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• W3092136142 abstract "Significance The virus causing COVID-19 has spread rapidly worldwide. It remains unknown whether summer weather will reduce its spread and justify relaxing political interventions and restarting economic activities. We develop statistical models that predict the maximum potential of COVID-19 worldwide and throughout the year. We find that UV light, in particular, is associated with decreased disease growth rate relative to other analyzed factors. Based on these associations with weather, we predict that COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. However, uncertainty remains high, and many factors besides climate, such as social interventions, will influence transmission. Thus, the world must remain vigilant, and continued interventions will likely be needed until a vaccine becomes available." @default.
• W3092136142 created "2020-10-15" @default.
• W3092136142 creator A5006070240 @default.
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• W3092136142 date "2020-10-13" @default.
• W3092136142 modified "2023-10-17" @default.
• W3092136142 title "Seasonality and uncertainty in global COVID-19 growth rates" @default.
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• W3092136142 doi "https://doi.org/10.1073/pnas.2008590117" @default.
• W3092136142 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33051302" @default.
• W3092136142 hasPublicationYear "2020" @default.
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