Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015
Identifieur interne : 000094 ( Pmc/Curation ); précédent : 000093; suivant : 000095Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015
Auteurs : Sun Hee Park [Corée du Sud] ; Woo Joo Kim [Corée du Sud] ; Jin-Hong Yoo [Corée du Sud] ; Jung-Hyun Choi [Corée du Sud]Source :
- Infection & Chemotherapy [ 2093-2340 ] ; 2016.
Abstract
Epidemiologic parameters are important in planning infection control policies during the outbreak of emerging infections. Korea experienced an outbreak of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infection in 2015, which was characterized by superspreading events in healthcare settings. We aimed to estimate the epidemiologic parameters over time during the outbreak to assess the effectiveness of countermeasures.
Publicly available data pertaining to the MERS outbreak in Korea were collected. We estimated the incubation periods of 162 cases whose sources of exposure were identified and the temporal trend was evaluated. Factors influencing incubation duration were analyzed. The generational reproduction number (
The estimated median incubation period was 7.4 days (95% CI, 6.9-8.0). Median incubation periods tended to be longer over time as the disease generation progressed: 6.16 days (95% CI, 5.38-6.97), 7.68 days (95% CI, 7.04-8.44), and 7.95 days (95% CI, 6.25-9.88) in the first, second, and third generations, respectively. The number of days of illness in the source cases at the time of exposure inversely correlated with the incubation periods in the receiving cases (HR 0.91 [95% CI, 0.84-0.99] per one illness day increase;
Despite the initial delay, the stringent countermeasures targeted towards second generation cases appeared to effectively contain the MERS outbreak in Korea as suggested by the decline of
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DOI: 10.3947/ic.2016.48.2.108
PubMed: 27433381
PubMed Central: 4945720
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015</title><author><name sortKey="Park, Sun Hee" sort="Park, Sun Hee" uniqKey="Park S" first="Sun Hee" last="Park">Sun Hee Park</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Kim, Woo Joo" sort="Kim, Woo Joo" uniqKey="Kim W" first="Woo Joo" last="Kim">Woo Joo Kim</name><affiliation wicri:level="1"><nlm:aff id="A2">Division of Infectious Diseases, Department of Internal Medicine, Guro Hospital, Korea University College of Medicine, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, Guro Hospital, Korea University College of Medicine, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Yoo, Jin Hong" sort="Yoo, Jin Hong" uniqKey="Yoo J" first="Jin-Hong" last="Yoo">Jin-Hong Yoo</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Choi, Jung Hyun" sort="Choi, Jung Hyun" uniqKey="Choi J" first="Jung-Hyun" last="Choi">Jung-Hyun Choi</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">27433381</idno><idno type="pmc">4945720</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4945720</idno><idno type="RBID">PMC:4945720</idno><idno type="doi">10.3947/ic.2016.48.2.108</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">000094</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000094</idno><idno type="wicri:Area/Pmc/Curation">000094</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000094</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015</title><author><name sortKey="Park, Sun Hee" sort="Park, Sun Hee" uniqKey="Park S" first="Sun Hee" last="Park">Sun Hee Park</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Kim, Woo Joo" sort="Kim, Woo Joo" uniqKey="Kim W" first="Woo Joo" last="Kim">Woo Joo Kim</name><affiliation wicri:level="1"><nlm:aff id="A2">Division of Infectious Diseases, Department of Internal Medicine, Guro Hospital, Korea University College of Medicine, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, Guro Hospital, Korea University College of Medicine, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Yoo, Jin Hong" sort="Yoo, Jin Hong" uniqKey="Yoo J" first="Jin-Hong" last="Yoo">Jin-Hong Yoo</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author><author><name sortKey="Choi, Jung Hyun" sort="Choi, Jung Hyun" uniqKey="Choi J" first="Jung-Hyun" last="Choi">Jung-Hyun Choi</name><affiliation wicri:level="1"><nlm:aff id="A1">Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</nlm:aff><country xml:lang="fr" wicri:curation="lc">Corée du Sud</country><wicri:regionArea>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul</wicri:regionArea></affiliation></author></analytic><series><title level="j">Infection & Chemotherapy</title><idno type="ISSN">2093-2340</idno><idno type="eISSN">2092-6448</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Epidemiologic parameters are important in planning infection control policies during the outbreak of emerging infections. Korea experienced an outbreak of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infection in 2015, which was characterized by superspreading events in healthcare settings. We aimed to estimate the epidemiologic parameters over time during the outbreak to assess the effectiveness of countermeasures.