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Seasonality and uncertainty in global COVID-19 growth rates.
Merow, Cory; Urban, Mark C.
  • Merow C; Eversource Energy Center, University of Connecticut, Storrs, CT 06268; cory.merow@gmail.com.
  • Urban MC; Center of Biological Risk, University of Connecticut, Storrs, CT 06268.
Proc Natl Acad Sci U S A ; 117(44): 27456-27464, 2020 11 03.
Article in English | MEDLINE | ID: covidwho-867657
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ABSTRACT
The virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown, as of April 2020, whether summer weather will reduce its spread, thereby alleviating strains on hospitals and providing time for vaccine development. Early insights from laboratory studies and research on related viruses predicted that COVID-19 would decline with higher temperatures, humidity, and ultraviolet (UV) light. Using current, fine-scaled weather data and global reports of infections, we develop a model that explains 36% of the variation in maximum COVID-19 growth rates based on weather and demography (17%) and country-specific effects (19%). UV light is most strongly associated with lower COVID-19 growth. Projections suggest that, without intervention, COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. Validation based on data from May and June 2020 confirms the generality of the climate signal detected. However, uncertainty remains high, and the probability of weekly doubling rates remains >20% throughout summer in the absence of social interventions. Consequently, aggressive interventions will likely be needed despite seasonal trends.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Seasons / Coronavirus Infections / Uncertainty Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Proc Natl Acad Sci U S A Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Seasons / Coronavirus Infections / Uncertainty Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Proc Natl Acad Sci U S A Year: 2020 Document Type: Article