A global dataset of pandemic- and epidemic-prone disease outbreaks
| dc.rights.license | open | en_US |
| dc.contributor.author | TORRES MUNGUÍA, Juan Armando | |
| hal.structure.identifier | Bordeaux Sciences Economiques [BSE] | |
| dc.contributor.author | BADARAU, Florina Cristina | |
| dc.contributor.author | DÍAZ PAVEZ, Luis Rodrigo | |
| dc.contributor.author | MARTINEZ-ZARZOSO, Inmaculada | |
| dc.contributor.author | WACKER, Konstantin M. | |
| dc.date.accessioned | 2023-03-15T10:45:49Z | |
| dc.date.available | 2023-03-15T10:45:49Z | |
| dc.date.issued | 2022-11-10 | |
| dc.identifier.issn | 2052-4463 | en_US |
| dc.identifier.uri | oai:crossref.org:10.1038/s41597-022-01797-2 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/172318 | |
| dc.description.abstractEn | AbstractThis 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. | |
| dc.language.iso | EN | en_US |
| dc.rights | Attribution 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
| dc.source | crossref | |
| dc.title.en | A global dataset of pandemic- and epidemic-prone disease outbreaks | |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1038/s41597-022-01797-2 | en_US |
| dc.subject.hal | Sciences de l'Homme et Société/Economies et finances | en_US |
| dc.description.sponsorshipEurope | Federal Ministry of Education & Research (BMBF) | en_US |
| dc.description.sponsorshipEurope | Enhanced Lightweight Design | en_US |
| bordeaux.journal | Scientific Data | en_US |
| bordeaux.volume | 9 | en_US |
| bordeaux.hal.laboratories | Bordeaux Sciences Economiques / Bordeaux School of Economics (BSE) - UMR 6060 | en_US |
| bordeaux.issue | 683 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | CNRS | |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| bordeaux.import.source | dissemin | |
| hal.identifier | hal-04029973 | |
| hal.version | 1 | |
| hal.date.transferred | 2023-03-15T10:46:09Z | |
| hal.export | true | |
| workflow.import.source | dissemin | |
| dc.rights.cc | CC BY | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Scientific%20Data&rft.date=2022-11-10&rft.volume=9&rft.issue=683&rft.eissn=2052-4463&rft.issn=2052-4463&rft.au=TORRES%20MUNGU%C3%8DA,%20Juan%20Armando&BADARAU,%20Florina%20Cristina&D%C3%8DAZ%20PAVEZ,%20Luis%20Rodrigo&MARTINEZ-ZARZOSO,%20Inmaculada&WACKER,%20Konstantin&rft.genre=article |
