Mathematical modeling of COVID-19 containment strategies with considerations for limited medical resources

Brydon Eastman; Cameron Meaney; Michelle Przedborski; Mohammad Kohandel

As powerful as these prediction methods are, all modelling is subject to assumptions. For instance, neither model considers how the burden on the healthcare system directly affects the case fatality rate. In practice, we expect that if the healthcare system were to become overburdened as a result of a large number of simultaneous infections, the case fatality rate would increase. This would happen as the result of health care practitioners being unable to provide care for all serious patients due to the sheer volume of cases. As a result, even with effective triage procedures, we would anticipate more fatalities from COVID-19 in an overburdened healthcare system than in one with extra resources, even when the total case count is constant over a period. Further, in the two models presented we ignore the role of random events, assume that the population is well mixed, and assume that the spread of the virus in each geographical region behaves like a single outbreak. In reality, random events can influence the spread of the virus in profound ways, populations 3 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.