</p></sec><sec><title>Materials and Methods</title><p>Publicly available data pertaining to the MERS outbreak in Korea were collected. We estimated the incubation periods of 162 cases whose sources of exposure were identified and the temporal trend was evaluated. Factors influencing incubation duration were analyzed. The generational reproduction number (<italic>R<sub>g</sub></italic>) and case reproduction number (<italic>R<sup>c</sup></italic>) were estimated over time.</p></sec><sec><title>Results</title><p>The estimated median incubation period was 7.4 days (95% CI, 6.9-8.0). Median incubation periods tended to be longer over time as the disease generation progressed: 6.16 days (95% CI, 5.38-6.97), 7.68 days (95% CI, 7.04-8.44), and 7.95 days (95% CI, 6.25-9.88) in the first, second, and third generations, respectively. The number of days of illness in the source cases at the time of exposure inversely correlated with the incubation periods in the receiving cases (HR 0.91 [95% CI, 0.84-0.99] per one illness day increase; <italic>P</italic>=0.026). This relationship was consistent (HR 0.83 [95% CI, 0.74-0.93] per one illness day increase) in the multivariable analysis incorporating clinical characteristics, the order of generation, and a link to superspreaders. Because the third generation cases were exposed to their source cases in the early stage (median one day) compared to the second generation cases (median 6 days), the temporal trend of incubation periods appears to be influenced by early isolation of symptomatic cases and reduction of potential exposure to source cases in the later stage. <italic>R<sub>g</sub></italic> declined rapidly from 28 to 0.23 in two generations. <italic>R<sup>c</sup></italic> dropped below the epidemic threshold at one on May 31, 2015, which approximately coincided with the initiation of the stringent countermeasures.</p></sec><sec><title>Conclusions</title><p>Despite the initial delay, the stringent countermeasures targeted towards second generation cases appeared to effectively contain the MERS outbreak in Korea as suggested by the decline of <italic>R<sup>c</sup></italic> shortly after implementation. Except for superspreading events, the transmission potential for MERS-CoV seems to be low. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Infect Chemother</journal-id><journal-id journal-id-type="iso-abbrev">Infect Chemother</journal-id><journal-id journal-id-type="publisher-id">IC</journal-id><journal-title-group><journal-title>Infection & Chemotherapy</journal-title></journal-title-group><issn pub-type="ppub">2093-2340</issn><issn pub-type="epub">2092-6448</issn><publisher><publisher-name>The Korean Society of Infectious Diseases and Korean Society for Chemotherapy</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">27433381</article-id><article-id pub-id-type="pmc">4945720</article-id><article-id pub-id-type="doi">10.3947/ic.2016.48.2.108</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Article</subject></subj-group></article-categories><title-group><article-title>Epidemiologic Parameters of the Middle East Respiratory Syndrome Outbreak in Korea, 2015</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid" authenticated="true">http://orcid.org/0000-0001-5648-9237</contrib-id><name><surname>Park</surname><given-names>Sun Hee</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">http://orcid.org/0000-0002-4546-3880</contrib-id><name><surname>Kim</surname><given-names>Woo Joo</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Yoo</surname><given-names>Jin-Hong</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><name><surname>Choi</surname><given-names>Jung-Hyun</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib></contrib-group><aff id="A1"><label>1</label>Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.</aff><aff id="A2"><label>2</label>Division of Infectious Diseases, Department of Internal Medicine, Guro Hospital, Korea University College of Medicine, Seoul, Korea.