A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences
Identifieur interne : 000729 ( Main/Exploration ); précédent : 000728; suivant : 000730A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences
Auteurs : Rebecca E. Ramshaw ; Ian D. Letourneau ; Amy Y. Hong [États-Unis] ; Julia Hon ; Julia D. Morgan ; Joshua C. P. Osborne ; Shreya Shirude ; Maria D. Van Kerkhove [Suisse] ; Simon I. Hay ; David M. PigottSource :
- Scientific Data [ 2052-4463 ] ; 2019.
Abstract
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.
Url:
DOI: 10.1038/s41597-019-0330-0
PubMed: 31836720
PubMed Central: 6911100
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p id="Par1">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.</p>
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<country name="Suisse"><noRegion><name sortKey="Van Kerkhove, Maria D" sort="Van Kerkhove, Maria D" uniqKey="Van Kerkhove M" first="Maria D." last="Van Kerkhove">Maria D. Van Kerkhove</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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