks, retrospective analysis of the evolution of infectious diseases, and intervention strategies/policies for disease control. In addition, Michael has a broad research interest in theoretical and applied statistics, mathematical biology, ecology & evolution, public health, and computations.