Serveur d'exploration MERS

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Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017

Identifieur interne : 000459 ( Pmc/Corpus ); précédent : 000458; suivant : 000460

Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017

Auteurs : Sibylle Bernard-Stoecklin ; Birgit Nikolay ; Abdullah Assiri ; Abdul Aziz Bin Saeed ; Peter Karim Ben Embarek ; Hassan El Bushra ; Moran Ki ; Mamunur Rahman Malik ; Arnaud Fontanet ; Simon Cauchemez ; Maria D. Van Kerkhove

Source :

RBID : PMC:6517387

Abstract

Since its emergence in 2012, 2,260 cases and 803 deaths due to Middle East respiratory syndrome coronavirus (MERS-CoV) have been reported to the World Health Organization. Most cases were due to transmission in healthcare settings, sometimes causing large outbreaks. We analyzed epidemiologic and clinical data of laboratory-confirmed MERS-CoV cases from eleven healthcare-associated outbreaks in the Kingdom of Saudi Arabia and the Republic of Korea between 2015–2017. We quantified key epidemiological differences between outbreaks. Twenty-five percent (n = 105/422) of MERS cases who acquired infection in a hospital setting were healthcare personnel. In multivariate analyses, age ≥65 (OR 4.8, 95%CI: 2.6–8.7) and the presence of underlying comorbidities (OR: 2.7, 95% CI: 1.3–5.7) were associated with increased mortality whereas working as healthcare personnel was protective (OR 0.07, 95% CI: 0.01–0.34). At the start of these outbreaks, the reproduction number ranged from 1.0 to 5.7; it dropped below 1 within 2 to 6 weeks. This study provides a comprehensive characterization of MERS HCA-outbreaks. Our results highlight heterogeneities in the epidemiological profile of healthcare-associated outbreaks. The limitations of our study stress the urgent need for standardized data collection for high-threat respiratory pathogens, such as MERS-CoV.


Url:
DOI: 10.1038/s41598-019-43586-9
PubMed: 31089148
PubMed Central: 6517387

Links to Exploration step

PMC:6517387

Le document en format XML

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<p id="Par1">Since its emergence in 2012, 2,260 cases and 803 deaths due to Middle East respiratory syndrome coronavirus (MERS-CoV) have been reported to the World Health Organization. Most cases were due to transmission in healthcare settings, sometimes causing large outbreaks. We analyzed epidemiologic and clinical data of laboratory-confirmed MERS-CoV cases from eleven healthcare-associated outbreaks in the Kingdom of Saudi Arabia and the Republic of Korea between 2015–2017. We quantified key epidemiological differences between outbreaks. Twenty-five percent (n = 105/422) of MERS cases who acquired infection in a hospital setting were healthcare personnel. In multivariate analyses, age ≥65 (OR 4.8, 95%CI: 2.6–8.7) and the presence of underlying comorbidities (OR: 2.7, 95% CI: 1.3–5.7) were associated with increased mortality whereas working as healthcare personnel was protective (OR 0.07, 95% CI: 0.01–0.34). At the start of these outbreaks, the reproduction number ranged from 1.0 to 5.7; it dropped below 1 within 2 to 6 weeks. This study provides a comprehensive characterization of MERS HCA-outbreaks. Our results highlight heterogeneities in the epidemiological profile of healthcare-associated outbreaks. The limitations of our study stress the urgent need for standardized data collection for high-threat respiratory pathogens, such as MERS-CoV.</p>
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<journal-id journal-id-type="nlm-ta">Sci Rep</journal-id>
<journal-id journal-id-type="iso-abbrev">Sci Rep</journal-id>
<journal-title-group>
<journal-title>Scientific Reports</journal-title>
</journal-title-group>
<issn pub-type="epub">2045-2322</issn>
<publisher>
<publisher-name>Nature Publishing Group UK</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">31089148</article-id>
<article-id pub-id-type="pmc">6517387</article-id>
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<article-id pub-id-type="doi">10.1038/s41598-019-43586-9</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Bernard-Stoecklin</surname>
<given-names>Sibylle</given-names>
</name>
<xref ref-type="aff" rid="Aff1">1</xref>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nikolay</surname>
<given-names>Birgit</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Assiri</surname>
<given-names>Abdullah</given-names>
</name>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bin Saeed</surname>
<given-names>Abdul Aziz</given-names>
</name>
<xref ref-type="aff" rid="Aff5">5</xref>
<xref ref-type="aff" rid="Aff6">6</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ben Embarek</surname>
<given-names>Peter Karim</given-names>
</name>
<xref ref-type="aff" rid="Aff7">7</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>El Bushra</surname>
<given-names>Hassan</given-names>
</name>
<xref ref-type="aff" rid="Aff5">5</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ki</surname>
<given-names>Moran</given-names>
</name>
<xref ref-type="aff" rid="Aff8">8</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Malik</surname>
<given-names>Mamunur Rahman</given-names>
</name>
<xref ref-type="aff" rid="Aff9">9</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fontanet</surname>
<given-names>Arnaud</given-names>
</name>
<xref ref-type="aff" rid="Aff10">10</xref>
<xref ref-type="aff" rid="Aff11">11</xref>
<xref ref-type="aff" rid="Aff12">12</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cauchemez</surname>
<given-names>Simon</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-6135-0018</contrib-id>
<name>
<surname>Van Kerkhove</surname>
<given-names>Maria D.</given-names>
</name>
<address>
<email>vankerkhovem@who.int</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
<xref ref-type="aff" rid="Aff13">13</xref>
</contrib>
<aff id="Aff1">
<label>1</label>
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<institution-id institution-id-type="GRID">grid.428999.7</institution-id>
<institution>Formerly Outbreak Investigation Task Force,</institution>
<institution>Centre for Global Health, Institut Pasteur,</institution>
</institution-wrap>
75015 Paris, France</aff>
<aff id="Aff2">
<label>2</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 5948 8741</institution-id>
<institution-id institution-id-type="GRID">grid.493975.5</institution-id>
<institution>Present Address: Direction of infectious diseases,</institution>
<institution>Santé publique France,</institution>
</institution-wrap>
Saint-Maurice, 94410 France</aff>
<aff id="Aff3">
<label>3</label>
Mathematical Modelling of Infectious Diseases, Institut Pasteur, UMR2000, CNRS, 75015 Paris, France</aff>
<aff id="Aff4">
<label>4</label>
<institution-wrap>
<institution-id institution-id-type="GRID">grid.415696.9</institution-id>
<institution>Ministry of Health,</institution>
</institution-wrap>
Riyadh, Saudi Arabia</aff>
<aff id="Aff5">
<label>5</label>
<institution-wrap>
<institution-id institution-id-type="GRID">grid.415696.9</institution-id>
<institution>Formerly Ministry of Health,</institution>
