Effect of temperature on the infectivity of COVID-19

•The relationship between infectivity of COVID-19 and temperature is not clear.•Mean temperature in February 2020 were associated with the cumulative number of COVID-19 case in Japan on March 16, 2020.•Number of inbound visitors from China and old-age dependency rate were also associated with the cu...

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Published inInternational journal of infectious diseases Vol. 95; pp. 301 - 303
Main Authors Ujiie, Mugen, Tsuzuki, Shinya, Ohmagari, Norio
Format Journal Article
LanguageEnglish
Published Canada Elsevier Ltd 01.06.2020
The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases
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Abstract •The relationship between infectivity of COVID-19 and temperature is not clear.•Mean temperature in February 2020 were associated with the cumulative number of COVID-19 case in Japan on March 16, 2020.•Number of inbound visitors from China and old-age dependency rate were also associated with the cumulative number of cases. To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model. Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020. Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.
AbstractList To evaluate the influence of temperature on the infectivity of COVID-19 in Japan.OBJECTIVESTo evaluate the influence of temperature on the infectivity of COVID-19 in Japan.We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model.METHODSWe evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model.Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020.RESULTSMonthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020.Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.CONCLUSIONSOur analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.
•The relationship between infectivity of COVID-19 and temperature is not clear.•Mean temperature in February 2020 were associated with the cumulative number of COVID-19 case in Japan on March 16, 2020.•Number of inbound visitors from China and old-age dependency rate were also associated with the cumulative number of cases. To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model. Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020. Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.
To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model. Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020. Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.
Objectives: To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. Methods: We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model. Results: Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020. Conclusions: Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.
• The relationship between infectivity of COVID-19 and temperature is not clear. • Mean temperature in February 2020 were associated with the cumulative number of COVID-19 case in Japan on March 16, 2020. • Number of inbound visitors from China and old-age dependency rate were also associated with the cumulative number of cases.
Author Tsuzuki, Shinya
Ujiie, Mugen
Ohmagari, Norio
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  surname: Ohmagari
  fullname: Ohmagari, Norio
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Cites_doi 10.1101/2020.03.04.20031112
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Snippet •The relationship between infectivity of COVID-19 and temperature is not clear.•Mean temperature in February 2020 were associated with the cumulative number of...
To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. We evaluated the relationship between the accumulated number of patients per...
To evaluate the influence of temperature on the infectivity of COVID-19 in Japan.OBJECTIVESTo evaluate the influence of temperature on the infectivity of...
• The relationship between infectivity of COVID-19 and temperature is not clear. • Mean temperature in February 2020 were associated with the cumulative number...
Objectives: To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. Methods: We evaluated the relationship between the accumulated...
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StartPage 301
SubjectTerms Betacoronavirus
China - epidemiology
Coronavirus Infections - epidemiology
COVID-19
Female
Humans
Japan - epidemiology
Male
Pandemics
Pneumonia, Viral - epidemiology
Poisson Distribution
SARS-CoV-2
Temperature
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Title Effect of temperature on the infectivity of COVID-19
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