Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea
Identifieur interne : 000B78 ( Pmc/Corpus ); précédent : 000B77; suivant : 000B79Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea
Auteurs : Seung Woo Kim ; Jung Wan Park ; Hee-Dong Jung ; Jeong-Sun Yang ; Yong-Shik Park ; Changhwan Lee ; Kyung Min Kim ; Keon-Joo Lee ; Donghyok Kwon ; Young Joo Hur ; Boyoul Choi ; Moran KiSource :
- Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America [ 1058-4838 ] ; 2017.
Abstract
We evaluated the epidemiological risk factors for MERS-CoV transmission during the recent South Korean outbreak. MERS-CoV transmission was determined by host infectivity and the number of contacts, whereas super-spreading events were determined by the number of contacts and hospital visits.
Url:
DOI: 10.1093/cid/ciw768
PubMed: 27940937
PubMed Central: 7108049
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PMC:7108049Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea</title><author><name sortKey="Kim, Seung Woo" sort="Kim, Seung Woo" uniqKey="Kim S" first="Seung Woo" last="Kim">Seung Woo Kim</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Park, Jung Wan" sort="Park, Jung Wan" uniqKey="Park J" first="Jung Wan" last="Park">Jung Wan Park</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Jung, Hee Dong" sort="Jung, Hee Dong" uniqKey="Jung H" first="Hee-Dong" last="Jung">Hee-Dong Jung</name><affiliation><nlm:aff id="AF0002"><institution>Division of Respiratory Viruses, Center of Infectious Disease,</institution></nlm:aff></affiliation></author><author><name sortKey="Yang, Jeong Sun" sort="Yang, Jeong Sun" uniqKey="Yang J" first="Jeong-Sun" last="Yang">Jeong-Sun Yang</name><affiliation><nlm:aff id="AF0002"><institution>Division of Respiratory Viruses, Center of Infectious Disease,</institution></nlm:aff></affiliation></author><author><name sortKey="Park, Yong Shik" sort="Park, Yong Shik" uniqKey="Park Y" first="Yong-Shik" last="Park">Yong-Shik Park</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Lee, Changhwan" sort="Lee, Changhwan" uniqKey="Lee C" first="Changhwan" last="Lee">Changhwan Lee</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Kim, Kyung Min" sort="Kim, Kyung Min" uniqKey="Kim K" first="Kyung Min" last="Kim">Kyung Min Kim</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Lee, Keon Joo" sort="Lee, Keon Joo" uniqKey="Lee K" first="Keon-Joo" last="Lee">Keon-Joo Lee</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Kwon, Donghyok" sort="Kwon, Donghyok" uniqKey="Kwon D" first="Donghyok" last="Kwon">Donghyok Kwon</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Hur, Young Joo" sort="Hur, Young Joo" uniqKey="Hur Y" first="Young Joo" last="Hur">Young Joo Hur</name><affiliation><nlm:aff id="AF0003"><institution>Center for Infectious Disease Control, Korea Centers for Disease Control and Prevention</institution>,<addr-line>Cheongju</addr-line>,</nlm:aff></affiliation></author><author><name sortKey="Choi, Boyoul" sort="Choi, Boyoul" uniqKey="Choi B" first="Boyoul" last="Choi">Boyoul Choi</name><affiliation><nlm:aff wicri:cut=", and" id="AF0004"><institution>Department of Preventive Medicine, Hanyang University Medical College</institution>,<addr-line>Seoul</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ki, Moran" sort="Ki, Moran" uniqKey="Ki M" first="Moran" last="Ki">Moran Ki</name><affiliation><nlm:aff id="AF0005"><institution>Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center</institution>,<addr-line>Goyang</addr-line>,<country>Republic of Korea</country></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">27940937</idno><idno type="pmc">7108049</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108049</idno><idno type="RBID">PMC:7108049</idno><idno type="doi">10.1093/cid/ciw768</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">000B78</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000B78</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea</title><author><name sortKey="Kim, Seung Woo" sort="Kim, Seung Woo" uniqKey="Kim S" first="Seung Woo" last="Kim">Seung Woo Kim</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Park, Jung Wan" sort="Park, Jung Wan" uniqKey="Park J" first="Jung Wan" last="Park">Jung Wan Park</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Jung, Hee Dong" sort="Jung, Hee Dong" uniqKey="Jung H" first="Hee-Dong" last="Jung">Hee-Dong Jung</name><affiliation><nlm:aff id="AF0002"><institution>Division of Respiratory Viruses, Center of Infectious Disease,</institution></nlm:aff></affiliation></author><author><name sortKey="Yang, Jeong Sun" sort="Yang, Jeong Sun" uniqKey="Yang J" first="Jeong-Sun" last="Yang">Jeong-Sun Yang</name><affiliation><nlm:aff id="AF0002"><institution>Division of Respiratory Viruses, Center of Infectious Disease,</institution></nlm:aff></affiliation></author><author><name sortKey="Park, Yong Shik" sort="Park, Yong Shik" uniqKey="Park Y" first="Yong-Shik" last="Park">Yong-Shik Park</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Lee, Changhwan" sort="Lee, Changhwan" uniqKey="Lee C" first="Changhwan" last="Lee">Changhwan Lee</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Kim, Kyung Min" sort="Kim, Kyung Min" uniqKey="Kim K" first="Kyung Min" last="Kim">Kyung Min Kim</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Lee, Keon Joo" sort="Lee, Keon Joo" uniqKey="Lee K" first="Keon-Joo" last="Lee">Keon-Joo Lee</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Kwon, Donghyok" sort="Kwon, Donghyok" uniqKey="Kwon D" first="Donghyok" last="Kwon">Donghyok Kwon</name><affiliation><nlm:aff id="AF0001"><institution>Division of Epidemic Intelligence Service,</institution></nlm:aff></affiliation></author><author><name sortKey="Hur, Young Joo" sort="Hur, Young Joo" uniqKey="Hur Y" first="Young Joo" last="Hur">Young Joo Hur</name><affiliation><nlm:aff id="AF0003"><institution>Center for Infectious Disease Control, Korea Centers for Disease Control and Prevention</institution>,<addr-line>Cheongju</addr-line>,</nlm:aff></affiliation></author><author><name sortKey="Choi, Boyoul" sort="Choi, Boyoul" uniqKey="Choi B" first="Boyoul" last="Choi">Boyoul Choi</name><affiliation><nlm:aff wicri:cut=", and" id="AF0004"><institution>Department of Preventive Medicine, Hanyang University Medical College</institution>,<addr-line>Seoul</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ki, Moran" sort="Ki, Moran" uniqKey="Ki M" first="Moran" last="Ki">Moran Ki</name><affiliation><nlm:aff id="AF0005"><institution>Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center</institution>,<addr-line>Goyang</addr-line>,<country>Republic of Korea</country></nlm:aff></affiliation></author></analytic><series><title level="j">Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America</title><idno type="ISSN">1058-4838</idno><idno type="eISSN">1537-6591</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Summary</title><p>We evaluated the epidemiological risk factors for MERS-CoV transmission during the recent South Korean outbreak. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Clin Infect Dis</journal-id><journal-id journal-id-type="iso-abbrev">Clin. Infect. Dis</journal-id><journal-id journal-id-type="publisher-id">cid</journal-id><journal-title-group><journal-title>Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America</journal-title></journal-title-group><issn pub-type="ppub">1058-4838</issn><issn pub-type="epub">1537-6591</issn><publisher><publisher-name>Oxford University Press</publisher-name><publisher-loc>US</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">27940937</article-id><article-id pub-id-type="pmc">7108049</article-id><article-id pub-id-type="doi">10.1093/cid/ciw768</article-id><article-id pub-id-type="publisher-id">ciw768</article-id><article-categories><subj-group subj-group-type="heading"><subject>Major Article</subject></subj-group></article-categories><title-group><article-title>Risk Factors for Transmission of Middle East Respiratory Syndrome Coronavirus Infection During the 2015 Outbreak in South Korea</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kim</surname><given-names>Seung Woo</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Park</surname><given-names>Jung Wan</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Jung</surname><given-names>Hee-Dong</given-names></name><xref ref-type="aff" rid="AF0002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Yang</surname><given-names>Jeong-Sun</given-names></name><xref ref-type="aff" rid="AF0002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Park</surname><given-names>Yong-Shik</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Lee</surname><given-names>Changhwan</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kim</surname><given-names>Kyung Min</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Lee</surname><given-names>Keon-Joo</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kwon</surname><given-names>Donghyok</given-names></name><xref ref-type="aff" rid="AF0001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hur</surname><given-names>Young Joo</given-names></name><xref ref-type="aff" rid="AF0003"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Choi</surname><given-names>BoYoul</given-names></name><xref ref-type="aff" rid="AF0004"><sup>4</sup></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Ki</surname><given-names>Moran</given-names></name><xref ref-type="aff" rid="AF0005"><sup>5</sup></xref><pmc-comment>moranki@ncc.re.kr </pmc-comment>
</contrib></contrib-group><aff id="AF0001"><label>1</label><institution>Division of Epidemic Intelligence Service,</institution></aff><aff id="AF0002"><label>2</label><institution>Division of Respiratory Viruses, Center of Infectious Disease,</institution></aff><aff id="AF0003"><label>3</label><institution>Center for Infectious Disease Control, Korea Centers for Disease Control and Prevention</institution>,<addr-line>Cheongju</addr-line>,</aff><aff id="AF0004"><label>4</label><institution>Department of Preventive Medicine, Hanyang University Medical College</institution>,<addr-line>Seoul</addr-line>, and</aff><aff id="AF0005"><label>5</label><institution>Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center</institution>,<addr-line>Goyang</addr-line>,<country>Republic of Korea</country></aff><author-notes><fn id="fn-0002"><p>Correspondence: M. Ki, Department of Cancer Control and Policy, Graduate School of Cancer Science and Policy, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do 10408, Republic of Korea (<email>moranki@ncc.re.kr</email>).</p></fn></author-notes><pub-date pub-type="ppub"><day>01</day><month>3</month><year>2017</year></pub-date><pub-date pub-type="epub" iso-8601-date="2017-02-09"><day>09</day><month>2</month><year>2017</year></pub-date><volume>64</volume><issue>5</issue><fpage>551</fpage><lpage>557</lpage><history><date date-type="received"><day>29</day><month>8</month><year>2016</year></date><date date-type="rev-recd"><day>27</day><month>10</month><year>2016</year></date><date date-type="accepted"><day>30</day><month>11</month><year>2016</year></date></history><permissions><copyright-statement>© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.</copyright-statement><copyright-year>2017</copyright-year><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.</license-p></license></permissions><self-uri xlink:href="ciw768.pdf"></self-uri><abstract abstract-type="teaser"><title>Summary</title><p>We evaluated the epidemiological risk factors for MERS-CoV transmission during the recent South Korean outbreak. MERS-CoV transmission was determined by host infectivity and the number of contacts, whereas super-spreading events were determined by the number of contacts and hospital visits.</p></abstract><abstract><title>Abstract</title><sec><title>Background.</title><p>Transmission heterogeneity was observed during the 2015 Korean outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection. Only 22 of 186 cases transmitted the infection, and 5 super-spreading events caused 150 transmissions. We investigated the risk factors for MERS-CoV transmission.</p></sec><sec><title>Methods.</title><p>Epidemiological reports were used to classify patients as nonspreaders, spreaders, or those associated with a super-spreading event (5 or more transmissions). Logistic regression analyses were used to evaluate the factors for MERS-CoV transmission.</p></sec><sec><title>Results.</title><p>Compared to nonspreaders, spreaders exhibited a longer interval from symptom onset to isolation (7 days vs 3 days) and more frequent pre-isolation pneumonia diagnoses (68.2% vs 17.1%). Spreaders also exhibited higher values for pre-isolation contacts (149 vs 17.5), pre-isolation hospitalization (68.2% vs 16.5%), and emergency room (ER) visits (50% vs 7.3%). Spreaders exhibited lower cycle thresholds for the <italic>upE</italic> and <italic>ORF1a</italic> genes (22.7 vs 27.2 and 23.7 vs 27.9, respectively). In multivariate analysis, transmission was independently associated with the cycle threshold (odds ratio [OR], 0.84; 95% confidence interval [CI], 0.75–0.96) and pre-isolation hospitalization or ER visits (OR, 6.82; 95% CI, 2.06–22.84). The super-spreading events exhibited higher values for pre-isolation contacts (777 vs 78), pre-isolation ER visits (100% vs 35.3%), and doctor shopping (100% vs 47.1%) compared to non-super-spreading events.</p></sec><sec><title>Conclusions.</title><p>These findings indicate that transmission is determined by host infectivity and the number of contacts, whereas super-spreading events were determined by the number of contacts and hospital visits. These relationships highlight the importance of rapidly enforcing infection control measures to prevent outbreaks.</p></sec></abstract><kwd-group><kwd>epidemiology</kwd><kwd>South Korea</kwd><kwd>Middle East respiratory syndrome coronavirus</kwd><kwd>super-spreading event</kwd><kwd>transmission.</kwd></kwd-group><counts><page-count count="7"></page-count></counts></article-meta></front><body><p>Transmission heterogeneity was a significant characteristic of the 2015 South Korean outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection [<xref rid="CIT0001" ref-type="bibr">1</xref>]. Transmission heterogeneity describes a state in which most transmissions are related to a few patients and most patients do not transmit the disease. Numerous other infectious diseases exhibit transmission heterogeneity [<xref rid="CIT0002" ref-type="bibr">2</xref>], and this concept is important for understanding epidemics. The course of an epidemic is influenced by the basic reproduction number (R<sub>0</sub> = the average number of cases that 1 case produces in a susceptible population) and transmission heterogeneity [<xref rid="CIT0003" ref-type="bibr">3</xref>]. As R<sub>0</sub> represents an average quantity, it is often insufficient to explain individual variation, and as transmission heterogeneity reflects individual variation, it can help predict the likelihood of super-spreading events. Even in instances with a low R<sub>0</sub>, a disease with high transmission heterogeneity (eg, severe acute respiratory syndrome [SARS]) can cause super-spreading events [<xref rid="CIT0002" ref-type="bibr">2</xref>], such as the super-spreading that occurred during the 2003 SARS outbreak [<xref rid="CIT0002" ref-type="bibr">2</xref>, <xref rid="CIT0004" ref-type="bibr">4</xref>].