I will present a deterministic compartmental model for COVID-19 with 2 main subgroups: one group that does social distancing and one that doesn't. We vary the number of contacts for the social distancing group, while keeping the basic reproduction number R0 fixed (by changing the relative sizes of the two groups). We see that the peak number of infections changes dramatically, dropping by as much as 70%, while the initial growth rate and timing of the peak remain constant. This suggests that heterogeneity in social distancing is fundamentally important.

As economies open up, heterogeneity will continue to be important.

Bio:

Connell McCluskey received his PhD in 2002 from the University of Alberta, receiving the CAIMS Doctoral Dissertation Award. After postdoctoral research at the University of Victoria and McMaster University, he moved to Wilfrid Laurier University in Waterloo, Ontario. He spent 2011 as a visiting professor at the Université Victor Segalen Bordeaux 2 in France.