About: Inverse correlation between average monthly high temperatures and COVID-19-related death rates in different geographical areas

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Inverse correlation between average monthly high temperatures and COVID-19-related death rates in different geographical areas
Creator	Ciccozzi, Massimo Benedetti, Francesca Gallo, Robert Ippodrino, Rudy Marini, Bruna Pachetti, Maria Zella, Davide
Source	Medline; PMC
abstract	BACKGROUND: With the aim of providing a dynamic evaluation of the effects of basic environmental parameters on COVID-19-related death rate, we assessed the correlation between average monthly high temperatures and population density, with death/rate (monthly number of deaths/1 M people) for the months of March (start of the analysis and beginning of local epidemic in most of the Western World, except in Italy where it started in February) and April 2020 (continuation of the epidemic). Different geographical areas of the Northern Hemisphere in the United States and in Europe were selected in order to provide a wide range among the different parameters. The death rates were gathered from an available dataset. As a further control, we also included latitude, as a proxy for temperature. METHODS: Utilizing a publicly available dataset, we retrieved data for the months of March and April 2020 for 25 areas in Europe and in the US. We computed the monthly number of deaths/1 M people of confirmed COVID-19 cases and calculated the average monthly high temperatures and population density for all these areas. We determined the correlation between number of deaths/1 M people and the average monthly high temperatures, the latitude and the population density. RESULTS: We divided our analysis in two parts: analysis of the correlation among the different variables in the month of March and subsequent analysis in the month of April. The differences were then evaluated. In the month of March there was no statistical correlation between average monthly high temperatures of the considered geographical areas and number of deaths/1 M people. However, a statistically significant inverse correlation became significant in the month of April between average monthly high temperatures (p = 0.0043) and latitude (p = 0.0253) with number of deaths/1 M people. We also observed a statistically significant correlation between population density and number of deaths/1 M people both in the month of March (p = 0.0297) and in the month of April (p = 0.0116), when three areas extremely populated (NYC, Los Angeles and Washington DC) were included in the calculation. Once these three areas were removed, the correlation was not statistically significant (p = 0.1695 in the month of March, and p = 0.7076 in the month of April). CONCLUSIONS: The number of COVID-19-related deaths/1 M people was essentially the same during the month of March for all the geographical areas considered, indicating essentially that the infection was circulating quite uniformly except for Lombardy, Italy, where it started earlier. Lockdown measures were implemented between the end of March and beginning of April, except for Italy which started March 9th. We observed a strong, statistically significant inverse correlation between average monthly high temperatures with the number of deaths/1 M people. We confirmed the data by analyzing the correlation with the latitude, which can be considered a proxy for high temperature. Previous studies indicated a negative effect of high climate temperatures on Sars-COV-2 spreading. Our data indicate that social distancing measure are more successful in the presence of higher average monthly temperatures in reducing COVID-19-related death rate, and a high level of population density seems to negatively impact the effect of lockdown measures.
has issue date	2020-06-23(xsd:dateTime)
bibo:doi	10.1186/s12967-020-02418-5
bibo:pmid	32576227
has license	cc-by
sha1sum (hex)	bf1baef49e6d3d23cb018f746cf0c8c9ed78e568
schema:url	https://doi.org/10.1186/s12967-020-02418-5
resource representing a document's title	Inverse correlation between average monthly high temperatures and COVID-19-related death rates in different geographical areas
has PubMed Central identifier	PMC7309213
has PubMed identifier	32576227
schema:publication	J Transl Med
resource representing a document's body	covid:bf1baef49e6d3d23cb018f746cf0c8c9ed78e568#body_text
is schema:about of	named entity 'temperature' named entity 'COVID-19' named entity 'COVID-19' named entity 'Western World' named entity 'dynamic' named entity 'epidemic' named entity 'number' named entity 'effects' named entity 'Inverse' named entity 'death rates' named entity 'death rates' named entity 'April 2020' named entity 'correlation' named entity 'Italy' named entity 'Northern hemisphere' named entity 'COVID' named entity 'Europe' named entity 'United States' named entity 'COVID' named entity 'Lombardy' named entity 'Italy' named entity 'geographical distribution' named entity 'Death rate' named entity 'high temperatures' named entity 'population density' named entity 'World Health Organization' named entity 'population density' named entity 'Los Angeles' named entity 'Washington DC' named entity 'WHO' named entity 'infection' named entity 'population density' named entity 'social distancing' named entity 'COVID' named entity 'increase in number' named entity 'COVID' named entity 'death rate' named entity 'SARS-CoV-2' named entity 'COVID' named entity 'European Centre for Disease Prevention and Control' named entity 'New York City' named entity 'Latitude' named entity 'COVID' named entity 'environmental conditions' named entity 'SARS-CoV-2' named entity 'high latitude' named entity 'virus' named entity 'viral transmission' named entity 'Lombardy' named entity 'statistical significance' named entity 'Italy' named entity 'New York City' named entity 'Lombardy' named entity 'March 2020' named entity 'SARS-CoV-2' named entity 'statistically significant' named entity 'Sars-COV-2' named entity 'Italy' named entity 'population density' named entity 'death rate' named entity 'population density' named entity 'Sicily' named entity 'death rate' named entity 'population density' named entity 'early start' named entity 'population density' named entity 'health systems' named entity 'United States' named entity 'Lombardy' named entity 'COVID' named entity 'Europe' named entity 'latitude' named entity 'death rate' named entity 'COVID' named entity 'SARS-CoV-2'

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