ArticleMicrobiology spectrum2025
The impact of temperature and relative humidity on SARS-CoV-2 airborne transmission in Syrian hamsters.
Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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2 authors.
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Abstract
Numerous studies have analyzed the effect of temperature and humidity on COVID-19 transmission, but the findings are inconsistent. This was due to differences in research methodologies, study regions and periods, selected variables, and confounding factors. Using Syrian hamsters, we conducted an evaluation of the airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under various temperature and relative humidity combination conditions in a tightly controlled environmental chamber. We found that the airborne transmission of SARS-CoV-2 was moderately slowed in high temperature and high relative humidity conditions. This can be partially attributed to reduced replication in hamsters and the shortened survival time of the virus in the air. In this study, we have demonstrated that the transmission of SARS-CoV-2 among hamsters is co-modulated to some extent by temperature and relative humidity, and the effect is less pronounced than anticipated that high temperatures would block or substantially reduce SARS-CoV-2 airborne transmission.IMPORTANCEIn this study, we found that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) airborne transmission is to some extent co-modulated by temperature and humidity. However, solely relying on seasonal fluctuations in temperature and humidity is insufficient to substantially mitigate COVID-19 transmission, underscoring the critical need for sustained public health measures. Based on our findings in this hamster model, we infer that COVID-19 may have some seasonal patterns, but these patterns would not be as conspicuous as those of influenza. This insight has significant implications for the ongoing efforts in monitoring, preventing, and controlling the spread of COVID-19.
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