</aff><author-notes><corresp>Corresponding Author: Sun Hee Park, MD, PhD, MPH. Division of Infectious Diseases, Department of Internal Medicine, Daejeon St Mary's Hospital, College of Medicine, The Catholic University of Korea, 64, Daeheung-ro, Jung-gu, Daejeon 34943, Korea. Tel: +82-42-220-9296, Fax: +82-42-220-7925, <email>sph0103@gmail.com</email></corresp></author-notes><pub-date pub-type="ppub"><month>6</month><year>2016</year></pub-date><pub-date pub-type="epub"><day>30</day><month>6</month><year>2016</year></pub-date><volume>48</volume><issue>2</issue><fpage>108</fpage><lpage>117</lpage><history><date date-type="received"><day>23</day><month>4</month><year>2016</year></date><date date-type="rev-recd"><day>04</day><month>6</month><year>2016</year></date><date date-type="accepted"><day>07</day><month>6</month><year>2016</year></date></history><permissions><copyright-statement>Copyright © 2016 by The Korean Society of Infectious Diseases and Korean Society for Chemotherapy</copyright-statement><copyright-year>2016</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/3.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/3.0/">http://creativecommons.org/licenses/by-nc/3.0/</ext-link>) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><sec><title>Background</title><p>Epidemiologic parameters are important in planning infection control policies during the outbreak of emerging infections. Korea experienced an outbreak of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infection in 2015, which was characterized by superspreading events in healthcare settings. We aimed to estimate the epidemiologic parameters over time during the outbreak to assess the effectiveness of countermeasures.</p></sec><sec><title>Materials and Methods</title><p>Publicly available data pertaining to the MERS outbreak in Korea were collected. We estimated the incubation periods of 162 cases whose sources of exposure were identified and the temporal trend was evaluated. Factors influencing incubation duration were analyzed. The generational reproduction number (<italic>R<sub>g</sub></italic>) and case reproduction number (<italic>R<sup>c</sup></italic>) were estimated over time.</p></sec><sec><title>Results</title><p>The estimated median incubation period was 7.4 days (95% CI, 6.9-8.0). Median incubation periods tended to be longer over time as the disease generation progressed: 6.16 days (95% CI, 5.38-6.97), 7.68 days (95% CI, 7.04-8.44), and 7.95 days (95% CI, 6.25-9.88) in the first, second, and third generations, respectively. The number of days of illness in the source cases at the time of exposure inversely correlated with the incubation periods in the receiving cases (HR 0.91 [95% CI, 0.84-0.99] per one illness day increase; <italic>P</italic>=0.026). This relationship was consistent (HR 0.83 [95% CI, 0.74-0.93] per one illness day increase) in the multivariable analysis incorporating clinical characteristics, the order of generation, and a link to superspreaders. Because the third generation cases were exposed to their source cases in the early stage (median one day) compared to the second generation cases (median 6 days), the temporal trend of incubation periods appears to be influenced by early isolation of symptomatic cases and reduction of potential exposure to source cases in the later stage. <italic>R<sub>g</sub></italic> declined rapidly from 28 to 0.23 in two generations. <italic>R<sup>c</sup></italic> dropped below the epidemic threshold at one on May 31, 2015, which approximately coincided with the initiation of the stringent countermeasures.</p></sec><sec><title>Conclusions</title><p>Despite the initial delay, the stringent countermeasures targeted towards second generation cases appeared to effectively contain the MERS outbreak in Korea as suggested by the decline of <italic>R<sup>c</sup></italic> shortly after implementation. Except for superspreading events, the transmission potential for MERS-CoV seems to be low. Further research should be focused on characterizing superspreaders in comparison to non-transmitting cases with regard to environmental, behavioral, and virologic and host genetic factors in order to better prepare for future outbreaks of MERS-CoV.</p></sec></abstract><kwd-group><kwd>Reproduction number</kwd><kwd>Incubation period</kwd><kwd>Middle East Respiratory Syndrome</kwd><kwd>Korea</kwd><kwd>Countermeasures</kwd></kwd-group></article-meta></front><floats-group><fig id="F1" orientation="portrait" position="float"><label>Figure 1</label><caption><title>The distribution of incubation periods (A) and serial intervals (B) in the Middle East respiratory syndrome outbreak in Korea in 2015.