</institution-wrap>
Riyadh, Saudi Arabia</aff>
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<label>6</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id>
<institution-id institution-id-type="GRID">grid.56302.32</institution-id>
<institution>Present Address: Department of Family and Community Medicine, College of Medicine,</institution>
<institution>King Saud University,</institution>
</institution-wrap>
Riyadh, Saudi Arabia</aff>
<aff id="Aff7">
<label>7</label>
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<institution-id institution-id-type="ISNI">0000000121633745</institution-id>
<institution-id institution-id-type="GRID">grid.3575.4</institution-id>
<institution>International Food Safety Authorities Network (INFOSAN) Management, Department of Food Safety and Zoonoses,</institution>
<institution>World Health Organization,</institution>
</institution-wrap>
Geneva, Switzerland</aff>
<aff id="Aff8">
<label>8</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 0628 9810</institution-id>
<institution-id institution-id-type="GRID">grid.410914.9</institution-id>
<institution>Department of Cancer Control and Policy,</institution>
<institution>Graduate School of Cancer Science and Policy, National Cancer Center,</institution>
</institution-wrap>
Goyang, Korea</aff>
<aff id="Aff9">
<label>9</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0001 1942 4602</institution-id>
<institution-id institution-id-type="GRID">grid.483405.e</institution-id>
<institution>Infectious Hazard Management Unit, Department of Health Emergencies,</institution>
<institution>World Health Organization Regional Office for the Eastern Mediterranean,</institution>
</institution-wrap>
Cairo, Egypt</aff>
<aff id="Aff10">
<label>10</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0001 2353 6535</institution-id>
<institution-id institution-id-type="GRID">grid.428999.7</institution-id>
<institution>Emerging Diseases Epidemiology Unit,</institution>
<institution>Institut Pasteur,</institution>
</institution-wrap>
75015 Paris, France</aff>
<aff id="Aff11">
<label>11</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0001 2353 6535</institution-id>
<institution-id institution-id-type="GRID">grid.428999.7</institution-id>
<institution>Centre for Global Health,</institution>
<institution>Institut Pasteur,</institution>
</institution-wrap>
75015 Paris, France</aff>
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<label>12</label>
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<institution-id institution-id-type="ISNI">0000 0001 2185 090X</institution-id>
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<institution>Conservatoire National des Arts et Métiers,</institution>
</institution-wrap>
Paris, France</aff>
<aff id="Aff13">
<label>13</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000000121633745</institution-id>
<institution-id institution-id-type="GRID">grid.3575.4</institution-id>
<institution>Infectious Hazards Management, Health Emergencies Programme,</institution>
<institution>World Health Organization,</institution>
</institution-wrap>
Geneva, Switzerland</aff>
</contrib-group>
<pub-date pub-type="epub">
<day>14</day>
<month>5</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>14</day>
<month>5</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="collection">
<year>2019</year>
</pub-date>
<volume>9</volume>
<elocation-id>7385</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>11</month>
<year>2018</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>4</month>
<year>2019</year>
</date>
</history>
<permissions>
<copyright-statement>© The Author(s) 2019</copyright-statement>
<license license-type="OpenAccess">
<license-p>
<bold>Open Access</bold>
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
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
.</license-p>
</license>
</permissions>
<abstract id="Abs1">
<p id="Par1">Since its emergence in 2012, 2,260 cases and 803 deaths due to Middle East respiratory syndrome coronavirus (MERS-CoV) have been reported to the World Health Organization. Most cases were due to transmission in healthcare settings, sometimes causing large outbreaks. We analyzed epidemiologic and clinical data of laboratory-confirmed MERS-CoV cases from eleven healthcare-associated outbreaks in the Kingdom of Saudi Arabia and the Republic of Korea between 2015–2017. We quantified key epidemiological differences between outbreaks. Twenty-five percent (n = 105/422) of MERS cases who acquired infection in a hospital setting were healthcare personnel. In multivariate analyses, age ≥65 (OR 4.8, 95%CI: 2.6–8.7) and the presence of underlying comorbidities (OR: 2.7, 95% CI: 1.3–5.7) were associated with increased mortality whereas working as healthcare personnel was protective (OR 0.07, 95% CI: 0.01–0.34). At the start of these outbreaks, the reproduction number ranged from 1.0 to 5.7; it dropped below 1 within 2 to 6 weeks. This study provides a comprehensive characterization of MERS HCA-outbreaks. Our results highlight heterogeneities in the epidemiological profile of healthcare-associated outbreaks. The limitations of our study stress the urgent need for standardized data collection for high-threat respiratory pathogens, such as MERS-CoV.</p>
</abstract>
<kwd-group kwd-group-type="npg-subject">
<title>Subject terms</title>
<kwd>Infectious diseases</kwd>
<kwd>Risk factors</kwd>
</kwd-group>
<funding-group>
<award-group>
<funding-source>
<institution-wrap>
<institution-id institution-id-type="FundRef">https://doi.org/10.13039/501100001961</institution-id>
<institution>AXA Research Fund (Le Fonds AXA pour la Recherche)</institution>
</institution-wrap>
</funding-source>
</award-group>
</funding-group>
<custom-meta-group>
<custom-meta>
<meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2019</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="Sec1" sec-type="introduction">
<title>Introduction</title>
<p id="Par2">Since its emergence in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) has caused recurrent spillovers from dromedary camel populations into the human population
<sup>
<xref ref-type="bibr" rid="CR1">1</xref>
<xref ref-type="bibr" rid="CR3">3</xref>
</sup>
. As of 1 October 2018, a total of 2260 laboratory-confirmed cases of MERS-CoV infection from 27 different countries, including 803 deaths, have been reported to the World Health Organization (WHO), with a large majority of them concentrated in the Arabian peninsula
<sup>
<xref ref-type="bibr" rid="CR4">4</xref>
</sup>
. Although human-to-human transmission of MERS-CoV has so far been self-limiting
<sup>
<xref ref-type="bibr" rid="CR5">5</xref>
<xref ref-type="bibr" rid="CR7">7</xref>
</sup>
, substantial human-to-human transmission has been observed in healthcare settings
<sup>
<xref ref-type="bibr" rid="CR8">8</xref>
<xref ref-type="bibr" rid="CR19">19</xref>
</sup>
, reaching up to approximately 550 cases in six weeks in Jeddah and Riyadh in the spring 2014
<sup>
<xref ref-type="bibr" rid="CR20">20</xref>
<xref ref-type="bibr" rid="CR22">22</xref>
</sup>
(Fig. 
