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首页> 外文期刊>Aerosol Science and Technology: The Journal of the American Association for Aerosol Research >The influence of temperature, humidity, and simulated sunlight on the inactivity of SARS-CoV-2 in aerosols
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The influence of temperature, humidity, and simulated sunlight on the inactivity of SARS-CoV-2 in aerosols

机译:The influence of temperature, humidity, and simulated sunlight on the inactivity of SARS-CoV-2 in aerosols

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摘要

Recent evidence suggests that respiratory aerosols may play a role in the spread of SARS-CoV-2 during the ongoing COVID-19 pandemic.Our laboratory has previously demonstrated that simulated sunlight inactivated SARS-CoV-2 in aerosols and on surfaces.In the present study, we extend these findings to include the persistence of SARS-CoV-2 in aerosols across a range of temperature, humidity, and simulated sunlight levels using an environmentally controlled rotating drum aerosol chamber.The results demonstrate that temperature, simulated sunlight, and humidity are all significant factors influencing the persistence of infectious SARS-CoV-2 in aerosols, but that simulated sunlight and temperature have a greater influence on decay than humidity across the range of conditions tested.The time needed for a 90% decrease in infectious virus ranged from 4.8 min at 40 °C, 20% relative humidity, and high intensity simulated sunlight representative of noon on a clear day on the summer solstice at 40°N latitude, to greater than two hours under conditions representative of those expected indoors or at night.These results suggest that the persistence of infectious SARS-CoV-2 in naturally occurring aerosols may be affected by environmental conditions, and that aerosolized virus could remain infectious for extended periods of time under some environmental conditions.The present study provides a comprehensive dataset on the influence of environmental parameters on the survival of SARS-CoV-2 in aerosols that can be utilized, along with data on viral shedding from infected individuals and the inhalational infectious dose, to inform future modeling and risk assessment efforts.

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