</p><p>Transmission heterogeneity was observed during early MERS-CoV outbreaks [<xref rid="CIT0001" ref-type="bibr">1</xref>] and became prominent during the 2015 South Korean outbreak. Among the 186 confirmed Korean cases of MERS-CoV infection, >80% of the transmissions were epidemiologically associated with 5 patients [<xref rid="CIT0005" ref-type="bibr">5</xref>], and almost 90% of the cases caused no transmission. Furthermore, a recent study revealed that MERS has greater transmission heterogeneity compared to SARS [<xref rid="CIT0006" ref-type="bibr">6</xref>]. Therefore, to successfully control MERS-CoV infection, it is essential to identify high-risk patients and perform targeted infection control [<xref rid="CIT0002" ref-type="bibr">2</xref>]. However, these patients are difficult to identify, as an individual’s infectiousness is affected by complex interactions between the pathogen, host, and environment. Several researchers have attempted to identify risk factors for super-spreading events during the SARS outbreak [<xref rid="CIT0003" ref-type="bibr">3</xref>, <xref rid="CIT0004" ref-type="bibr">4</xref>, <xref rid="CIT0007" ref-type="bibr">7</xref>], although there is little information regarding the high-risk group(s) from the MERS-CoV outbreak.</p><p>The recent South Korean MERS-CoV outbreak was triggered by a single imported case, and epidemiological tracing was performed for all laboratory-confirmed cases and their close contacts [<xref rid="CIT0005" ref-type="bibr">5</xref>, <xref rid="CIT0008" ref-type="bibr">8–13</xref>]. Thus, it is possible to precisely reconstruct the transmission chain and identify patients who transmitted MERS-CoV infection. Therefore, we analyzed the epidemiological characteristics that were associated with MERS-CoV transmission and super-spreading events.</p><sec sec-type="methods" id="s1"><title>METHODS</title><sec id="s2"><title>Definitions</title><p>Cases of MERS-CoV infection were confirmed using real-time reverse-transcription polymerase chain reaction (RT-PCR) assays, regardless of their clinical manifestations. The epidemiological reports were analyzed by epidemic intelligence service officers who participated in the MERS-CoV outbreak investigation. When a case was exposed to multiple confirmed cases, the transmission was attributed to the case with the highest likelihood of transmission, and any conflicts were resolved through the consensus of the epidemic intelligence service officers. Spreaders were defined as confirmed cases of MERS-CoV infection that were epidemiologically suspected of transmitting MERS-CoV to 1 or more persons. Super-spreading events were arbitrarily defined as transmission of MERS-CoV infection to 5 or more cases. The patient who triggered the outbreak was defined as patient zero. Cases that were infected by patient zero were defined as first-generation cases; cases that were infected by first-generation cases were defined as second-generation cases; and cases that were infected by second-generation cases were defined as third-generation cases [<xref rid="CIT0014" ref-type="bibr">14</xref>]. Isolation was defined as separating symptomatic patients from others to prevent spreading, and quarantine was defined as separating or restricting the movement of healthy individuals who may have been exposed to the infection within the maximum incubation period. The transmission date was defined as the date of contact between the spreader and suspected secondary case during the spreader’s infectious period. In cases with an exposure duration of longer than 1 day, the transmission date was defined as the day with the highest likelihood of transmission or as the median day during the exposure period in cases with consistent contact throughout the exposure. The date of sampling was the day on which the first positive respiratory specimen was collected. Close contacts were defined using the Guidelines on Middle East Respiratory Syndrome [<xref rid="CIT0015" ref-type="bibr">15</xref>], which include persons who stayed in a room or ward with a confirmed case, who directly contacted respiratory secretions from confirmed cases, or who stayed within 2 m from the confirmed cases without wearing appropriate personal protective equipment. Pre-isolation pneumonia diagnoses were based on radiographic evidence. Doctor shopping was defined as visiting multiple healthcare facilities without an official interhospital transfer after developing MERS-CoV symptoms [<xref rid="CIT0016" ref-type="bibr">16</xref>].</p></sec><sec id="s3"><title>Data Collection</title><p>Epidemiological reports from the outbreak were evaluated to collect data regarding basic demographic characteristics, medical history, MERS-CoV exposure, symptoms and their onset date(s), sampling date(s), contact history, and post-exposure infection control. The reports were drafted during the outbreak based on direct interviews with the confirmed cases and follow-up epidemiological investigations that were performed to identify the exposure route and close contacts. Hospital information systems were reviewed to identify patients who stayed in the hospital during the exposure period and healthcare providers who contacted the patient(s). Persons who contacted confirmed cases outside healthcare facilities were also traced. Data from closed circuit television, credit card transactions, and health insurance services were also reviewed [<xref rid="CIT0005" ref-type="bibr">5</xref>]. The numbers of close contacts were calculated based on the number of quarantines during the outbreak. All data were collected as part of the public health response and in accordance with the Infectious Disease Control and Prevention Act [<xref rid="CIT0017" ref-type="bibr">17</xref>].</p></sec><sec id="s4"><title>Laboratory Confirmation</title><p>Clinical specimens were collected in sterile containers and immediately transferred to qualified facilities. Sputum samples were mixed with 0–1× phosphate-buffered saline and vortexed vigorously to reduce their viscosity. Viral RNA was extracted from the clinical specimens using a Qiagen viral RNA mini kit (Qiagen, Hilden, Germany). All laboratory diagnoses of MERS-CoV were confirmed using the World Health Organization guidelines [<xref rid="CIT0018" ref-type="bibr">18</xref>] and results from real-time RT-PCR assays that target upstream of the MERS-CoV envelope protein gene (<italic>upE</italic>) and the open reading frame 1a gene (<italic>ORF1a</italic>) [<xref rid="CIT0019" ref-type="bibr">19</xref>]. Cycle threshold (Ct) values for the <italic>upE</italic> and <italic>ORF1a</italic> genes were obtained during testing. We analyzed the Ct value from the first positive MERS-CoV specimen (or the specimen obtained immediately after a positive screening test).</p></sec><sec id="s5"><title>Statistical Analyses</title><p>Categorical variables were compared using the χ<sup>2</sup> test and Fisher exact test, and the Mann–Whitney test was used for continuous variables. The variables’ associations with MERS-CoV transmission were evaluated using multiple logistic regression analyses, and covariates were selected based on a <italic>P</italic> value of < .1 in the univariate analyses. A <italic>P</italic> value of < .05 was considered statistically significant. All analyses were performed using R software (version 3.2.2; R Foundation, Vienna, Austria).