<xref rid="Fig1" ref-type="fig">1A</xref>
).
<fig id="Fig1">
<label>Figure 1</label>
<caption>
<p>Epidemiological curves of MERS-CoV infections by outbreak. (
<bold>A</bold>
) Global MERS-CoV epidemiological curve. Gray surface: total weekly number of laboratory-confirmed MERS-CoV infections reported to WHO. Colored curves: HCA-outbreaks included in the study after systematic policies and procedures for case identification and comprehensive contact identification and follow up were established and implemented. (
<bold>B</bold>
) Weekly number of cases in each outbreak, each line representing an outbreak. Dark blue: ROK15; grey: SAU15_1; orange: SAU15_2; light green: SAU16_1; light blue: SAU16_2; dark green: SAU16_3; red: SAU17_1; pink: SAU17_2; purple: SAU17_3; brown: SAU17_4; turquoise: SAU17_5. (
<bold>C</bold>
) Epidemic curve for each HCA by week comparing symptomatic (dark grey), asymptomatic case (light grey) and unknown symptoms of laboratory confirmed cases (white). X axis represents the number of weeks since the first case was reported in each HCA-outbreak.</p>
</caption>
<graphic xlink:href="41598_2019_43586_Fig1_HTML" id="d29e474"></graphic>
</fig>
</p>
<p id="Par3">Such large healthcare-associated (HCA) outbreaks have mainly been limited to the Kingdom of Saudi Arabia (KSA) and the United Arabian Emirates (UAE) until the spring 2015, when a single imported case of MERS returning from the Middle East initiated a cluster of 186 cases in the Republic of Korea (ROK) across at least 17 hospitals and much of the country
<sup>
<xref ref-type="bibr" rid="CR18">18</xref>
</sup>
. Super spreading events in healthcare settings has been described for several previous MERS outbreaks, including an outbreak in Al-Hasa governorate in 2013 and during the outbreak in ROK, where approximately 80% of the transmission events were epidemiologically linked to five MERS cases
<sup>
<xref ref-type="bibr" rid="CR14">14</xref>
,
<xref ref-type="bibr" rid="CR18">18</xref>
,
<xref ref-type="bibr" rid="CR23">23</xref>
</sup>
. Superspreading events in health care facilities have been observed in similar high threat respiratory disease pathogens, such as Severe Acute Respiratory Syndrome (SARS) in Canada, China, Singapore
<sup>
<xref ref-type="bibr" rid="CR24">24</xref>
<xref ref-type="bibr" rid="CR26">26</xref>
</sup>
.</p>
<p id="Par4">While more than half of the laboratory confirmed MERS-CoV infections reported globally to date are associated with human-to-human transmission in healthcare settings
<sup>
<xref ref-type="bibr" rid="CR27">27</xref>
</sup>
, there has been little human-to-human transmission reported in household settings
<sup>
<xref ref-type="bibr" rid="CR28">28</xref>
</sup>
. Outbreak investigations and scientific studies conducted during or after MERS hospital outbreaks have identified that aerosol-generating medical procedures with improper or inadequate personal protective equipment place medical personnel and patients sharing wards with MERS patients and family visitors at higher risk for MERS-CoV infection
<sup>
<xref ref-type="bibr" rid="CR29">29</xref>
,
<xref ref-type="bibr" rid="CR30">30</xref>
</sup>
, with exposure to infectious droplets being the likely source of contamination. Although close unprotected contact with a MERS patient is generally considered necessary for human-to-human transmission
<sup>
<xref ref-type="bibr" rid="CR31">31</xref>
</sup>
, several studies have revealed that MERS-CoV particles can persist on surfaces as long as several days, raising the possibility of a role of fomites in transmission
<sup>
<xref ref-type="bibr" rid="CR32">32</xref>
,
<xref ref-type="bibr" rid="CR33">33</xref>
</sup>
. Fomite transmission is further supported by observed viral spreading between rooms that were clearly separated
<sup>
<xref ref-type="bibr" rid="CR15">15</xref>
,
<xref ref-type="bibr" rid="CR18">18</xref>
</sup>
and outbreaks that occurred in hemodialysis units
<sup>
<xref ref-type="bibr" rid="CR14">14</xref>
,
<xref ref-type="bibr" rid="CR15">15</xref>
</sup>
.</p>
<p id="Par5">Factors leading to healthcare-associated outbreaks include overcrowding in emergency departments, slow triage and isolation of suspected patients and inadequate compliance to infection prevention and control procedures
<sup>
<xref ref-type="bibr" rid="CR17">17</xref>
,
<xref ref-type="bibr" rid="CR23">23</xref>
,
<xref ref-type="bibr" rid="CR34">34</xref>
</sup>
. However, few studies have described or compared the characteristics of HCA-outbreaks as a whole in terms of their size, epidemiologic factors
<sup>
<xref ref-type="bibr" rid="CR34">34</xref>
,
<xref ref-type="bibr" rid="CR35">35</xref>
</sup>
, or the role of interventions to stop transmission
<sup>
<xref ref-type="bibr" rid="CR23">23</xref>
,
<xref ref-type="bibr" rid="CR36">36</xref>
</sup>
. Here, we provide the largest comprehensive study of eleven healthcare-associated outbreaks that occurred between 2015 and June 2017. We carried out a comparative analysis of these outbreaks in terms of epidemiological profiles, demographic characteristics and clinical outcome.</p>
</sec>
<sec id="Sec2">
<title>Methods</title>
<sec id="Sec3">
<title>Study design</title>
