Fighting COVID with math
Professors Caroline Colijn and Paul Tupper from Simon Fraser University published a paper that outlines a quantitative framework for determining which COVID interventions - such as handwashing, masks, physical distancing and social bubbles - are likely to have the most impact in a given setting.
Using data collected from outbreak reports around the world, the paper introduces the concept of “event R”, which is the expected number of people who will contract COVID-19 from a single event. Four parameters are then factored in: transmission intensity, duration of exposure, proximity, and the degree of mixing.
The model shows that physical distancing is effective in all settings, but the effectiveness of social bubbles and masks depends on the parameters. For example, a mask may be effective for a short event such as a bus ride, but less effective for something like sitting in an office all day.
Intended as a decision-making tool, Colijn and Tupper hope the model will help disentangle which interventions work best in any given situation.