</title><p>The estimation included 162 cases with a single source of exposure for incubation periods and 153 cases with identified onset of symptoms for serial intervals. The fitted distributions are plotted against the empirical cumulative density function of observed incubation periods (midpoint of exposure to symptom onset) and serial intervals (black line). The 95% confidence intervals for the 5th, 50th, and 95th percentiles of these fitted distributions are also plotted. Bootstrapped estimates are in grey shading.</p></caption><graphic xlink:href="ic-48-108-g001"></graphic></fig><fig id="F2" orientation="portrait" position="float"><label>Figure 2</label><caption><title>The temporal trend of incubation periods (A), serial intervals (B) and time form symptom onset to confirmation (C) during the Middle East respiratory syndrome outbreak in Korea in 2015.</title><p>In the box plots, the box extends from the 25<sup>th</sup> to 75<sup>th</sup> percentile (interquartile range, IQR) of observations with the center line indicating the median. The bars define the upper (75<sup>th</sup> percentile + 1.5 IQR) and lower values (25<sup>th</sup> percentile-1.5IQR). In (C), the gray bars indicate the mean days from symptom onset to confirmation with standard errors.</p></caption><graphic xlink:href="ic-48-108-g002"></graphic></fig><fig id="F3" orientation="portrait" position="float"><label>Figure 3</label><caption><title>Differences in distributions of incubation periods according to the disease generation (A), a link to superspreaders (B), and days of illness in source cases (C).</title></caption><graphic xlink:href="ic-48-108-g003"></graphic></fig><fig id="F4" orientation="portrait" position="float"><label>Figure 4</label><caption><title>The epidemic curve of the Middle East respiratory syndrome outbreak in Korea in 2015 (A) and daily estimates of the case reproduction number <italic>R<sup>c</sup></italic> (B) and the instantaneous reproduction number <italic>R<sub>t</sub></italic> (C).</title><p><italic>R<sup>c</sup></italic> is depicted with 95% confidence intervals (vertical bars) where the grey region indicates R<sup>c</sup> below 1 (B). <italic>R<sub>t</sub></italic> is shown with 95% credible intervals in grey shading and a dotted line indicates <italic>R<sub>t</sub></italic> at 1(C).</p></caption><graphic xlink:href="ic-48-108-g004"></graphic></fig><table-wrap id="T1" orientation="portrait" position="float"><label>Table 1</label><caption><title>Demographic and clinical characteristics of confirmed cases according to the disease generation during the Middle East respiratory syndrome outbreak in Korea in 2015.</title></caption><alternatives><graphic xlink:href="ic-48-108-i001"></graphic><table frame="hsides" rules="rows"><col width="30.37%" span="1"></col><col width="18.69%" span="1"></col><col width="18.69%" span="1"></col><col width="18.69%" span="1"></col><col width="13.55%" span="1"></col><thead><tr><th valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></th><th valign="middle" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">1<sup>st</sup> generation (N = 28)</th><th valign="middle" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">2<sup>nd</sup> generation (N = 124)</th><th valign="middle" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">3<sup>rd</sup> generation (N = 29)</th><th valign="middle" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"><italic>P</italic>-value<sup>a</sup></th></tr></thead><tbody><tr><td valign="top" rowspan="1" colspan="1">Age, mean years (SD)</td><td valign="top" align="center" rowspan="1" colspan="1">52 (14.9)</td><td valign="top" align="center" rowspan="1" colspan="1">56.6 (16.0)</td><td valign="top" align="center" rowspan="1" colspan="1">48.4 (17.6)</td><td valign="top" align="right" rowspan="1" colspan="1">0.03</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">Gender</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.68</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> Male</td><td valign="top" align="center" rowspan="1" colspan="1">16 (57.1)</td><td valign="top" align="center" rowspan="1" colspan="1">75 (60.5)</td><td valign="top" align="center" rowspan="1" colspan="1">15 (51.7)</td><td valign="top" align="right" rowspan="1" colspan="1"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Female</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">12 (42.9)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">49 (39.5)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">14 (48.3)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Case classification</td><td valign="top" align="center" rowspan="1" colspan="1"></td><td valign="top" align="center" rowspan="1" colspan="1"></td><td valign="top" align="center" rowspan="1" colspan="1"></td><td valign="top" align="right" rowspan="1" colspan="1"><0.01</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Patient</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">13 (46.4)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">62 (50)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">8 (27.6)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> HCW</td><td valign="top" align="center" rowspan="1" colspan="1">4 (14.3)</td><td valign="top" align="center" rowspan="1" colspan="1">12 (9.7)</td><td valign="top" align="center" rowspan="1" colspan="1">15 (51.7)</td><td valign="top" align="right" rowspan="1" colspan="1"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Others<sup>b</sup></td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">11 (39.3)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">50 (40.3)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">6 (20.7)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Comorbid conditions</td><td valign="top" align="center" rowspan="1" colspan="1">17 (60.7)</td><td valign="top" align="center" rowspan="1" colspan="1">66 (53.2)</td><td valign="top" align="center" rowspan="1" colspan="1">10 (34.5)</td><td valign="top" align="right" rowspan="1" colspan="1">0.11</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Diabetes</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">5 (17.9)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">17 (13.7)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">2 (6.9)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.46</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> CKD</td><td valign="top" align="center" rowspan="1" colspan="1">1 (3.6)</td><td valign="top" align="center" rowspan="1" colspan="1">11 (8.9)</td><td valign="top" align="center" rowspan="1" colspan="1">1 (3.45)</td><td valign="top" align="right" rowspan="1" colspan="1">0.43</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Liver disease</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">3 (10.7)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">12 (9.7)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">1 (3.45)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.53</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> Malignancy</td><td valign="top" align="center" rowspan="1" colspan="1">4 (14.3)</td><td valign="top" align="center" rowspan="1" colspan="1">20 (16.1)</td><td valign="top" align="center" rowspan="1" colspan="1">3 (10.3)</td><td valign="top" align="right" rowspan="1" colspan="1">0.73</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> Lung disease</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">6 (21.4)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">18 (14.5)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">1 (3.45)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.13</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Case fatality</td><td valign="top" align="center" rowspan="1" colspan="1">4 (14.3)</td><td valign="top" align="center" rowspan="1" colspan="1">32 (25.8)</td><td valign="top" align="center" rowspan="1" colspan="1">2 (6.9)</td><td valign="top" align="right" rowspan="1" colspan="1">0.05</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">Link to superspreaders</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">28 (100)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">110 (88.7)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">11 (37.9)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"><0.01</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Number of identified source cases</td><td valign="top" align="center" rowspan="1" colspan="1">1</td><td valign="top" align="center" rowspan="1" colspan="1">5</td><td valign="top" align="center" rowspan="1" colspan="1">9</td><td valign="top" align="right" rowspan="1" colspan="1"></td></tr></tbody></table></alternatives><table-wrap-foot><fn><p>SD, standard deviation; HCW, healthcare workers; CKD, chronic kidney disease</p><p><sup>a</sup>For age, one-way ANOVA test was performed. For categorical variables, Chi-squared test for trend was performed; <sup>b</sup>Others included family members, visitors, and paid caregivers.