randomxsk8 / covid19_regional

Dailycases of COVID-19 pandemic at regional level

A global association between Covid-19 cases and airborne particulate matter at regional level

Solimini A.^, Filipponi F. §, Alunni Fegatelli D. ^, Caputo B. ^, De Marco C.M. ^, Spagnoli A. ^, Vestri A.R. ^.

^ Department of Public Health and Infectious Diseases, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy

§ Institute for Environmental Protection and Research (ISPRA), Via Vitaliano Brancati 48, 00144 Rome, Italy

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This is the data repository for the paper published in Scientific Reports http://www.nature.com/articles/s41598-021-85751-z. The analysis is based on a large global dataset built by collecting information from various freely available sources. We provide here a static dataset with the file used in the analysis (https://tinyurl.com/ujdcfruz) and a linux bash script for downloading updated Covid-19 data (https://tinyurl.com/adyzjs8c). Explanatory Readme files are also provided.

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Data sources: This list includes a complete list of all sources ever used in the data set, up to June 1st, 2020. Please refer to the published paper for full method description LINK.

Region-equivalent administrative units were collected from GADM version 3.6 (https://gadm.org);

Region spatial polygons of the European countries, were downloaded from Eurostat (https://ec.europa.eu/eurostat/web/nuts/nuts-maps);

Population counts and densities were derived from the Gridded Population of the World (version 4.11, distributed by Socioeconomic Data and Applications Center, https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density-rev11/data-download);

Climate and air quality datasets were collected from the Copernicus Climate Change Service (C3S) (https://climate.copernicus.eu);

Air quality datasets were collected from the Copernicus Atmosphere Monitoring Service (CAMS) (https://atmosphere.copernicus.eu);

The Covid-19 dataset was built by integrating several repositories on GithubGitHub, that collected regional daily cases by country up to the 1st of June,June 2020. The sources of data for other world regions are listed in at this link (https://tinyurl.com/yxmh6blb ).

Information on the Covid-19 cumulative tests performed at the date of outcome were extracted from our world data (https://ourworldindata.org/);

Data on several country level covariates (prevalence of diabetes, GDP etc.) were extracted from the world bank (https://data.worldbank.org/);

Government Response Stringency Index was downloaded from https://www.bsg.ox.ac.uk/research/research-projects/covid-19-government-response-tracker

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Authors

Angelo Solimini, University of Rome La Sapienza, epidemiologist and project coordinator;

Federico Filipponi, Institute for Environmental Protection and Research, geographer and geospatial analyst;

Danilo Alunni Fegatelli, University of Rome La Sapienza, biostatistician;

Beniamino Caputo, University of Rome La Sapienza, medical entomologist;

Carlo Maria De Marco, University of Rome La Sapienza, bioinformatician;

Alessandra Spagnoli, University of Rome La Sapienza, biostatistician;

Anna Rita Vestri, University of Rome La Sapienza, biostatistician

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Contacts

Dr. Angelo Solimini, University of Rome La Sapienza, project coordinator ([email protected])