Mathematical modeling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada

Ashleigh Tuite; David N Fisman; Amy L Greer

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.24.20042705 doi: medRxiv preprint to know where exactly on the epidemic curve we currently find ourselves. Any model involves trade-offs between simplicity and realism, and in the current work we have not attempted to model social distancing measures in a highly realistic way, but rather generically as reductions in contact frequency. Our understanding of the natural history of SARS-CoV-2 infection continues to evolve and the precise role of pre-symptomatic and subclinical transmission is uncertain. Social distancing becomes a more important control measure in the face of incomplete case ascertainment due to asymptomatic or mildly symptomatic cases. The model does not include seasonality; it is possible that transmission will attenuate in the summer (31), resulting in a decline in cases that would be expected to resurge with the return of colder weather. All of these factors mean that the quantitative findings are subject to uncertainty.