<p id="Par6">We analyzed epidemiological datasets of laboratory-confirmed MERS patients and focused our study on eleven healthcare-associated outbreaks that were reported in KSA and ROK since 2015, when policies and procedures for case identification and comprehensive contact identification and follow up became systematic and were implemented by affected countries. The data used documented MERS-CoV infections reported to WHO under the International Health Regulations (2005). We only included clusters of cases/outbreaks that were linked to healthcare facilities. Supplemental ROK case-based data were provided as a detailed line list of the Korean MERS cases included in a published study
<sup>
<xref ref-type="bibr" rid="CR17">17</xref>
</sup>
. We defined laboratory-confirmed MERS-CoV infection as following WHO guidelines
<sup>
<xref ref-type="bibr" rid="CR4">4</xref>
,
<xref ref-type="bibr" rid="CR37">37</xref>
</sup>
.</p>
<p id="Par7">We defined a HCA-outbreak as the occurrence of 5 or more laboratory-confirmed MERS-CoV infections with reported epidemiologic links between cases and during which the human-to-human transmission events were documented within a single healthcare facility, with no more than 14 days apart between cases symptom onset. The MERS outbreak in the Republic of Korea in 2015 is treated as a single outbreak.</p>
<p id="Par8">Individual-level variables included information on age, sex, nationality, occupation (healthcare personnel (HCP) yes/no), dates of symptom onset, date of notification to WHO, presence of any pre-existing co-morbid conditions, and clinical outcome. In case of missing or conflicting information and when information from the country was not available, we considered the data as missing.</p>
</sec>
<sec id="Sec4">
<title>Statistical analysis</title>
<p id="Par9">Descriptive analysis was performed by HCA-outbreak (outbreak-level analysis) using aggregated data, and for all cases (individual-level analysis). All analyses were conducted using Stata, version 14 (College Station, TX: StataCorp LP), Microsoft Excel (Version 15.35 2017, Jones, Chicago USA) and
<italic>R</italic>
.</p>
<sec id="Sec5">
<title>Outbreak-level analysis</title>
<p id="Par10">We calculated the duration, size and case fatality ratio for each outbreak. The duration of an outbreak was calculated as the number of days between the date of symptom onset of the first reported case to the date of symptom onset of the last reported case.</p>
<p id="Par11">We obtained weekly smoothed estimates of the case reproduction number based on the approach developed by Wallinga and Teunis
<sup>
<xref ref-type="bibr" rid="CR38">38</xref>
,
<xref ref-type="bibr" rid="CR39">39</xref>
</sup>
using the
<italic>R</italic>
<sub>0</sub>
package. We assumed that the serial interval of MERS-CoV had a Gamma distribution with a mean of 6.8 days and a standard deviation of 4.1 days, as described elsewhere
<sup>
<xref ref-type="bibr" rid="CR40">40</xref>
</sup>
.</p>
</sec>
<sec id="Sec6">
<title>Individual-level analysis</title>
<p id="Par12">We summarized case characteristics as frequencies and proportions for categorical variables, as median and interquartile ranges (IQR) for continuous variables. Chi-square tests were used to compare subgroups of cases when appropriate. A P value of less than 0.05 was used to indicate statistical significance. Univariate analysis identified variables significantly associated with fatal outcome, which were included in a multivariable model. Model selection was performed using a multilevel mixed-effects logistic regression with backwards selection taking into account clustering of individuals by outbreak. For the variable “age”, the cut-off was fixed at 65, based on the results of the univariate analysis. Variables with p-values < 0.05 were retained in the final model.</p>
</sec>
</sec>
<sec id="Sec7">
<title>Ethics</title>
<p id="Par13">All data used in these secondary analyses were de-identified data obtained from WHO or datasets from peer-reviewed literature. As such, these data were deemed exempt from institutional review board assessment.</p>
</sec>
</sec>
<sec id="Sec8" sec-type="results">
<title>Results</title>
<sec id="Sec9">
<title>General characteristics of HCA-outbreaks</title>
<p id="Par14">Since 1 January 2015 to 1 October 2018, 2,260 laboratory-confirmed MERS-CoV infections have been reported to WHO. Figure 
<xref rid="Fig1" ref-type="fig">1A</xref>
illustrates the global epidemic curve since MERS was first identified in humans. Each peak is associated with a health care associated outbreak (colored lines, Fig. 
<xref rid="Fig1" ref-type="fig">1A</xref>
). From 2015, affected countries implemented systematic contact tracing and follow up (including laboratory testing), investigation and data collection of MERS suspect cases
<sup>
<xref ref-type="bibr" rid="CR41">41</xref>
,
<xref ref-type="bibr" rid="CR42">42</xref>
</sup>
.</p>
<p id="Par15">In our analysis, a total of 423 laboratory-confirmed MERS cases from eleven distinct HCA-outbreaks during 2015–2017 were included (Table 
<xref rid="Tab1" ref-type="table">1</xref>
). The eleven HCA-outbreaks varied in terms of duration, size and epidemiological profile (Table 
<xref rid="Tab1" ref-type="table">1</xref>
, Fig. 
<xref rid="Fig1" ref-type="fig">1B</xref>
). The median number of total reported cases per outbreak was 10 (interquartile range, [IQR] 6–27), ranging from 5 to 186 cases. The median duration was 20 days (IQR 16–23), ranging from 10 to 57 days.