</p></fn></table-wrap-foot></table-wrap><table-wrap id="T2" orientation="portrait" position="float"><label>Table 2</label><caption><title>Factors associated with the longer duration of incubation periods of Middle East respiratory syndrome-coronavirus infection in Korea</title></caption><alternatives><graphic xlink:href="ic-48-108-i002"></graphic><table frame="hsides" rules="rows"><col width="34.59%" span="1"></col><col width="18.59%" span="1"></col><col width="14.12%" span="1"></col><col width="18.59%" span="1"></col><col width="14.12%" span="1"></col><thead><tr><th valign="top" align="center" rowspan="2" colspan="1" style="background-color:rgb(228,222,238)"></th><th valign="top" align="center" rowspan="1" colspan="2" style="background-color:rgb(228,222,238)">Univariate Analysis</th><th valign="top" align="center" rowspan="1" colspan="2" style="background-color:rgb(228,222,238)">Multivariate Analysis</th></tr><tr><th valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">HR (95% CI)</th><th valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"><italic>P</italic>-value</th><th valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">HR (95% CI)</th><th valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"><italic>P</italic>-value</th></tr></thead><tbody><tr><td valign="top" align="left" rowspan="1" colspan="1">Age</td><td valign="top" align="left" rowspan="1" colspan="1">1.0 (0.99-1.01)</td><td valign="top" align="center" rowspan="1" colspan="1">0.617</td><td valign="top" align="left" rowspan="1" colspan="1">1.00 (0.98-1.00)</td><td valign="top" align="right" rowspan="1" colspan="1">0.525</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">Male</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.83 (0.61-1.16)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.285</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.91 (0.66-1.26)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.579</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Lung disease</td><td valign="top" align="left" rowspan="1" colspan="1">0.84 (0.54-1.32)</td><td valign="top" align="center" rowspan="1" colspan="1">0.453</td><td valign="top" align="left" rowspan="1" colspan="1">0.90 (0.56-1.43)</td><td valign="top" align="right" rowspan="1" colspan="1">0.644</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">Generation</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> 1<sup>st</sup> generation</td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="center" rowspan="1" colspan="1"></td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="right" rowspan="1" colspan="1"></td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"> 2<sup>nd</sup> generation</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">1.87 (12.2-2.87)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.004</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">2.36 (1.48-3.75)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)"><0.001</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1"> 3<sup>rd</sup> generation</td><td valign="top" align="left" rowspan="1" colspan="1">2.05 (1215-3.64)</td><td valign="top" align="center" rowspan="1" colspan="1">0.015</td><td valign="top" align="left" rowspan="1" colspan="1">0.93 (0.44-1.97)</td><td valign="top" align="right" rowspan="1" colspan="1">0.844</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">Link to superspreaders</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.64 (0.36-1.13)</td><td valign="top" align="center" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.127</td><td valign="top" align="left" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.55 (0.27-1.12)</td><td valign="top" align="right" rowspan="1" colspan="1" style="background-color:rgb(228,222,238)">0.097</td></tr><tr><td valign="top" align="left" rowspan="1" colspan="1">Days of illness in source cases<sup>a</sup></td><td valign="top" align="left" rowspan="1" colspan="1">0.91 (0.84-0.99)</td><td valign="top" align="center" rowspan="1" colspan="1">0.026</td><td valign="top" align="left" rowspan="1" colspan="1">0.83 (0.74-0.93)</td><td valign="top" align="right" rowspan="1" colspan="1">0.001</td></tr></tbody></table></alternatives><table-wrap-foot><fn><p>HR, hazard ratio; CI, confidence interval</p><p><sup>a</sup>Hazard ratio was estimated per 1 illness day increase.</p></fn></table-wrap-foot></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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