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A global dataset of pandemic- and epidemic-prone disease outbreaks
This paper presents a new dataset of infectious disease outbreaks collected from the Disease Outbreak News and the Coronavirus Dashboard produced by the World Health Organization. The dataset contains information on 70 infectious diseases and 2227 public health events that occurred over the period f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648436/ https://www.ncbi.nlm.nih.gov/pubmed/36357405 http://dx.doi.org/10.1038/s41597-022-01797-2 |
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author | Torres Munguía, Juan Armando Badarau, Florina Cristina Díaz Pavez, Luis Rodrigo Martínez-Zarzoso, Inmaculada Wacker, Konstantin M. |
author_facet | Torres Munguía, Juan Armando Badarau, Florina Cristina Díaz Pavez, Luis Rodrigo Martínez-Zarzoso, Inmaculada Wacker, Konstantin M. |
author_sort | Torres Munguía, Juan Armando |
collection | PubMed |
description | This paper presents a new dataset of infectious disease outbreaks collected from the Disease Outbreak News and the Coronavirus Dashboard produced by the World Health Organization. The dataset contains information on 70 infectious diseases and 2227 public health events that occurred over the period from January 1996 to March 2022 in 233 countries and territories around the world. We illustrate the potential use of this dataset to the research community by analysing the spatial distribution of disease outbreaks. We find evidence of spatial clusters of high incidences (“hot spots”) in Africa, America, and Asia. This spatial analysis enables policymakers to identify the regions with the greatest likelihood of suffering from disease outbreaks and, taking into account their degree of preparedness and vulnerability, to develop policies that may help contain the spreading of future outbreaks. Further applications could focus on combining our data with other information sources to study, for instance, the link between environmental, globalization, and/or socioeconomic factors with disease outbreaks. |
format | Online Article Text |
id | pubmed-9648436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96484362022-11-14 A global dataset of pandemic- and epidemic-prone disease outbreaks Torres Munguía, Juan Armando Badarau, Florina Cristina Díaz Pavez, Luis Rodrigo Martínez-Zarzoso, Inmaculada Wacker, Konstantin M. Sci Data Data Descriptor This paper presents a new dataset of infectious disease outbreaks collected from the Disease Outbreak News and the Coronavirus Dashboard produced by the World Health Organization. The dataset contains information on 70 infectious diseases and 2227 public health events that occurred over the period from January 1996 to March 2022 in 233 countries and territories around the world. We illustrate the potential use of this dataset to the research community by analysing the spatial distribution of disease outbreaks. We find evidence of spatial clusters of high incidences (“hot spots”) in Africa, America, and Asia. This spatial analysis enables policymakers to identify the regions with the greatest likelihood of suffering from disease outbreaks and, taking into account their degree of preparedness and vulnerability, to develop policies that may help contain the spreading of future outbreaks. Further applications could focus on combining our data with other information sources to study, for instance, the link between environmental, globalization, and/or socioeconomic factors with disease outbreaks. Nature Publishing Group UK 2022-11-10 /pmc/articles/PMC9648436/ /pubmed/36357405 http://dx.doi.org/10.1038/s41597-022-01797-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Torres Munguía, Juan Armando Badarau, Florina Cristina Díaz Pavez, Luis Rodrigo Martínez-Zarzoso, Inmaculada Wacker, Konstantin M. A global dataset of pandemic- and epidemic-prone disease outbreaks |
title | A global dataset of pandemic- and epidemic-prone disease outbreaks |
title_full | A global dataset of pandemic- and epidemic-prone disease outbreaks |
title_fullStr | A global dataset of pandemic- and epidemic-prone disease outbreaks |
title_full_unstemmed | A global dataset of pandemic- and epidemic-prone disease outbreaks |
title_short | A global dataset of pandemic- and epidemic-prone disease outbreaks |
title_sort | global dataset of pandemic- and epidemic-prone disease outbreaks |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648436/ https://www.ncbi.nlm.nih.gov/pubmed/36357405 http://dx.doi.org/10.1038/s41597-022-01797-2 |
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