<table-wrap id="Tab1">
<label>Table 1</label>
<caption>
<p>Characteristics of HCA MERS outbreaks from 2015–2017.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th>Outbreak</th>
<th>Country/City</th>
<th>Year of outbreak</th>
<th>Period of time*</th>
<th>Number of cases</th>
<th>Duration (days)</th>
<th>Initial R(t), median (95% CI)</th>
<th>Time to peak (weeks)</th>
<th>Delay onset to notification</th>
<th>Case fatality ratio</th>
<th>Age, median (IQR)</th>
<th>Male, n (%)</th>
<th>Asymptomatic, n (%)</th>
<th>Presence of comorbidity, n (%)</th>
<th>HCP, n (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td>ROK15</td>
<td>Republic of Korea</td>
<td>2015</td>
<td>11/05/15–03/07/15</td>
<td>186</td>
<td>53</td>
<td>5.7 (3.0–9.0)</td>
<td>4</td>
<td>6 (3–9)</td>
<td>18</td>
<td>55 (42–66)</td>
<td>110 (59)</td>
<td>1 (1)</td>
<td>83 (45)</td>
<td>32 (17)</td>
</tr>
<tr>
<td>SAU15_1</td>
<td>Riyadh</td>
<td>2015</td>
<td>13/07/15–08/09/15</td>
<td>112</td>
<td>57</td>
<td>2.9 (2.0–5.0)</td>
<td>6</td>
<td>5 (4–8)</td>
<td>50</td>
<td>58 (42–72)</td>
<td>68 (61)</td>
<td>0</td>
<td>82 (80)</td>
<td>15 (13)</td>
</tr>
<tr>
<td>SAU15_2</td>
<td>Al Manea</td>
<td>2015</td>
<td>03/10/15–22/10/15</td>
<td>8</td>
<td>19</td>
<td>1.4 (0.5–3.0)</td>
<td>4</td>
<td>8.5 (5–11.5)</td>
<td>75</td>
<td>57.5 (36.5–71)</td>
<td>6 (75)</td>
<td>0</td>
<td>6 (75)</td>
<td>2 (25)</td>
</tr>
<tr>
<td>SAU16_1</td>
<td>Buraidah</td>
<td>2016</td>
<td>06/02/16–13/03/16</td>
<td>19</td>
<td>36</td>
<td>1.0 (0.7–1.3)</td>
<td>4</td>
<td>4 (3–8)</td>
<td>42</td>
<td>36 (26–60)</td>
<td>15 (79)</td>
<td>3 (19)</td>
<td>11***</td>
<td>6 (32)</td>
</tr>
<tr>
<td>SAU16_2</td>
<td>Riyadh</td>
<td>2016</td>
<td>09/06/16–29/06/16</td>
<td>30</td>
<td>20</td>
<td>4.9 (2.7–7.3)</td>
<td>2</td>
<td>3 (3–4.5)</td>
<td>3</td>
<td>44.5 (32–58)</td>
<td>5 (17)</td>
<td>26 (87)</td>
<td>5***</td>
<td>17 (57)</td>
</tr>
<tr>
<td>SAU16_3</td>
<td>Hofouf</td>
<td>2016</td>
<td>10/10/16–20/10/16</td>
<td>5</td>
<td>10</td>
<td>1.6 (0.5–3.0)</td>
<td>2</td>
<td>3 (2–5)</td>
<td>40</td>
<td>55 (40–61)</td>
<td>4 (80)</td>
<td>0</td>
<td>3 (60)</td>
<td>2 (40)</td>
</tr>
<tr>
<td>SAU17_1</td>
<td>Wadi Aldwasser</td>
<td>2017</td>
<td>26/02/17–11/03/17</td>
<td>10</td>
<td>13</td>
<td>2.0 (0.3–4.3)</td>
<td>2</td>
<td>2.5 (2–5)</td>
<td>0</td>
<td>39 (32–52)</td>
<td>4 (40)</td>
<td>4 (40)</td>
<td>7 (78)</td>
<td>2 (20)</td>
</tr>
<tr>
<td>SAU17_2</td>
<td>Wadi Aldwasser</td>
<td>2017</td>
<td>11/04/17–26/04/17</td>
<td>5</td>
<td>15</td>
<td>3.0 (3.0–4.0)</td>
<td>2</td>
<td>2**</td>
<td>20</td>
<td>50 (31–55)</td>
<td>5 (100)</td>
<td>4 (80)</td>
<td>1***</td>
<td>1 (20)</td>
</tr>
<tr>
<td>SAU17_3</td>
<td>Riyadh</td>
<td>2017</td>
<td>24/04/17–15/05/17</td>
<td>5</td>
<td>21</td>
<td>1.0 (0.7–1.3)</td>
<td>3</td>
<td>2 (2–6)</td>
<td>20</td>
<td>33 (30–38)</td>
<td>3 (60)</td>
<td>3 (60)</td>
<td>1***</td>
<td>3 (60)</td>
</tr>
<tr>
<td>SAU17_4</td>
<td>Riyadh</td>
<td>2017</td>
<td>26/05/17–19/06/17</td>
<td>34</td>
<td>24</td>
<td>4.3 (1.5–7.5)</td>
<td>3</td>
<td>2 (2–3.5)</td>
<td>21</td>
<td>34.5 (30–54)</td>
<td>20 (59)</td>
<td>22 (65)</td>
<td>14 (42)</td>
<td>17 (50)</td>
</tr>
<tr>
<td>SAU17_5</td>
<td>Riyadh</td>
<td>2017</td>
<td>28/05/17–17/06/17</td>
<td>9</td>
<td>20</td>
<td>2.3 (0.5–4.5)</td>
<td>2</td>
<td>4 (3–4)</td>
<td>11</td>
<td>45 (42–48)</td>
<td>3 (33)</td>
<td>4 (44)</td>
<td>1 (11)</td>
<td>8 (89)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>*Dates of symptom onset (or notification to WHO if the latter was not reported/available) of the first and the last cases. **No median or quartiles available: 4 cases out of 5 were notified to WHO the same day as the onset of symptoms. ***High proportion of missing values.</p>
</table-wrap-foot>
</table-wrap>
</p>
<p id="Par16">Three outbreaks began with sporadic cases during the first two to five weeks of the outbreak, while the other eight displayed a rapid increase to the peak. The median time between onset of symptoms of the first reported case and the peak of incidence was 3 weeks (IQR 2–3.75), ranging from 2 to 6 weeks.</p>
<p id="Par17">The case fatality ratio (CFR) in outbreaks was 28% (116 reported deaths among 423 cases), compared with the global overall CFR of 35.5% (800 reported deaths among 2,254 cases reported as of 1 October
<sup>
<xref ref-type="bibr" rid="CR3">3</xref>
</sup>
(Table 
<xref rid="Tab1" ref-type="table">1</xref>
). During HCA outbreaks, CFR ranged from 0 to 75% (p < 0.01) and CFR was significantly lower among HCP MERS-CoV infections compared to non-HCP MERS-CoV infections (2% vs. 36% p < 0.01).</p>
</sec>
<sec id="Sec10">
<title>Demographic and clinical characteristics</title>
