Author: Ashleigh Tuite; David N Fisman; Amy L Greer
Title: Mathematical modeling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada Document date: 2020_3_26
ID: e4pr78n0_4
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint .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 Epidemiological models can contribute important insight for public health decision-makers by allowing for the examination of a variety of "what-if" scenarios. The Canadian Pandemic Influenza Plan (CPIP) for the Health Sector (the backbone of which informs COVID-19 pandemic preparedness and response) ident.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint .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 Epidemiological models can contribute important insight for public health decision-makers by allowing for the examination of a variety of "what-if" scenarios. The Canadian Pandemic Influenza Plan (CPIP) for the Health Sector (the backbone of which informs COVID-19 pandemic preparedness and response) identifies two main objectives for responding to a pandemic: (1) to minimize serious morbidity and mortality, and (2) to minimize societal disruption (11) . The overarching goal of pandemic response is to find a combination of NPIs that would minimize the number of cases requiring in-patient medical care (e.g. hospitalization and/or ICU admission), and deaths, while also minimizing the level of societal disruption.
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