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Human and economic impacts of natural disasters: can we trust the global data?
Reliable and complete data held in disaster databases are imperative to inform effective disaster preparedness and mitigation policies. Nonetheless, disaster databases are highly prone to missingness. In this article, we conduct a missing data diagnosis of the widely-cited, global disaster database,...
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/PMC9481555/ https://www.ncbi.nlm.nih.gov/pubmed/36114183 http://dx.doi.org/10.1038/s41597-022-01667-x |
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author | Jones, Rebecca Louise Guha-Sapir, Debarati Tubeuf, Sandy |
author_facet | Jones, Rebecca Louise Guha-Sapir, Debarati Tubeuf, Sandy |
author_sort | Jones, Rebecca Louise |
collection | PubMed |
description | Reliable and complete data held in disaster databases are imperative to inform effective disaster preparedness and mitigation policies. Nonetheless, disaster databases are highly prone to missingness. In this article, we conduct a missing data diagnosis of the widely-cited, global disaster database, the Emergency Events Database (EM-DAT) to identify the extent and potential determinants of missing data within EM-DAT. In addition, through a review of prominent empirical literature, we contextualise how missing data within EM-DAT has been handled previously. A large proportion of missing data was identified for disasters attributed to natural hazards occurring between 1990 and 2020, particularly on the economic losses. The year the disaster occurred, income-classification of the affected country and disaster type were all significant predictors of missingness for key human and economic loss variables. Accordingly, data are unlikely to be missing completely at random. Advanced statistical methods to handle missing data are thus warranted when analysing disaster data to minimise the risk of biasing statistical inferences and to ensure global disaster data can be trusted. |
format | Online Article Text |
id | pubmed-9481555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94815552022-09-18 Human and economic impacts of natural disasters: can we trust the global data? Jones, Rebecca Louise Guha-Sapir, Debarati Tubeuf, Sandy Sci Data Analysis Reliable and complete data held in disaster databases are imperative to inform effective disaster preparedness and mitigation policies. Nonetheless, disaster databases are highly prone to missingness. In this article, we conduct a missing data diagnosis of the widely-cited, global disaster database, the Emergency Events Database (EM-DAT) to identify the extent and potential determinants of missing data within EM-DAT. In addition, through a review of prominent empirical literature, we contextualise how missing data within EM-DAT has been handled previously. A large proportion of missing data was identified for disasters attributed to natural hazards occurring between 1990 and 2020, particularly on the economic losses. The year the disaster occurred, income-classification of the affected country and disaster type were all significant predictors of missingness for key human and economic loss variables. Accordingly, data are unlikely to be missing completely at random. Advanced statistical methods to handle missing data are thus warranted when analysing disaster data to minimise the risk of biasing statistical inferences and to ensure global disaster data can be trusted. Nature Publishing Group UK 2022-09-16 /pmc/articles/PMC9481555/ /pubmed/36114183 http://dx.doi.org/10.1038/s41597-022-01667-x 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 | Analysis Jones, Rebecca Louise Guha-Sapir, Debarati Tubeuf, Sandy Human and economic impacts of natural disasters: can we trust the global data? |
title | Human and economic impacts of natural disasters: can we trust the global data? |
title_full | Human and economic impacts of natural disasters: can we trust the global data? |
title_fullStr | Human and economic impacts of natural disasters: can we trust the global data? |
title_full_unstemmed | Human and economic impacts of natural disasters: can we trust the global data? |
title_short | Human and economic impacts of natural disasters: can we trust the global data? |
title_sort | human and economic impacts of natural disasters: can we trust the global data? |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481555/ https://www.ncbi.nlm.nih.gov/pubmed/36114183 http://dx.doi.org/10.1038/s41597-022-01667-x |
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