<p id="Par18">The demographic and clinical characteristics of the cases from HCA outbreaks included in our analyses are summarized in Table 
<xref rid="Tab1" ref-type="table">1</xref>
. The median age was 54 (IQR, 36–65), and significantly varied by outbreak (p < 0.001). Five outbreaks had a median age <40 and the other 6 outbreaks had a median age ≥50.</p>
<p id="Par19">The majority of cases were male (57%, n = 243/423), and the sex ratio among cases differed significantly between outbreaks (p < 0.001). The overall proportion of HCP was 25% (n = 105/422). This proportion varied significantly by outbreak (p < 0.001), from 13% to 89% (Table 
<xref rid="Tab1" ref-type="table">1</xref>
). Median age was significantly lower among HCP than non-HCP cases (35 IQR 29–46 vs 58 IQR 45–70, p < 0.001) and the proportion of females was higher among HCP than non-HCP (70% vs 33%, n = 422, p < 0.001).</p>
<p id="Par20">More than half (57%, n = 214/377) of cases had at least one underlying co-morbid condition (Table 
<xref rid="Tab1" ref-type="table">1</xref>
), and this was significantly lower among females compared to males (46% vs 64%, respectively, n = 377, p < 0.001) and among HCP compared to non-HCP (13% vs 70%, n = 376, p < 0.001).</p>
<p id="Par21">Sixteen percent (n = 67/419) of cases were asymptomatic at time of reporting (Table 
<xref rid="Tab1" ref-type="table">1</xref>
). This proportion varied significantly between outbreaks ranging from 0% to 87% (n = 419, p < 0.001, Fig. 
<xref rid="Fig1" ref-type="fig">1C</xref>
). Median age of asymptomatic cases was 34 (IQR, 30–48), the majority of whom were females (70%, n = 47/67) and had no underlying co-morbid conditions (78%, n = 29/37). The proportion of HCP among asymptomatic infections was high (70%, n = 47/67), and the CFR was null.</p>
<p id="Par22">The median duration between symptom onset and case notification to WHO was 5 days (IQR 3–8).</p>
</sec>
<sec id="Sec11">
<title>Risk factors associated with fatal outcome</title>
<p id="Par23">In univariate analysis, fatal outcome was significantly associated with age (p < 0.001), presence of underlying comorbidities (p < 0.001), non-HCP status (p < 0.001), and male sex (p < 0.001, Table 
<xref rid="Tab2" ref-type="table">2</xref>
).
<table-wrap id="Tab2">
<label>Table 2</label>
<caption>
<p>Risk factors associated with the disease outcome among MERS cases (n = 423) identified in 11 HCA-outbreaks from 2015–2017.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2">Variables</th>
<th colspan="3">Univariate Analyses</th>
<th colspan="3">Multivariate Analyses</th>
</tr>
<tr>
<th>OR</th>
<th>p-value</th>
<th>95%CI</th>
<th>Adjusted OR</th>
<th>p-value</th>
<th>95%CI</th>
</tr>
</thead>
<tbody>
<tr>
<td colspan="7">Age</td>
</tr>
<tr>
<td>  <65</td>
<td>1</td>
<td></td>
<td></td>
<td>1</td>
<td></td>
<td></td>
</tr>
<tr>
<td>  ≧65</td>
<td>7.50</td>
<td><0.001</td>
<td>4.39–12.77</td>
<td>4.79</td>
<td><0.001</td>
<td>2.60–8.64</td>
</tr>
<tr>
<td>Underlying medical condition (yes vs. no)</td>
<td>10.12</td>
<td><0.001</td>
<td>5.07–20.21</td>
<td>2.74</td>
<td>0.007</td>
<td>1.32–5.70</td>
</tr>
<tr>
<td>Health care personnel status (HCP vs. non-HCP)</td>
<td>0.03</td>
<td><0.001</td>
<td>0.01–0.15</td>
<td>0.07</td>
<td>0.001</td>
<td>0.01–0.35</td>
</tr>
<tr>
<td>Gender (male vs. female</td>
<td>2.74</td>
<td><0.001</td>
<td>1.69–4.44</td>
<td></td>
<td></td>
<td></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>OR: odds ratio. Adj. OR: adjusted odds ratio. Analysis using individual-level data. Univariate comparison of the association between the probability of fatal outcome and each categorical variable, using the chi-square test with a significance threshold at 0.05. Multilevel mixed-effects logistic regression model with a random effect (outbreak) and adjusting for potential confounding factors, with an exclusion threshold of 0.05 (n = 376, p < 0.001). Missing values were excluded from both analyses.</p>
</table-wrap-foot>
</table-wrap>
</p>
<p id="Par24">In multivariate analysis, patients ≥65 years old (OR 4.79, 95% CI: 2.60–8.64) and the presence of ≥1 underlying comorbid condition (OR 2.74, 95% CI: 1.32–5.70) had an increased risk of death. HCP status was associated with a decreased risk of death (OR 0.07, 95% CI: 0.001–0.35) (Table 
<xref rid="Tab2" ref-type="table">2</xref>
).</p>
</sec>
<sec id="Sec12">
<title>Estimation of time-varying reproduction number</title>
<p id="Par25">At the start of each HCA outbreaks, the case reproduction number
<italic>R</italic>
<sub>
<italic>(t)</italic>
</sub>
ranged from 1.0 (95% CI 0.7–1.3) to 5.7 (95% CI 3.0–9.0) (Table 
<xref rid="Tab1" ref-type="table">1</xref>
and Fig. 
