Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.
Identifieur interne : 001930 ( PubMed/Corpus ); précédent : 001929; suivant : 001931Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.
Auteurs : C. Poletto ; C. Pelat ; D. Levy-Bruhl ; Y. Yazdanpanah ; P Y Boelle ; V. ColizzaSource :
- Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin [ 1560-7917 ] ; 2014.
English descriptors
- KwdEn :
- Coronavirus (isolation & purification), Coronavirus Infections (epidemiology), Coronavirus Infections (transmission), Disease Reservoirs (virology), Epidemics (statistics & numerical data), Global Health, Humans, Likelihood Functions, Middle East (epidemiology), Respiratory Tract Infections (epidemiology), Respiratory Tract Infections (transmission), Risk Assessment.
- MESH :
- geographic , epidemiology : Middle East.
- epidemiology : Coronavirus Infections, Respiratory Tract Infections.
- isolation & purification : Coronavirus.
- statistics & numerical data : Epidemics.
- transmission : Coronavirus Infections, Respiratory Tract Infections.
- virology : Disease Reservoirs.
- Global Health, Humans, Likelihood Functions, Risk Assessment.
Abstract
The emergence of the novel Middle East (ME) respiratory syndrome coronavirus (MERS-CoV) has raised global public health concerns regarding the current situation and its future evolution. Here we propose an integrative maximum likelihood analysis of both cluster data in the ME and importations in a set of European countries to assess the transmission scenario and incidence of sporadic infections. Our approach is based on a spatial-transmission model integrating mobility data worldwide and allows for variations in the zoonotic/environmental transmission and under-ascertainment. Maximum likelihood estimates for the ME, considering outbreak data up to 31 August 2013, indicate the occurrence of a subcritical epidemic with a reproductive number R of 0.50 (95% confidence interval (CI): 0.30-0.77) associated with a daily rate of sporadic introductions psp of 0.28 (95% CI: 0.12-0.85). Infections in the ME appear to be mainly dominated by zoonotic/environmental transmissions, with possible under-ascertainment (ratio of estimated to observed (0.116) sporadic cases equal to 2.41, 95% CI: 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from ME countries indicate areas at high risk of importation. While dismissing an immediate threat for global health security, this analysis provides a baseline scenario for future reference and updates, suggests reinforced surveillance to limit under-ascertainment, and calls for alertness in high importation risk areas worldwide.
DOI: 10.2807/1560-7917.es2014.19.23.20824
PubMed: 24957746
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pubmed:24957746Le document en format XML
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Yazdanpanah</name></author><author><name sortKey="Boelle, P Y" sort="Boelle, P Y" uniqKey="Boelle P" first="P Y" last="Boelle">P Y Boelle</name></author><author><name sortKey="Colizza, V" sort="Colizza, V" uniqKey="Colizza V" first="V" last="Colizza">V. 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Pelat</name></author><author><name sortKey="Levy Bruhl, D" sort="Levy Bruhl, D" uniqKey="Levy Bruhl D" first="D" last="Levy-Bruhl">D. Levy-Bruhl</name></author><author><name sortKey="Yazdanpanah, Y" sort="Yazdanpanah, Y" uniqKey="Yazdanpanah Y" first="Y" last="Yazdanpanah">Y. Yazdanpanah</name></author><author><name sortKey="Boelle, P Y" sort="Boelle, P Y" uniqKey="Boelle P" first="P Y" last="Boelle">P Y Boelle</name></author><author><name sortKey="Colizza, V" sort="Colizza, V" uniqKey="Colizza V" first="V" last="Colizza">V. Colizza</name></author></analytic><series><title level="j">Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin</title><idno type="eISSN">1560-7917</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Coronavirus (isolation & purification)</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (transmission)</term><term>Disease Reservoirs (virology)</term><term>Epidemics (statistics & numerical data)</term><term>Global Health</term><term>Humans</term><term>Likelihood Functions</term><term>Middle East (epidemiology)</term><term>Respiratory Tract Infections (epidemiology)</term><term>Respiratory Tract Infections (transmission)</term><term>Risk Assessment</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Middle East</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Epidemics</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Coronavirus Infections</term><term>Respiratory Tract Infections</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Disease Reservoirs</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Global Health</term><term>Humans</term><term>Likelihood Functions</term><term>Risk Assessment</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The emergence of the novel Middle East (ME) respiratory syndrome coronavirus (MERS-CoV) has raised global public health concerns regarding the current situation and its future evolution. Here we propose an integrative maximum likelihood analysis of both cluster data in the ME and importations in a set of European countries to assess the transmission scenario and incidence of sporadic infections. Our approach is based on a spatial-transmission model integrating mobility data worldwide and allows for variations in the zoonotic/environmental transmission and under-ascertainment. Maximum likelihood estimates for the ME, considering outbreak data up to 31 August 2013, indicate the occurrence of a subcritical epidemic with a reproductive number R of 0.50 (95% confidence interval (CI): 0.30-0.77) associated with a daily rate of sporadic introductions psp of 0.28 (95% CI: 0.12-0.85). Infections in the ME appear to be mainly dominated by zoonotic/environmental transmissions, with possible under-ascertainment (ratio of estimated to observed (0.116) sporadic cases equal to 2.41, 95% CI: 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from ME countries indicate areas at high risk of importation. While dismissing an immediate threat for global health security, this analysis provides a baseline scenario for future reference and updates, suggests reinforced surveillance to limit under-ascertainment, and calls for alertness in high importation risk areas worldwide.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24957746</PMID><DateCompleted><Year>2014</Year><Month>08</Month><Day>18</Day></DateCompleted><DateRevised><Year>2019</Year><Month>06</Month><Day>09</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1560-7917</ISSN><JournalIssue CitedMedium="Internet"><Volume>19</Volume><Issue>23</Issue><PubDate><Year>2014</Year><Month>Jun</Month><Day>12</Day></PubDate></JournalIssue><Title>Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin</Title><ISOAbbreviation>Euro Surveill.</ISOAbbreviation></Journal><ArticleTitle>Assessment of the Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic in the Middle East and risk of international spread using a novel maximum likelihood analysis approach.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">20824</ELocationID><Abstract><AbstractText>The emergence of the novel Middle East (ME) respiratory syndrome coronavirus (MERS-CoV) has raised global public health concerns regarding the current situation and its future evolution. Here we propose an integrative maximum likelihood analysis of both cluster data in the ME and importations in a set of European countries to assess the transmission scenario and incidence of sporadic infections. Our approach is based on a spatial-transmission model integrating mobility data worldwide and allows for variations in the zoonotic/environmental transmission and under-ascertainment. Maximum likelihood estimates for the ME, considering outbreak data up to 31 August 2013, indicate the occurrence of a subcritical epidemic with a reproductive number R of 0.50 (95% confidence interval (CI): 0.30-0.77) associated with a daily rate of sporadic introductions psp of 0.28 (95% CI: 0.12-0.85). Infections in the ME appear to be mainly dominated by zoonotic/environmental transmissions, with possible under-ascertainment (ratio of estimated to observed (0.116) sporadic cases equal to 2.41, 95% CI: 1.03-7.32). No time evolution of the situation emerges. Analyses of flight passenger data from ME countries indicate areas at high risk of importation. 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