A Predictive Model of the Temperature-Dependent Inactivation of Coronaviruses

21 April 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The COVID-19 pandemic has stressed healthcare systems and supply lines, forcing medical doctors to risk infection by decontaminating and reusing medical personal protective equipment intended only for a single use. The uncertain future of the pandemic is compounded by a lack of data on the ability of the responsible virus, SARS-CoV-2, to survive across various climates, preventing epidemiologists from accurately modeling its spread. However, existing data on the thermal inactivation of related coronaviruses can provide insights enabling progress towards understanding and mitigating COVID-19. This paper describes a thermodynamic model that synthesizes data from the literature to accurately predict the temperature-dependent inactivation of coronaviruses. The model provides much-needed thermal sterilization guidelines for personal protective equipment, including masks, and will also allow epidemiologists to incorporate temperature into models forecasting the spread of coronaviruses across different climates and seasons.

Keywords

Virology
Coronavirus
SARS
COVID-19
Thermodynamics
Physical Chemistry

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