These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
Preprints are manuscripts made publicly available before they have been submitted for formal peer review and publication. They might contain new research findings or data. Preprints can be a draft or final version of an author's research but must not have been accepted for publication at the time of submission.
COVID-19 pandemic has stressed healthcare systems and supply lines, forcing
medical doctors to risk infection by decontaminating and reusing single-use
medical personal protective equipment. The uncertain future of the pandemic is
compounded by limited data on the ability of the responsible virus, SARS-CoV-2,
to survive across various climates, preventing epidemiologists from accurately
modeling its spread. However, a detailed thermodynamic analysis of experimental
data on the inactivation of SARS-CoV-2 and related coronaviruses can enable a
fundamental understanding of their thermal degradation that will help model the
COVID-19 pandemic and mitigate future outbreaks. This paper introduces a
thermodynamic model that synthesizes existing data into an analytical framework
built on first principles, including the rate law and the Arrhenius equation,
to accurately predict the temperature-dependent inactivation of coronaviruses.
The model provides much-needed thermal decontamination guidelines for personal
protective equipment, including masks. For example, at 70 °C, a 3-log (99.9%)
reduction in virus concentration can be achieved in ≈ 3 minutes and can be
performed in most home ovens without reducing the efficacy of typical N95
masks. The model will also allow for epidemiologists to incorporate the
lifetime of SARS-CoV-2 as a continuous function of environmental temperature
into models forecasting the spread of coronaviruses across different climates
The authors declare no competing financial interest.
Under consideration at Applied Physics Letters.
Version 3 submitted 23 June 2020; added uncertainty analysis to predictions of virus lifetime.
Version 2 submitted 1 May 2020; added data for SARS-CoV-2 (Chin 2020, van Doremalen 2020) and SARS-CoV-1 (van Doremalen 2020).
Version 1 submitted 19 April 2020.