<xref rid="Fig2" ref-type="fig">2</xref>
). Estimates of
<italic>R</italic>
<sub>
<italic>(t)</italic>
</sub>
dropped below 1 within 2 to 6 weeks from the first reported case in the outbreak (n = 11 outbreaks, median 3 weeks, IQR 2–4).
<fig id="Fig2">
<label>Figure 2</label>
<caption>
<p>Weekly estimates of the case reproduction number R
<sub>(t)</sub>
for 11 HCA-outbreaks between 2015 and 2017. Weekly R
<sub>(t)</sub>
estimates per outbreak are shown (plain blue line) with their 95% confidence intervals interval (dotted blue lines) (left Y axis). The bar chart represents the weekly incidence (right Y axis). The horizontal dotted red line represents the R(t) threshold set at 1.</p>
</caption>
<graphic xlink:href="41598_2019_43586_Fig2_HTML" id="d29e1501"></graphic>
</fig>
</p>
</sec>
</sec>
<sec id="Sec13" sec-type="discussion">
<title>Discussion</title>
<p id="Par26">We provide here a comparative characterization of MERS HCA-outbreaks and report substantial heterogeneity between HCA-outbreaks illustrating the complexity of the factors contributing to the emergence of a cluster of cases associated with nosocomial transmission.</p>
<p id="Par27">The duration and epidemic profiles of outbreaks varied; some started with an apparent sharp increase in incidence while others began more slowly with isolated cases emerging intermittently for a few weeks before a cluster of cases appeared in a healthcare facility. Some outbreaks had a sharp decline in cases, while others experienced a long tail lasting several weeks after the peak.</p>
<p id="Par28">The median estimates of the reproduction number
<italic>R</italic>
(t) in the early stages of outbreaks included in our analyses reached as high as 5.7 in the Republic of Korea, as has been found by others
<sup>
<xref ref-type="bibr" rid="CR43">43</xref>
</sup>
, likely facilitated by multiple superspreading events at two hospitals
<sup>
<xref ref-type="bibr" rid="CR43">43</xref>
</sup>
. What is perhaps most informative from a public health perspective is the length of time it took to bring the outbreaks under control. All of outbreaks reached
<italic>R</italic>
<sub>
<italic>t</italic>
</sub>
values below 1 within 2 to 6 weeks after the first cases were identified, highlighting that the time frame in which hospital and ministry officials can implement control measures to stop nosocomial outbreaks.</p>
<p id="Par29">Factors explaining differences in HCA outbreak size and duration might include variations in the speed in which cases were suspected and timing of interventions implemented in healthcare settings, including contact identification, management and isolation of patients, improved infection prevention and control measures and in some cases, the requirement to close departments
<sup>
<xref ref-type="bibr" rid="CR14">14</xref>
<xref ref-type="bibr" rid="CR18">18</xref>
,
<xref ref-type="bibr" rid="CR29">29</xref>
</sup>
. In this study, we were not able to evaluate the impact of interventions in these outbreaks.</p>
<p id="Par30">Prevention of large HCA outbreaks since 2014 (Fig. 
<xref rid="Fig1" ref-type="fig">1A</xref>
), may be, in part, explained by improvements in contact tracing policies implemented in 2015. In 2015, contact tracing became more systematic with the identification and follow up of high (close, unprotected contact) and low risk contacts (protected HCW). In affected countries, National Ministries of Health and hospital staff comprehensively list all contacts of known MERS patients, including healthcare workers at all facilities/departments the patient visited, patients who shared wards/rooms with MERS patients, family and visitors and occupational contacts. Follow up of contacts includes the testing of all high-risk contacts, regardless of the development of symptoms. Recommendations stated that positive contacts are placed in quarantine (home or hospital isolation for asymptomatic or symptomatic secondary cases, respectively) until they test negative
<sup>
<xref ref-type="bibr" rid="CR41">41</xref>
,
<xref ref-type="bibr" rid="CR44">44</xref>
<xref ref-type="bibr" rid="CR46">46</xref>
</sup>
. Additionally, affected countries enhanced infection prevention and control procedures education, and training, and implemented visual triage systems
<sup>
<xref ref-type="bibr" rid="CR41">41</xref>
</sup>
to reduce delays in testing, isolation and care of suspected MERS-CoV patients. This has again been recently illustrated by the lack of secondary cases following the identification of a confirmed case of MERS in Korea in September 2018
<sup>
<xref ref-type="bibr" rid="CR47">47</xref>
</sup>
was due to the rapid and comprehensive isolation, treatment and management of contacts of the patient.</p>
<p id="Par31">The variation in outbreak size and duration is also affected by superspreading events early in some outbreaks, during which a limited number of cases generated a disproportionately large proportion of the secondary cases under specific conditions in hospitals, occurring in some outbreaks
<sup>
<xref ref-type="bibr" rid="CR48">48</xref>
<xref ref-type="bibr" rid="CR50">50</xref>
</sup>
. Two super spreading events have been documented in KSA and in the Republic of Korea. In the Republic of Korea, the practice of “doctor shopping”, extended stays in overcrowded emergency departments, cultural practices of large numbers of family members visiting sick relatives, and environmental contamination amplified transmission from some patients to others
<sup>
<xref ref-type="bibr" rid="CR14">14</xref>
,
<xref ref-type="bibr" rid="CR17">17</xref>
,
<xref ref-type="bibr" rid="CR18">18</xref>
,
<xref ref-type="bibr" rid="CR51">51</xref>
</sup>
. During the outbreak in KSA in 2015 at the Ministry of the National Guard Hospital, a high number of secondary cases were among HCP very quickly after the hospitalization and a surgical procedure of the index case
<sup>
<xref ref-type="bibr" rid="CR16">16</xref>
</sup>
. These events triggered comprehensive review IPC in hospitals, emergency department layout, movements of patients, triage of respiratory visits, duration of emergency department stay, training of hospital staff and disinfection of healthcare facilities.</p>