</p></sec></sec><sec id="s6"><title>RESULTS</title><sec id="s7"><title>Transmission Chain</title><p>We identified 186 cases of confirmed MERS-CoV infection. Patient zero infected 28 first-generation cases. Among the 28 cases, 8 were responsible for transmission to 121 second-generation cases. Among the 121 cases, 12 infected 30 third-generation cases. One patient with an unclear source of infection (case 119) transmitted the infection to another patient. Four patients exhibited unclear sources of transmission (cases 43, 178, 184, and 185). Each confirmed case transmitted the infection to 0–83 secondary cases (<xref ref-type="fig" rid="F1">Figure 1</xref>). There were 164 nonspreaders and 22 spreaders (1 or more transmission). Of the spreaders, 5 cases transmitted the infection to 5 or more cases (super-spreading event).</p><fig fig-type="figure" id="F1" orientation="portrait" position="float"><label>Figure 1.</label><caption><p>Transmission chain for the 186 laboratory-confirmed cases of Middle East respiratory syndrome coronavirus infection in South Korea during 2015. Figures in squares indicate the spreaders that transmitted the infection to 5 or more cases. One case with an unclear infection generation (case 119) transmitted the infection to an additional case. The source of infection was unclear in 4 additional cases (cases 43, 178, 184, and 185).</p></caption><graphic xlink:href="ciw76801"></graphic></fig></sec><sec id="s8"><title>The Spreaders’ Epidemiological Characteristics</title><p>After excluding the 5 cases with unclear infection sources, we identified 180 transmissions generated by 22 spreaders. A total of 150 transmission events (83.3%) were epidemiologically linked to the 5 super-spreading events. Twenty-five transmission events (13.9%) occurred within 3 days after symptom onset, 136 transmissions (75.6%) occurred 4–7 days after symptom onset, and 19 transmissions (10.6%) occurred >7 days after symptom onset. A total of 170 transmission events (94.4%) occurred on the day of or after a radiographically confirmed diagnosis of pneumonia. A total of 173 transmissions (96.1%) occurred before appropriate in-hospital isolation. Seven transmissions (3.9%) occurred between confirmed cases and healthcare personnel after in-hospital isolation: 4 (cases164, 169, 181, and 183) were doctors or nurses who managed confirmed cases, 1 (case148) participated in cardiopulmonary resuscitation of a confirmed case, 1 (case 162) involved portable radiography for a confirmed case, and 1 (case 179) rode in an ambulance with a confirmed case during a hospital transfer.</p></sec><sec id="s9"><title>Comparing the Spreaders and Nonspreaders</title><p><xref rid="T1" ref-type="table">Table 1</xref> shows the spreaders’ and nonspreaders’ epidemiological characteristics. These individuals exhibited similar values for age, sex, and presence of cough at symptom onset. However, spreaders exhibited significantly more frequent underlying respiratory disease (27.3% vs 11%; <italic>P</italic> = .044). The spreaders also had significantly lower Ct values (<italic>upE</italic>: median [interquartile range], 22.7 [19.5–29.1] vs 27.2 [23.5–30.4]; <italic>P</italic> = .004 and <italic>ORF1a</italic>: 23.7 [20.3–29.8] vs 27.9 [24.9–30.8]; <italic>P</italic> = .009). The intervals from symptom onset to diagnosis or obtaining a respiratory specimen were also significantly longer among spreaders (to diagnosis: 9 [5.5–10] days vs 5 [3–8] days; <italic>P</italic> = .008 and to sampling: 8 [5–9.3] days vs 4 [2–6] days; <italic>P</italic> < .001). Furthermore, the interval from symptom onset to isolation was longer among spreaders (7 [4.5–9] days vs 3 [1–6] days; <italic>P</italic> = .002). Spreaders exhibited a significantly higher proportion of pre-isolation pneumonia diagnoses (68.2% vs 17.1%; <italic>P</italic> < .001) and a longer interval from the pneumonia diagnosis to isolation (4 [3–7] days vs 1 [0–3] days; <italic>P</italic> = .008). The overall number of contacts was significantly larger among spreaders compared to nonspreaders (149 [22.3–640.5] vs 17.5 [2–92.5]; <italic>P</italic> = .004). Compared to nonspreaders, spreaders exhibited a significantly higher proportion for pre-isolation hospitalization (68.2% vs 16.5%; <italic>P</italic> < .001), visiting outpatient clinics (59.1% vs 33.5%; <italic>P</italic> = .019), and visiting emergency rooms (ERs; 50% vs 7.3%; <italic>P</italic> < .001).</p><table-wrap id="T1" orientation="portrait" position="float"><label>Table 1.</label><caption><p>Comparing the Demographic and Epidemiological Characteristics of Middle East Respiratory Syndrome Coronavirus Infection Spreaders and Nonspreaders During the 2015 South Korean Outbreak</p></caption><table frame="vsides" rules="groups"><thead><tr><th align="left" valign="bottom" rowspan="1" colspan="1">Variables, n (%) or median [interquartile range]</th><th align="center" valign="bottom" rowspan="1" colspan="1">Spreaders (n = 22)</th><th align="center" valign="bottom" rowspan="1" colspan="1">Nonspreaders (n = 164)</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic> Value</th></tr></thead><tbody><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Host factors</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Age, y</td><td align="center" rowspan="1" colspan="1">55.5 [35.0–67.0]</td><td align="center" rowspan="1" colspan="1">55 [42.5–66.0]</td><td align="char" char="." rowspan="1" colspan="1">.938</td></tr><tr><td align="left" rowspan="1" colspan="1">Sex, male</td><td align="center" rowspan="1" colspan="1">16 (72.7)</td><td align="center" rowspan="1" colspan="1">95 (57.9)</td><td align="char" char="." rowspan="1" colspan="1">.184</td></tr><tr><td align="left" rowspan="1" colspan="1">Case classification</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">.013<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Healthcare personnel</td><td align="center" rowspan="1" colspan="1">0 (0)</td><td align="center" rowspan="1" colspan="1">25 (15.2)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> Patients</td><td align="center" rowspan="1" colspan="1">9 (40.9)</td><td align="center" rowspan="1" colspan="1">74 (45.1)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> Family members</td><td align="center" rowspan="1" colspan="1">5 (22.7)</td><td align="center" rowspan="1" colspan="1">46 (28.0)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> Paid caregivers</td><td align="center" rowspan="1" colspan="1">2 (9.1)</td><td align="center" rowspan="1" colspan="1">7 (4.3)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> Others<xref ref-type="other" rid="fn-04"><sup>b</sup></xref></td><td align="center" rowspan="1" colspan="1">6 (27.3)</td><td align="center" rowspan="1" colspan="1">12 (7.3)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Stage of transmission<xref ref-type="other" rid="fn-05"><sup>c</sup></xref></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"><.001<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Patient zero</td><td align="center" rowspan="1" colspan="1">1 (4.8)</td><td align="center" rowspan="1" colspan="1">0 (0)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1st generation</td><td align="center" rowspan="1" colspan="1">8 (38.1)</td><td align="center" rowspan="1" colspan="1">20 (12.5)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 2nd generation</td><td align="center" rowspan="1" colspan="1">12 (57.1)</td><td align="center" rowspan="1" colspan="1">111 (69.4)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 3rd generation</td><td align="center" rowspan="1" colspan="1">0 (0)</td><td align="center" rowspan="1" colspan="1">29 (18.1)</td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Underlying respiratory disease<xref ref-type="other" rid="fn-06"><sup>d</sup></xref></td><td align="center" rowspan="1" colspan="1">6 (27.3)</td><td align="center" rowspan="1" colspan="1">18 (11.0)</td><td align="char" char="." rowspan="1" colspan="1">.044<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1">Cough at symptom onset</td><td align="center" rowspan="1" colspan="1">5 (22.7)</td><td align="center" rowspan="1" colspan="1">30 (18.3)</td><td align="char" char="." rowspan="1" colspan="1">.571<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" colspan="4" rowspan="1">Cycle threshold value (reverse transcription polymerase chain reaction)</td></tr><tr><td align="left" rowspan="1" colspan="1"> <italic>upE</italic></td><td align="center" rowspan="1" colspan="1">22.7 [19.5–29.1]</td><td align="center" rowspan="1" colspan="1">27.2 [23.5–30.4]</td><td align="char" char="." rowspan="1" colspan="1">.004</td></tr><tr><td align="left" rowspan="1" colspan="1"> <italic>ORF1a</italic></td><td align="center" rowspan="1" colspan="1">23.7 [20.3–29.8]</td><td align="center" rowspan="1" colspan="1">27.9 [24.9–30.8]</td><td align="char" char="." rowspan="1" colspan="1">.009</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Duration</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset to sampling, days</td><td align="center" rowspan="1" colspan="1">8 [5.0–9.3]</td><td align="center" rowspan="1" colspan="1">4 [2.0–6.0]</td><td align="char" char="." rowspan="1" colspan="1"><.001</td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset to diagnosis, days<xref ref-type="other" rid="fn-07"><sup>e</sup></xref></td><td align="center" rowspan="1" colspan="1">9 [5.5–10.0]</td><td align="center" rowspan="1" colspan="1">5 [3.0–8.0]</td><td align="char" char="." rowspan="1" colspan="1">.008</td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset before isolation<xref ref-type="other" rid="fn-07"><sup>e</sup></xref></td><td align="center" rowspan="1" colspan="1">21 (95.5)</td><td align="center" rowspan="1" colspan="1">124 (78.0)</td><td align="char" char="." rowspan="1" colspan="1">.083<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Onset to isolation, days</td><td align="center" rowspan="1" colspan="1">7 [4.5–9.0]</td><td align="center" rowspan="1" colspan="1">3 [1.0–6.0]</td><td align="char" char="." rowspan="1" colspan="1">.002</td></tr><tr><td align="left" rowspan="1" colspan="1">Diagnosis of pneumonia before isolation<xref ref-type="other" rid="fn-08"><sup>f</sup></xref></td><td align="center" rowspan="1" colspan="1">15 (68.2)</td><td align="center" rowspan="1" colspan="1">28 (17.1)</td><td align="char" char="." rowspan="1" colspan="1"><.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Pneumonia to isolation, days</td><td align="center" rowspan="1" colspan="1">4 [3.0–7.0]</td><td align="center" rowspan="1" colspan="1">1 [0–3.0]</td><td align="char" char="." rowspan="1" colspan="1">.008</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Contacts</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Contact with other persons before isolation</td><td align="center" rowspan="1" colspan="1">21 (95.5)</td><td align="center" rowspan="1" colspan="1">138 (84.1)</td><td align="char" char="." rowspan="1" colspan="1">.209<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Number of contacts</td><td align="center" rowspan="1" colspan="1">149 [22.3–640.5]</td><td align="center" rowspan="1" colspan="1">17.5 [2.0–92.5]</td><td align="char" char="." rowspan="1" colspan="1">.004</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Hospital visit before isolation</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Hospitalization</td><td align="center" rowspan="1" colspan="1">15 (68.2)</td><td align="center" rowspan="1" colspan="1">27 (16.5)</td><td align="char" char="." rowspan="1" colspan="1"><.001<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Duration of hospitalization, days</td><td align="center" rowspan="1" colspan="1">5 [4.0–8.0]</td><td align="center" rowspan="1" colspan="1">4 [2.0–7.0]</td><td align="char" char="." rowspan="1" colspan="1">.354</td></tr><tr><td align="left" rowspan="1" colspan="1">Outpatient clinic visit</td><td align="center" rowspan="1" colspan="1">13 (59.1)</td><td align="center" rowspan="1" colspan="1">55 (33.5)</td><td align="char" char="." rowspan="1" colspan="1">.019</td></tr><tr><td align="left" rowspan="1" colspan="1"> Frequency of visits</td><td align="center" rowspan="1" colspan="1">2 [1.0–2.0]</td><td align="center" rowspan="1" colspan="1">2 [1.0–3.0]</td><td align="char" char="." rowspan="1" colspan="1">.472</td></tr><tr><td align="left" rowspan="1" colspan="1">ER visit</td><td align="center" rowspan="1" colspan="1">11 (50.0)</td><td align="center" rowspan="1" colspan="1">12 (7.3)</td><td align="char" char="." rowspan="1" colspan="1"><.001<xref ref-type="other" rid="fn-03"><sup>a</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Frequency of visits</td><td align="center" rowspan="1" colspan="1">2 [1.0–2.0]</td><td align="center" rowspan="1" colspan="1">1.5 [1.0–2.0]</td><td align="char" char="." rowspan="1" colspan="1">.499</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of hospitals visited</td><td align="center" rowspan="1" colspan="1">2 [1.0–2.3]</td><td align="center" rowspan="1" colspan="1">0 [0–1.0]</td><td align="char" char="." rowspan="1" colspan="1"><.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> For hospitalization or ER visit</td><td align="center" rowspan="1" colspan="1">1 [0–2.0]</td><td align="center" rowspan="1" colspan="1">0 [0–0]</td><td align="char" char="." rowspan="1" colspan="1"><.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> For outpatient clinic visit</td><td align="center" rowspan="1" colspan="1">1 [1.0–2.0]</td><td align="center" rowspan="1" colspan="1">1 [1.0–2.0]</td><td align="char" char="." rowspan="1" colspan="1">.364</td></tr></tbody></table><table-wrap-foot><fn id="fn-01" fn-type="other"><p><italic>P</italic> values were obtained using the chi-square test or Fisher’s exact test for categorical variables, and the Mann-Whitney test for continuous variables.</p></fn><fn id="fn-02" fn-type="other"><p>Abbreviation: ER, emergency room.</p></fn><fn id="fn-03" fn-type="other"><label>a</label><p>Fisher exact test.</p></fn><fn id="fn-04" fn-type="other"><label>b</label><p>Includes hospital security agents in the emergency department, emergency medical technicians, visitors, police officers, and hospital office workers.</p></fn><fn id="fn-05" fn-type="other"><label>c</label><p>Excludes 5 cases with unclear stages of transmission.</p></fn><fn id="fn-06" fn-type="other"><label>d</label><p>Includes chronic obstructive pulmonary disease, asthma, pulmonary tuberculosis, and pneumonia before the exposure to Middle East respiratory syndrome coronavirus.</p></fn><fn id="fn-07" fn-type="other"><label>e</label><p>Excludes 5 cases with unclear symptom onset dates.</p></fn><fn id="fn-08" fn-type="other"><label>f</label><p>Cases with radiographic evidence of pneumonia before their isolation.</p></fn></table-wrap-foot></table-wrap><p>We used logistic regression analyses to evaluate the risk factors for transmission (<xref rid="T2" ref-type="table">Table 2</xref>). In the univariate analyses, transmission was associated with underlying respiratory disease, Ct value, interval from symptom onset to diagnosis, number of contacts, and pre-isolation hospitalization or ER visits. In the multivariate analyses, transmission was independently associated with a low Ct value for <italic>upE</italic> (odds ratio [OR], 0.84; 95% confidence interval [CI], 0.75–0.96) and pre-isolation hospitalization or ER visits (OR, 6.82; 95% CI, 2.06–22.84).</p><table-wrap id="T2" orientation="portrait" position="float"><label>Table 2.