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  • Mechanistic theory predicts...
    Morris, Dylan H; Yinda, Kwe Claude; Gamble, Amandine; Rossine, Fernando W; Huang, Qishen; Bushmaker, Trenton; Fischer, Robert J; Matson, M Jeremiah; Van Doremalen, Neeltje; Vikesland, Peter J; Marr, Linsey C; Munster, Vincent J; Lloyd-Smith, James O

    eLife, 07/2021, Letnik: 10
    Journal Article

    Ambient temperature and humidity strongly affect inactivation rates of enveloped viruses, but a mechanistic, quantitative theory of these effects has been elusive. We measure the stability of SARS-CoV-2 on an inert surface at nine temperature and humidity conditions and develop a mechanistic model to explain and predict how temperature and humidity alter virus inactivation. We find SARS-CoV-2 survives longest at low temperatures and extreme relative humidities (RH); median estimated virus half-life is >24 hours at 10C and 40% RH, but ~1.5 hours at 27C and 65% RH. Our mechanistic model uses fundamental chemistry to explain why inactivation rate increases with increased temperature and shows a U-shaped dependence on RH. The model accurately predicts existing measurements of five different human coronaviruses, suggesting that shared mechanisms may affect stability for many viruses. The results indicate scenarios of high transmission risk, point to mitigation strategies, and advance the mechanistic study of virus transmission.