Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities

Brazil has one of the fastest-growing COVID-19 epidemics worldwide. Non-pharmaceutical interventions (NPIs) have been adopted at the municipal level with asynchronous actions taken across 5,568 municipalities and the Federal District. This paper systematises the fragmented information on NPIs report...

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Autores principales: de Souza Santos, Andreza Aruska, Candido, Darlan da Silva, de Souza, William Marciel, Buss, Lewis, Li, Sabrina L., Pereira, Rafael H. M., Wu, Chieh-Hsi, Sabino, Ester C., Faria, Nuno R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933188/
https://www.ncbi.nlm.nih.gov/pubmed/33664243
http://dx.doi.org/10.1038/s41597-021-00859-1
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author de Souza Santos, Andreza Aruska
Candido, Darlan da Silva
de Souza, William Marciel
Buss, Lewis
Li, Sabrina L.
Pereira, Rafael H. M.
Wu, Chieh-Hsi
Sabino, Ester C.
Faria, Nuno R.
author_facet de Souza Santos, Andreza Aruska
Candido, Darlan da Silva
de Souza, William Marciel
Buss, Lewis
Li, Sabrina L.
Pereira, Rafael H. M.
Wu, Chieh-Hsi
Sabino, Ester C.
Faria, Nuno R.
author_sort de Souza Santos, Andreza Aruska
collection PubMed
description Brazil has one of the fastest-growing COVID-19 epidemics worldwide. Non-pharmaceutical interventions (NPIs) have been adopted at the municipal level with asynchronous actions taken across 5,568 municipalities and the Federal District. This paper systematises the fragmented information on NPIs reporting on a novel dataset with survey responses from 4,027 mayors, covering 72.3% of all municipalities in the country. This dataset responds to the urgency to track and share findings on fragmented policies during the COVID-19 pandemic. Quantifying NPIs can help to assess the role of interventions in reducing transmission. We offer spatial and temporal details for a range of measures aimed at implementing social distancing and the dates when these measures were relaxed by local governments.
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spelling pubmed-79331882021-03-19 Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities de Souza Santos, Andreza Aruska Candido, Darlan da Silva de Souza, William Marciel Buss, Lewis Li, Sabrina L. Pereira, Rafael H. M. Wu, Chieh-Hsi Sabino, Ester C. Faria, Nuno R. Sci Data Data Descriptor Brazil has one of the fastest-growing COVID-19 epidemics worldwide. Non-pharmaceutical interventions (NPIs) have been adopted at the municipal level with asynchronous actions taken across 5,568 municipalities and the Federal District. This paper systematises the fragmented information on NPIs reporting on a novel dataset with survey responses from 4,027 mayors, covering 72.3% of all municipalities in the country. This dataset responds to the urgency to track and share findings on fragmented policies during the COVID-19 pandemic. Quantifying NPIs can help to assess the role of interventions in reducing transmission. We offer spatial and temporal details for a range of measures aimed at implementing social distancing and the dates when these measures were relaxed by local governments. Nature Publishing Group UK 2021-03-04 /pmc/articles/PMC7933188/ /pubmed/33664243 http://dx.doi.org/10.1038/s41597-021-00859-1 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
de Souza Santos, Andreza Aruska
Candido, Darlan da Silva
de Souza, William Marciel
Buss, Lewis
Li, Sabrina L.
Pereira, Rafael H. M.
Wu, Chieh-Hsi
Sabino, Ester C.
Faria, Nuno R.
Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title_full Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title_fullStr Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title_full_unstemmed Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title_short Dataset on SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities
title_sort dataset on sars-cov-2 non-pharmaceutical interventions in brazilian municipalities
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933188/
https://www.ncbi.nlm.nih.gov/pubmed/33664243
http://dx.doi.org/10.1038/s41597-021-00859-1
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