</label><caption><p>Epidemiological Factors Associated With Middle East Respiratory Syndrome Coronavirus Transmission During the 2015 South Korean Outbreak</p></caption><table frame="vsides" rules="groups"><thead><tr><th valign="bottom" rowspan="2" colspan="1">Variable (reference)</th><th align="center" valign="bottom" colspan="3" rowspan="1">Univariate Logistic Regression</th><th align="center" valign="bottom" colspan="3" rowspan="1">Multivariate Logistic Regression</th></tr><tr><th align="center" valign="bottom" rowspan="1" colspan="1">OR</th><th align="center" valign="bottom" rowspan="1" colspan="1">95% CI</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic> Value</th><th align="center" valign="bottom" rowspan="1" colspan="1">OR</th><th align="center" valign="bottom" rowspan="1" colspan="1">95% CI</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic> Value</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Underlying respiratory disease (no)</td><td align="char" char="." rowspan="1" colspan="1">3.04</td><td align="char" char="." rowspan="1" colspan="1">1.06–8.76</td><td align="char" char="." rowspan="1" colspan="1">.039</td><td align="char" char="." rowspan="1" colspan="1">3.02</td><td align="char" char="." rowspan="1" colspan="1">0.80–11.40</td><td align="char" char="." rowspan="1" colspan="1">.103</td></tr><tr><td align="left" rowspan="1" colspan="1">Cycle threshold value (<italic>upE</italic>)</td><td align="char" char="." rowspan="1" colspan="1">0.85</td><td align="char" char="." rowspan="1" colspan="1">0.76–0.94</td><td align="char" char="." rowspan="1" colspan="1">.002</td><td align="char" char="." rowspan="1" colspan="1">0.84</td><td align="char" char="." rowspan="1" colspan="1">0.75–0.96</td><td align="char" char="." rowspan="1" colspan="1">.007</td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset to diagnosis (days)</td><td align="char" char="." rowspan="1" colspan="1">1.13</td><td align="char" char="." rowspan="1" colspan="1">1.01–1.27</td><td align="char" char="." rowspan="1" colspan="1">.031</td><td align="char" char="." rowspan="1" colspan="1">1.02</td><td align="char" char="." rowspan="1" colspan="1">0.87–1.18</td><td align="char" char="." rowspan="1" colspan="1">.846</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of contacts (<10)</td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">.004</td><td align="char" char="." rowspan="1" colspan="1">1.49</td><td align="char" char="." rowspan="1" colspan="1">0.75–2.97</td><td align="char" char="." rowspan="1" colspan="1">.260</td></tr><tr><td align="left" rowspan="1" colspan="1"> 10–99</td><td align="char" char="." rowspan="1" colspan="1">1.03</td><td align="char" char="." rowspan="1" colspan="1">0.27–4.03</td><td align="char" char="." rowspan="1" colspan="1">.963</td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥100</td><td align="char" char="." rowspan="1" colspan="1">4.86</td><td align="char" char="." rowspan="1" colspan="1">1.61–14.65</td><td align="char" char="." rowspan="1" colspan="1">.005</td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Hospitalization or emergency room visit before isolation (no)</td><td align="char" char="." rowspan="1" colspan="1">10.59</td><td align="char" char="." rowspan="1" colspan="1">3.84–29.15</td><td align="char" char="." rowspan="1" colspan="1"><.001</td><td align="char" char="." rowspan="1" colspan="1">6.82</td><td align="char" char="." rowspan="1" colspan="1">2.06–22.84</td><td align="char" char="." rowspan="1" colspan="1">.002</td></tr></tbody></table><table-wrap-foot><fn id="fn-09" fn-type="other"><p>There was no multicollinearity between the independent variables (all variables: R score of <0.5).</p></fn><fn id="fn-10" fn-type="other"><p>Abbreviations: CI, confidence interval; OR, odds ratio.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s10"><title>Comparing the Spreaders With 5 or More Transmissions and Spreaders With 4 or Fewer Transmissions</title><p>We compared the epidemiological characteristics of the 5 spreaders with 5 or more transmissions and the 17 spreaders with 4 or fewer transmissions (<xref rid="T3" ref-type="table">Table 3</xref>). Both groups exhibited similar host factors and contact durations. However, spreaders with 5 or more transmissions exhibited higher values for pre-isolation contacts (777 [459.5–862] vs 78 [8.5–281.5]; <italic>P</italic> = .017), pre-isolation ER visits (100% vs 35.3%; <italic>P</italic> = .035), and the number of healthcare facilities that each patient visited for hospitalization or ER treatment (2 [2.0–2.5] vs 1 [0–1.5]; <italic>P</italic> = .009). In addition, super-spreading events were marginally associated with doctor shopping (100% vs 47.1%; <italic>P</italic> = .054).</p><table-wrap id="T3" orientation="portrait" position="float"><label>Table 3.</label><caption><p>Comparison of the Epidemiological Characteristics of Spreaders With 5 or More Cases and Spreaders With 4 or Fewer Cases</p></caption><table frame="vsides" rules="groups"><thead><tr><th valign="bottom" rowspan="1" colspan="1">Variables, n (%) or Median [interquartile range]</th><th align="center" valign="bottom" rowspan="1" colspan="1">Spreaders With 5 or More Cases (n = 5)</th><th align="center" valign="bottom" rowspan="1" colspan="1">Spreaders With 4 or Fewer cases (n = 17)</th><th align="center" valign="bottom" rowspan="1" colspan="1"><italic>P</italic> Value</th></tr></thead><tbody><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Host factors</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Underlying respiratory disease<xref ref-type="other" rid="fn-13"><sup>a</sup></xref></td><td align="center" rowspan="1" colspan="1">2 (40)</td><td align="center" rowspan="1" colspan="1">4 (23.5)</td><td align="char" char="." rowspan="1" colspan="1">.585<xref ref-type="other" rid="fn-14"><sup>b</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1">Cough at symptom onset</td><td align="center" rowspan="1" colspan="1">3 (60)</td><td align="center" rowspan="1" colspan="1">2 (11.8)</td><td align="char" char="." rowspan="1" colspan="1">.055<xref ref-type="other" rid="fn-14"><sup>b</sup></xref></td></tr><tr><td align="left" colspan="4" rowspan="1">Cycle threshold value (reverse transcription polymerase chain reaction)</td></tr><tr><td align="left" rowspan="1" colspan="1"> <italic>upE</italic></td><td align="center" rowspan="1" colspan="1">22.2 [17.4–29.9]</td><td align="center" rowspan="1" colspan="1">22.8 [20.7–26.9]</td><td align="char" char="." rowspan="1" colspan="1">.820</td></tr><tr><td align="left" rowspan="1" colspan="1"> <italic>ORF1a</italic></td><td align="center" rowspan="1" colspan="1">23.2 [18.2–32.2]</td><td align="center" rowspan="1" colspan="1">23.9 [21.3–28.1]</td><td align="char" char="." rowspan="1" colspan="1">.880</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Duration</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset to sampling, days</td><td align="center" rowspan="1" colspan="1">9 [4.5–10.5]</td><td align="center" rowspan="1" colspan="1">6 [5.0–8.5]</td><td align="char" char="." rowspan="1" colspan="1">.284</td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset to diagnosis, days</td><td align="center" rowspan="1" colspan="1">9 [5.5–11]</td><td align="center" rowspan="1" colspan="1">8 [5.0–9.5]</td><td align="char" char="." rowspan="1" colspan="1">.320</td></tr><tr><td align="left" rowspan="1" colspan="1">Symptom onset before isolation</td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">16 (94.1)</td><td align="char" char="." rowspan="1" colspan="1">1<xref ref-type="other" rid="fn-14"><sup>b</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Onset to isolation, days</td><td align="center" rowspan="1" colspan="1">8 [4.0–9.5]</td><td align="center" rowspan="1" colspan="1">6.5 [4.3–8.8]</td><td align="char" char="." rowspan="1" colspan="1">.453</td></tr><tr><td align="left" rowspan="1" colspan="1">Diagnosis of pneumonia before isolation<xref ref-type="other" rid="fn-15"><sup>c</sup></xref></td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">10 (58.8)</td><td align="char" char="." rowspan="1" colspan="1">.135<xref ref-type="other" rid="fn-14"><sup>b</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Pneumonia to isolation, days</td><td align="center" rowspan="1" colspan="1">5 [2.0–8.0]</td><td align="center" rowspan="1" colspan="1">3.5 [2.3–6.3]</td><td align="char" char="." rowspan="1" colspan="1">.419</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Contacts</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Contact with other persons before isolation</td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">16 (94.1)</td><td align="char" char="." rowspan="1" colspan="1">1<xref ref-type="other" rid="fn-14"><sup>b</sup></xref></td></tr><tr><td align="left" rowspan="1" colspan="1"> Number of contacts</td><td align="center" rowspan="1" colspan="1">777 [459.5–862]</td><td align="center" rowspan="1" colspan="1">78 [8.5–281.5]</td><td align="char" char="." rowspan="1" colspan="1">.017</td></tr><tr><td align="left" colspan="4" rowspan="1"><bold><italic>Hospital visit before isolation</italic></bold></td></tr><tr><td align="left" rowspan="1" colspan="1">Hospitalization</td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">10 (58.8)</td><td align="char" char="." rowspan="1" colspan="1">.135<sup>b</sup></td></tr><tr><td align="left" rowspan="1" colspan="1"> Duration of hospitalization, days</td><td align="center" rowspan="1" colspan="1">5 [2.5–9]</td><td align="center" rowspan="1" colspan="1">4.5 [3.5–8.3]</td><td align="char" char="." rowspan="1" colspan="1">.852</td></tr><tr><td align="left" rowspan="1" colspan="1">Outpatient clinic visit</td><td align="center" rowspan="1" colspan="1">3 (60)</td><td align="center" rowspan="1" colspan="1">10 (58.8)</td><td align="char" char="." rowspan="1" colspan="1">1<sup>b</sup></td></tr><tr><td align="left" rowspan="1" colspan="1">ER visit</td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">6 (35.3)</td><td align="char" char="." rowspan="1" colspan="1">.035<sup>b</sup></td></tr><tr><td align="left" rowspan="1" colspan="1"> Frequency of visits</td><td align="center" rowspan="1" colspan="1">2 [2–2.5]</td><td align="center" rowspan="1" colspan="1">1.5 [1.0–2.0]</td><td align="char" char="." rowspan="1" colspan="1">.054</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of hospitals visited</td><td align="center" rowspan="1" colspan="1">2 [2.0–3.5]</td><td align="center" rowspan="1" colspan="1">1 [1.0–2.0]</td><td align="char" char="." rowspan="1" colspan="1">.055</td></tr><tr><td align="left" rowspan="1" colspan="1"> For hospitalization or ER visit</td><td align="center" rowspan="1" colspan="1">2 [2.0–2.5]</td><td align="center" rowspan="1" colspan="1">1 [0–1.5]</td><td align="char" char="." rowspan="1" colspan="1">.009</td></tr><tr><td align="left" rowspan="1" colspan="1"> For outpatient clinic visit</td><td align="center" rowspan="1" colspan="1">1 [0–1.5]</td><td align="center" rowspan="1" colspan="1">1 [0–1.0]</td><td align="char" char="." rowspan="1" colspan="1">.966</td></tr><tr><td align="left" rowspan="1" colspan="1">Doctor shopping</td><td align="center" rowspan="1" colspan="1">5 (100)</td><td align="center" rowspan="1" colspan="1">8 (47.1)</td><td align="char" char="." rowspan="1" colspan="1">.054<sup>b</sup></td></tr></tbody></table><table-wrap-foot><fn id="fn-11" fn-type="other"><p><italic>P</italic> values were obtained using the χ<sup>2</sup> test or Fisher exact test for categorical variables, and the Mann–Whitney test for continuous variables.</p></fn><fn id="fn-12" fn-type="other"><p>Abbreviation: ER, emergency room.</p></fn><fn id="fn-13" fn-type="other"><label>a</label><p>Includes chronic obstructive pulmonary disease, asthma, pulmonary tuberculosis, and pneumonia before the exposure to Middle East respiratory syndrome coronavirus.</p></fn><fn id="fn-14" fn-type="other"><label>b</label><p>Fisher exact test.</p></fn><fn id="fn-15" fn-type="other"><label>c</label><p>Cases with radiographic evidence of pneumonia before their isolation.</p></fn></table-wrap-foot></table-wrap></sec></sec><sec id="s11"><title>DISCUSSION</title><p>We evaluated the epidemiological characteristics of patients who transmitted MERS-CoV during the recent South Korean outbreak. Among the 186 confirmed MERS-CoV cases, only 22 cases transmitted the infection to other individuals. These spreaders had higher host infectivity and wider and prolonged contacts compared to nonspreaders. The risk factors for super-spreading events included a larger number of contacts and a pre-isolation ER visit. Doctor shopping was marginally associated with a super-spreading event. However, both spreaders with 5 or more transmissions and spreaders with 4 or fewer transmissions exhibited similar levels of host infectivity. It appears that both host infectivity and the number of contacts influenced MERS-CoV transmission, whereas super-spreading events were mostly associated with a greater likelihood of encountering other people under diverse environmental conditions.</p><p>During the 2015 outbreak, approximately 75% of the transmissions occurred during days 4–7 after symptom onset, and this may be a period when the risk of transmission is particularly high. Furthermore, this high-risk period was temporally associated with other epidemiological factors. First, the period overlapped with the confirmed cases’ visits to healthcare facilities, as hospitalization and ER visits peaked during days 4–7 after symptom onset. It is well known that MERS-CoV outbreaks generally occur in the healthcare setting [<xref rid="CIT0001" ref-type="bibr">1</xref>, <xref rid="CIT0005" ref-type="bibr">5</xref>, <xref rid="CIT0013" ref-type="bibr">13</xref>, <xref rid="CIT0020" ref-type="bibr">20</xref>], and the high-risk period may be associated with healthcare-seeking behaviors. Second, the high-risk period was several days (1–4 days) after the radiographic diagnoses of pneumonia, which generally occurred on days 3–4 after symptom onset. Although the significance of pre-isolation pneumonia has not been discussed previously, a radiographic diagnosis of pneumonia may influence transmission in 2 ways. First, it may directly increase the chance of transmission by actively generating lower respiratory tract secretions and a productive cough. Second, it may be an indirect index of disease severity and hospital visiting status. In our study, cases with pre-isolation pneumonia had lower Ct values and more frequent pre-isolation hospital visits.</p><p>The epidemiological significance of the high-risk period could also be observed when we compared the spreaders and nonspreaders. The spreaders were typically isolated after the high-risk period (median, 7 days after symptom onset and 4 days after a diagnosis of pneumonia), whereas nonspreaders were typically isolated before this period (median, 3 days after symptom onset and 1 day after a diagnosis of pneumonia). Similar results were observed in a study of the SARS outbreak, which revealed that late admission to healthcare facilities (especially >4 days after symptom onset) was associated with super-spreading events [<xref rid="CIT0021" ref-type="bibr">21</xref>]. Thus, infection prevention measures should target isolation before this critical period (ie, within 4–7 days after symptom onset and within 1 day after the detection of pneumonia). Interestingly, the average duration from symptom onset to isolation dropped to <4 days during the first week of June 2015, and reports of new cases have rapidly decreased since that time.