Warmer weather unlikely to reduce the COVID-19 transmission: An ecological study in 202 locations in 8 countries

Purpose: To examine the association between meteorological factors (temperature, relative humidity, wind speed, and UV radiation) and transmission capacity of COVID-19. Methods: We collected daily numbers of COVID-19 cases in 202 locations in 8 countries. We matched meteorological data from the NOAA...

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Autores:
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/13678
Acceso en línea:
https://doi.org/10.1016/j.scitotenv.2020.142272
http://hdl.handle.net/20.500.12010/13678
Palabra clave:
SARS-CoV-2
Meteorological factors
Temperature
Ultraviolet radiation
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
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License
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Description
Summary:Purpose: To examine the association between meteorological factors (temperature, relative humidity, wind speed, and UV radiation) and transmission capacity of COVID-19. Methods: We collected daily numbers of COVID-19 cases in 202 locations in 8 countries. We matched meteorological data from the NOAA National Centers for Environmental Information.We used a time-frequency approach to examine the possible association between meteorological conditions and basic reproductive number (R0) of COVID-19. We determined the correlations between meteorological factors and R0 of COVID-19 using multiple linear regression models and meta-analysis. We further validated our results using a susceptible-exposedinfectious-recovered (SEIR) metapopulation model to simulate the changes of daily cases of COVID-19 in China under different temperatures and relative humidity conditions. Principal results: Temperature did not exhibit significant association with R0 of COVID-19 (meta p = 0.446). Also, relative humidity (meta p = 0.215), wind speed (meta p = 0.986), and ultraviolet (UV) radiation (meta p = 0.491) were not significantly associated with R0 either. The SEIR model in China showed that with a wide range of meteorological conditions, the number of COVID-19 confirmed cases would not change substantially.