<p id="Par32">Our study confirmed that age and presence of comorbidities are linked to increased risk of death, similar to previously published results
<sup>
<xref ref-type="bibr" rid="CR52">52</xref>
,
<xref ref-type="bibr" rid="CR53">53</xref>
</sup>
whereas being HCP was protective. The protective effect of HCP could be explained by the fact that HCP are more likely to be younger (<60 years old) and have fewer underlying medical conditions than hospitalized patients, but also that they are likely to be identified earlier or seek medical care soon following contact with a confirmed patient.</p>
<p id="Par33">The proportion of asymptomatic secondary cases identified during outbreaks has increased since 2014. There is no evidence to suggest that this represents changes in virus pathogenicity, epidemiology or transmission patterns of MERS in recent years. However, the increase in the number of reported asymptomatic cases is hypothesized to be due to earlier detection efforts from more aggressive contact identification and testing during HCA-outbreaks since 2015 as testing policies adopted and implemented by KSA and other countries have changed following the large outbreaks in Jeddah/Riyadh in 2014
<sup>
<xref ref-type="bibr" rid="CR3">3</xref>
,
<xref ref-type="bibr" rid="CR41">41</xref>
,
<xref ref-type="bibr" rid="CR54">54</xref>
</sup>
. In 2017, 40–80% of the laboratory confirmed HCP secondary cases experienced no symptoms and were detected as part of a policy to test all contacts irrespective of symptoms (Table 
<xref rid="Tab1" ref-type="table">1</xref>
). We believe that the identification of HCP asymptomatic cases, and their subsequent isolation, has had a strong impact on prevent further human to human transmission in health care settings. This is visually demonstrated in Fig. 
<xref rid="Fig1" ref-type="fig">1C</xref>
by the outbreak labelled SAU16_2, which included 26 (of 30 reported cases) asymptomatic cases. While this is a large number of secondary cases, we argue that the early identification, isolation and recovery of these asymptomatic/mildly symptomatic cases effectively stopped human to human transmission.</p>
<p id="Par34">Our study has several limitations due to variability in the completeness and quality of case-based data provided to WHO since 2012 and also due to the lack of detailed information on the timing specific interventions were implemented in relation to each outbreak. Without detailed information on the timing of interventions in each health care facility it was not possible in our analyses to determine which intervention or combination of interventions had the greatest impact on stopping the MERS outbreaks. Moreover, prior to 2015, contacts without symptoms were not tested for MERS-CoV infection, thus the rate of identification of secondary cases was drastically different prior to 2015, which complicates the comparison of data collected before and after 2015. The improvements in data reporting on cases (e.g., more systematic reporting of underlying conditions, reported exposures, contacts between patients) from 2015 allowed us to perform better analyses with less missing values.</p>
<p id="Par35">We continue to encourage the policy of identifying, following and testing of all high risk contacts of MERS patients in HCA-outbreaks
<sup>
<xref ref-type="bibr" rid="CR3">3</xref>
,
<xref ref-type="bibr" rid="CR41">41</xref>
,
<xref ref-type="bibr" rid="CR55">55</xref>
</sup>
. The natural history of asymptomatic infection and role of asymptomatic or mildly symptomatic HCP in transmission of the virus between patients, requires detailed scientific studies to better understand their potential role in transmission
<sup>
<xref ref-type="bibr" rid="CR15">15</xref>
</sup>
.</p>
<p id="Par36">The sharing of outbreak experiences between affected hospitals within and between countries and a detailed evaluation of the impact of non-therapeutic interventions is critical to our understanding and for the prevention of nosocomial outbreaks of respiratory pathogens. Health care professionals and hospitals currently have tools to limit the extent and impact of such events, which include early identification and isolation of suspect patients and strict adherence to standard infection prevention and control measures. These are the hallmark of effective MERS-CoV control. A combination of interventions including the efficient triage of patients with respiratory symptoms at hospital entry; limiting wait times and overcrowding in waiting areas; isolation of suspected and confirmed cases; appropriate use of droplet personal protection equipment by HCP; basic hand hygiene; increased protective aerosol precautions for HCP during aerosol-generating medical procedures; efficient surface and environmental decontamination of areas with MERS patients, and extensive contact tracing, can prevent human to human transmission in health care settings.</p>
</sec>
</body>
<back>
<fn-group>
<fn>
<p>
<bold>Publisher’s note:</bold>
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
</fn>
</fn-group>
<ack>
<title>Acknowledgements</title>
<p>The authors would like to thank the many individuals involved in the collection of case-based data and in the care of MERS patients in the affected countries. B.N. and S.C. acknowledge financial support from the Investissement d’Avenir program, the Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), the Models of Infectious Disease Agent Study of the National Institute of General Medical Sciences, the AXA Research Fund and the INCEPTION project (PIA/ANR-16-CONV-0005).</p>
</ack>
<notes notes-type="author-contribution">
<title>Author Contributions</title>
<p>M.D.V.K., M.R.M., A.A. and A.A.B.S. developed the concept of the paper. S.B.-S., B.N., S.C. and M.D.V.K. conducted the analyses; S.B.-S., B.N., A.A., A.A.B.S., P.K.B.E., H.E.B., M.K., M.R.M., A.F., S.C. and M.D.V.K. contributed to the interpretation of the analyses and results and drafted and edited versions of the manuscript. S.B.-S., B.N., A.A., A.A.B.S., P.K.B.E., H.E.B., M.K., M.R.M., A.F., S.C. and M.D.V.K. all reviewed and approved the final manuscript.</p>
</notes>
<notes notes-type="COI-statement">
<title>Competing Interests</title>
<p id="Par37">The authors declare no competing interests.</p>
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