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A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences
As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV g...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6911100/ https://www.ncbi.nlm.nih.gov/pubmed/31836720 http://dx.doi.org/10.1038/s41597-019-0330-0 |
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author | Ramshaw, Rebecca E. Letourneau, Ian D. Hong, Amy Y. Hon, Julia Morgan, Julia D. Osborne, Joshua C. P. Shirude, Shreya Van Kerkhove, Maria D. Hay, Simon I. Pigott, David M. |
author_facet | Ramshaw, Rebecca E. Letourneau, Ian D. Hong, Amy Y. Hon, Julia Morgan, Julia D. Osborne, Joshua C. P. Shirude, Shreya Van Kerkhove, Maria D. Hay, Simon I. Pigott, David M. |
author_sort | Ramshaw, Rebecca E. |
collection | PubMed |
description | As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover. |
format | Online Article Text |
id | pubmed-6911100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69111002019-12-23 A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences Ramshaw, Rebecca E. Letourneau, Ian D. Hong, Amy Y. Hon, Julia Morgan, Julia D. Osborne, Joshua C. P. Shirude, Shreya Van Kerkhove, Maria D. Hay, Simon I. Pigott, David M. Sci Data Data Descriptor As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover. Nature Publishing Group UK 2019-12-13 /pmc/articles/PMC6911100/ /pubmed/31836720 http://dx.doi.org/10.1038/s41597-019-0330-0 Text en © The Author(s) 2019 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 Ramshaw, Rebecca E. Letourneau, Ian D. Hong, Amy Y. Hon, Julia Morgan, Julia D. Osborne, Joshua C. P. Shirude, Shreya Van Kerkhove, Maria D. Hay, Simon I. Pigott, David M. A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title | A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title_full | A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title_fullStr | A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title_full_unstemmed | A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title_short | A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences |
title_sort | database of geopositioned middle east respiratory syndrome coronavirus occurrences |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6911100/ https://www.ncbi.nlm.nih.gov/pubmed/31836720 http://dx.doi.org/10.1038/s41597-019-0330-0 |
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