</p><p>Among the host factors that were associated with transmission, only the Ct value was statistically significant in the multivariate analyses. The Ct value is a semiquantitative continuous variable that is inversely proportional to the viral load. Ct values are associated with the severity of MERS-CoV infection [<xref rid="CIT0022" ref-type="bibr">22</xref>], although its relationship with transmission has rarely been studied. In the present study, spreaders had significantly lower Ct values compared to nonspreaders, which suggests that Ct values might reliably predict transmission. Moreover, the cases with very low Ct values (Ct <23) tended to transmit the infection in uncommon circumstances. In both the present study and previous studies, MERS-CoV transmission usually occurred in the hospital setting [<xref rid="CIT0001" ref-type="bibr">1</xref>, <xref rid="CIT0011" ref-type="bibr">11</xref>, <xref rid="CIT0013" ref-type="bibr">13</xref>, <xref rid="CIT0023" ref-type="bibr">23</xref>]. In contrast, cases with very low Ct values transmitted the infection in more diverse settings in the present outbreak (eg, their household, in an ambulance, in an outpatient clinic, or to healthcare personnel after in-hospital isolation). These findings suggest that cases with very low Ct values can potentially transmit the infection in unexpected conditions. However, our data regarding the Ct values have several limitations. First, various amounts of phosphate-buffered saline were added to dilute the respiratory specimens, and this may have affected the Ct values. Second, the Ct value is influenced by the specimen type and the interval between symptom onset and sample collection [<xref rid="CIT0022" ref-type="bibr">22</xref>, <xref rid="CIT0024" ref-type="bibr">24</xref>], but various different types of specimens were collected at different time points in the present study. However, we only evaluated 5 nonsputum specimens, and there was no linear correlation between the Ct values and the interval from onset to sampling.</p><p>Our comparison of the spreaders with 5 or more transmissions and spreaders with 4 or fewer transmissions revealed that the spreaders with 5 or more transmissions had an approximately 10-fold higher number of contacts. Furthermore, there were no significant differences in host infectivity. These findings may suggest that the underlying likelihood of transmission has the greatest influence on super-spreading events rather than an intrinsic difference in host infectivity. A similar finding was observed in a previous study of the SARS super-spreading event [<xref rid="CIT0004" ref-type="bibr">4</xref>], with those super-spreaders having 11–74 contacts compared to 1–4 contacts for the spreaders with 1–2 transmissions.</p><p>Our study also revealed that a pre-isolation ER visit and doctor shopping were associated with super-spreading events. In addition, super-spreading events were associated with the number of healthcare facilities that each patient visited for hospitalization or ER treatment but not with the number of hospitals visited for outpatient treatment. In South Korea, patients who seek hospitalization without prior arrangements tend to visit the ER, and a history of 2 or more ER visits strongly suggests that the patient had been doctor shopping during hospitalization. Specific environmental conditions have been suggested to increase the likelihood of a super-spreading event [<xref rid="CIT0003" ref-type="bibr">3</xref>], and doctor shopping may increase the likelihood of encountering these conditions. For example, when a confirmed case changes hospital during hospitalization without an official interhospital transfer, multiple environments are exposed to the infected case (an ambulance, an ER, and a ward). Thus, doctor shopping can greatly increase the likelihood of encountering conditions that are suitable for a super-spreading event. In the present outbreak, 4 of the 5 super spreaders (cases 1, 14, 16, and 76) transmitted the infection at 2 or more hospitals, as they had visited multiple healthcare facilities. Therefore, it is very important to have an early suspicion of MERS-CoV infection and minimize doctor shopping during the early stage of an outbreak.</p><p>Our study has several limitations. First, some of the confirmed cases had multiple potential sources of infection, and we attributed the transmission to the case with the highest epidemiological probability. The source of infection was clear in >95% of the transmissions, and we excluded 3 cases that had contact with multiple cases and an unclear source of transmission. However, as the analyses of the epidemiological data are ongoing, the list of spreaders may change if new epidemiological evidence is uncovered. Second, we did not have access to genomic sequencing data, which might have provided information regarding the relatedness of transmitted strains. Third, transmission may be affected by other epidemiological factors, including aerosol-generating procedures, differences in environmental conditions, and variations in crowdedness [<xref rid="CIT0003" ref-type="bibr">3</xref>, <xref rid="CIT0013" ref-type="bibr">13</xref>, <xref rid="CIT0025" ref-type="bibr">25</xref>]. However, these factors were not included in the present analysis. Fourth, serological testing was not performed for every close contact, and additional asymptomatic cases may have been present. However, the seropositive rate was 0.7% in a recent serological study of close contacts [<xref rid="CIT0026" ref-type="bibr">26</xref>]. Thus, the absence of serological testing likely did not significantly influence our results.</p><p>We evaluated the epidemiological risk factors for MERS-CoV transmission during the recent South Korean outbreak. Super-spreading events were not related to intrinsic host characteristics and were attributable to the likelihood of transmission. Therefore, strict ER triage and minimizing doctor shopping during an outbreak’s early stage may help prevent super-spreading events.</p></sec></body><back><notes id="n01"><title>Notes</title><p><bold><italic>Acknowledgments.</italic></bold> The authors thank Sung Soon Kim and Jeong-Gu Nam (Division of Respiratory Viruses, Center of Infectious Disease, Korea Centers for Disease Control and Prevention) for laboratory assistance and technical support in the production of the manuscript. In addition, we thank all administrative and laboratory staff of the Korea Centers for Disease Control and Prevention who participated in the MERS-CoV outbreak control effort</p><p><bold><italic>Author contributions.</italic></bold> S. W. K. performed the literature search, study design, data collection, analysis, interpretation, and writing. M. K. contributed to the study design, data interpretation, and writing. J. W. P., Y. S. P., C. L., K. M. K., K. J. L., and D. K. contributed to the data collection and interpretation. H. D. J. and J. S. Y. contributed to the data collection, MERS PCR testing, data interpretation, and analysis. Y. J. H. and B. Y. C. contributed to the study design, data interpretation, and revising the manuscript. S. W. K. and M. K. revised the manuscript. All authors contributed to writing and approved the final manuscript.</p><p><bold><italic>Potential conflicts of interest.</italic></bold>Authors certify no potential conflicts of interest. The authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. 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