key: cord-0785207-7usv3ljo
authors: Takagi, H.; Kuno, T.; v, Y.; Ueyama, H.; Matsushiro, T.; Hari, Y.; Ando, T.
title: Meteorological Conditions and Covid-19 in Large U.S. Cities
date: 2020-05-22
journal: nan
DOI: 10.1101/2020.05.17.20104547
sha: 280440d45c36d6cc9bafad1dbb0aa198651f756c
doc_id: 785207
cord_uid: 7usv3ljo

To determine whether prevalence of Coronavirus disease 2019 (Covid-19) is modulated by meteorological conditions, we herein conducted meta-regression of data in large U.S. cities. We selected 33 large U.S. cities with a population of >500,000. The integrated numbers of confirmed Covid-19 cases in the country to which the city belongs on 14 May 2020, the estimated population in 2019 in the country, and monthly meteorological conditions at the city for 4 months (from January to April 2020) were obtained. Meteorological conditions consisted of mean temperature (F), total precipitation (inch), mean wind speed (MPH), mean sky cover, and mean relative humidity (%). Monthly data for 4 months were averaged or integrated. The Covid-19 prevalence was defined as the integrated number of Covid-19 cases divided by the population. Random-effects meta-regression was performed by means of OpenMetaAnalyst. In a meta-regression graph, Covid-19 prevalence (plotted as the logarithm transformed prevalence on the y-axis) was depicted as a function of a given factor (plotted as a meteorological datum on the x-axis). A slope of the meta-regression line was significantly negative (coefficient, -0.069; P < 0.001) for the mean temperature and significantly positive for the mean wind speed (coefficient, 0.174; P = 0.027) and the sky cover (coefficient, 2.220; P = 0.023). In conclusion, lower temperature and higher wind speed/sky cover may be associated with higher Covid-19 prevalence, which should be confirmed by further epidemiological researches adjusting for various risk and protective factors (in addition to meteorological conditions) of Covid-19.

To determine whether prevalence of Coronavirus disease 2019 (Covid-19) is modulated by meteorological conditions, we herein conducted meta-regression of data in large U.S. cities. We selected 33 large U.S. cities with a population of >500,000. The integrated numbers of confirmed Covid-19 cases in the country to which the city belongs on 14 May 2020, the estimated population in 2019 in the country, and monthly meteorological conditions at the city for 4 months (from January to April 2020) were obtained.

Meteorological conditions consisted of mean temperature (F), total precipitation (inch), mean wind speed (MPH), mean sky cover, and mean relative humidity (%). Monthly data for 4 months were averaged or integrated. The Covid-19 prevalence was defined as the integrated number of Covid-19 cases divided by the population. Random-effects meta-regression was performed by means of OpenMetaAnalyst. In a meta-regression graph, Covid-19 prevalence (plotted as the logarithm transformed prevalence on the yaxis) was depicted as a function of a given factor (plotted as a meteorological datum on the x-axis). A slope of the meta-regression line was significantly negative (coefficient, -0.069; P < 0.001) for the mean temperature and significantly positive for the mean wind speed (coefficient, 0.174; P = 0.027) and the sky cover (coefficient, 2.220; P = 0.023).

In conclusion, lower temperature and higher wind speed/sky cover may be associated with higher Covid-19 prevalence, which should be confirmed by further epidemiological researches adjusting for various risk and protective factors (in addition to meteorological conditions) of Covid-19.

Higher temperature and ultraviolet (UV) index in Northern Europe have been reported as the most important meteorological protective factors for the transmission of influenza virus. 1 On the other hand, a recent study in China suggests that higher temperature and UV radiation may not be associated with a decrease in the epidemics of Coronavirus disease 2019 (Covid-19). 2 To determine whether prevalence of COVID-19 is modulated by meteorological conditions, we herein conducted meta-regression of data in large U.S. cities.

We selected 33 large U.S. cities with a population of >500,000 in 2010 from the U.S. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 22, 2020. . https://doi.org/10.1101/2020.05.17.20104547 doi: medRxiv preprint (http://www.cebm.brown.edu/openmeta/index.html).

In a meta-regression graph, Covid-19 prevalence (plotted as the logarithm transformed prevalence on the y-axis) was depicted as a function of a given factor (plotted as the meteorological data on the x-axis).

Results of the meta-regression were summarized in Table 2 prevalence increased significantly as the mean wind speed and the sky cover increased).

The present meta-regression suggests that temperature may be negatively and wind speed/sky cover may be positively associated with COVID-19 prevalence. Higher sky cover is probably related to lower UV radiation. Our recent preliminary study of Japanese prefectural data suggests that temperature and UV index may be negatively associated with COVID-19 prevalence, 3 which could strengthen the present findings.

Despite the association of lower temperature and UV index with the influenza transmission, 1 no association of temperature and UV radiation with the COVID-19 epidemics has been reported, 2 however, which may be denied by the present results of the association of lower temperature and higher sky cover with higher COVID-19

prevalence. In conclusion, lower temperature and higher wind speed/sky cover may be All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 22, 2020. All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 22, 2020. . https://doi.org/10.1101/2020.05.17.20104547 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 22, 2020. . (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

Low Temperature and Low UV Indexes Correlated with Peaks of Influenza Virus Activity in Northern Europe during

No association of COVID-19 transmission with temperature or UV radiation in Chinese cities

Higher Air Temperature, Pressure, and Ultraviolet Are Associated with Less Covid-19 Incidence