Stochastic and spatio-temporal analysis of the Middle East Respiratory Syndrome outbreak in South Korea, 2015.
Identifieur interne : 000374 ( PubMed/Checkpoint ); précédent : 000373; suivant : 000375Stochastic and spatio-temporal analysis of the Middle East Respiratory Syndrome outbreak in South Korea, 2015.
Auteurs : Hyunsun Lee [États-Unis]Source :
- Infectious Disease Modelling [ 2468-0427 ] ; 2019.
Abstract
South Korea was free of the Middle East Respiratory Syndrome (MERS) until 2015. The MERS outbreak in South Korea during 2015 was the largest outbreak of the Coronavirus outside the Middle East. The major characteristic of this outbreak is inter- or intra-hospital transmission. This recent MERS outbreak in South Korea is examined and assessed in this paper. The main objectives of the study is to characterize the pattern of the MERS outbreak in South Korea based on a basic reproductive ratio, the probability of ultimate extinction of the disease, and the spatio-temporal proximity of occurrence between patients. The survival function method and stochastic branching process model are adapted to calculate the basic reproductive ratio and the probability of ultimate extinction of the disease. We further investigate the occurrence pattern of the outbreak using a spatio-temporal autocorrelation function.
DOI: 10.1016/j.idm.2019.06.002
PubMed: 31297469
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<front><div type="abstract" xml:lang="en">South Korea was free of the Middle East Respiratory Syndrome (MERS) until 2015. The MERS outbreak in South Korea during 2015 was the largest outbreak of the Coronavirus outside the Middle East. The major characteristic of this outbreak is inter- or intra-hospital transmission. This recent MERS outbreak in South Korea is examined and assessed in this paper. The main objectives of the study is to characterize the pattern of the MERS outbreak in South Korea based on a basic reproductive ratio, the probability of ultimate extinction of the disease, and the spatio-temporal proximity of occurrence between patients. The survival function method and stochastic branching process model are adapted to calculate the basic reproductive ratio and the probability of ultimate extinction of the disease. We further investigate the occurrence pattern of the outbreak using a spatio-temporal autocorrelation function.</div>
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<ReferenceList><Reference><Citation>Biomed Eng Online. 2017 Jun 13;16(1):79</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28610609</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Science. 2003 Jun 20;300(5627):1966-70</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12766207</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>J R Soc Interface. 2005 Sep 22;2(4):281-93</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16849186</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>J Hosp Infect. 2018 Jun;99(2):162-168</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28958834</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Nature. 2004 Dec 16;432(7019):904-6</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15602562</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Emerg Infect Dis. 2013 Jun;19(6):945-53</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23735713</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
<ReferenceList><Reference><Citation>Biomed Res Int. 2016;2016:7247983</Citation>
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