Abstract
AbstractAs 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.
Funder
Bill and Melinda Gates Foundation
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
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