Over the last two years (and counting) we have all grown accustomed to mathematical modelling as a tool for projecting and predicting the development of the covid-19 pandemic. Besides working on different kinds of modelling for the pandemic, I have had many conversations with mathematicians, other scientists, public health officials and journalists about “the numbers” and “the models”. Along the way I learned some facts and developed a number of opinions. In this talk I will share a selection of my opinions (and maybe even a few facts) related to those crucial whats, whys and hows related to epidemic modelling, communicating our findings, working with others, and the future of this area of science.

Bio: Professor Daniel Coombs is an expert in mathematical modelling applied to human health, immunity, and disease. Dr. Coombs obtained his MSc and PhD in applied mathematics from the University of Arizona and did postdoctoral work at Los Alamos National Lab, before joining the Department of Mathematics at the University of British Columbia (UBC) as a faculty member in 2003. Dr. Coombs contributes to our understanding of infection and immunity across scales from subcellular processes of immunological recognition to virus dynamics at the single-patient level, to epidemiological modelling across human communities. He works closely with experimental scientists at UBC and BC Children’s Hospital Research Centre and public health experts at the BC Centre for Disease Control.

Prof. Coombs' website: https://personal.math.ubc.ca/~coombs/