Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus
Identifieur interne : 000559 ( Pmc/Checkpoint ); précédent : 000558; suivant : 000560Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus
Auteurs : Oyelola Adegboye [Australie] ; Timor Saffary [États-Unis] ; Majeed Adegboye [Nigeria] ; Faiz Elfaki [Qatar]Source :
- Journal of Infection and Public Health [ 1876-0341 ] ; 2018.
Abstract
During outbreaks of infectious diseases, transmission of the pathogen can form networks of infected individuals connected either directly or indirectly.
Network centrality metrics were used to characterize hospital-acquired Middle East Respiratory Syndrome Coronavirus (HA-MERS) outbreaks in the Kingdom of Saudi Arabia between 2012 and 2016. Covariate-adjusted multivariable logistic regression models were applied to assess the effect of individual level risk factors and network level metrics associated with increase in length of hospital stay and risk of deaths from MERS.
About 27% of MERS cases were hospital acquired during the study period. The median age of healthcare workers and hospitalized patients were 35 years and 63 years, respectively, Although HA-MERS were more connected, we found no significant difference in degree centrality metrics between HA-MERS and non-HA-MERS cases. Pre-existing medical conditions (adjusted Odds ratio (aOR) = 2.43, 95% confidence interval: (CI) [1.11–5.33]) and hospitalized patients (aOR = 29.99, 95% CI [1.80–48.65]) were the strongest risk predictors of death from MERS. The risk of death associated with 1-day increased length of stay was significantly higher for patients with comorbidities.
Our investigation also revealed that patients with an HA-MERS infection experienced a significantly longer hospital stay and were more likely to die from the disease. Healthcare worker should be reminded of their potential role as hubs for pathogens because of their proximity to and regular interaction with infected patients. On the other hand, this study has shown that while healthcare workers acted as epidemic attenuators, hospitalized patients played the role of an epidemic amplifier.
Url:
DOI: 10.1016/j.jiph.2018.12.002
PubMed: 30578142
PubMed Central: 7102844
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus</title><author><name sortKey="Adegboye, Oyelola" sort="Adegboye, Oyelola" uniqKey="Adegboye O" first="Oyelola" last="Adegboye">Oyelola Adegboye</name><affiliation wicri:level="1"><nlm:aff id="aff0005">Australian Institute of Tropical Health & Medicine, James Cook University, Townsville, QLD 4811, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Australian Institute of Tropical Health & Medicine, James Cook University, Townsville, QLD 4811</wicri:regionArea><wicri:noRegion>QLD 4811</wicri:noRegion></affiliation></author><author><name sortKey="Saffary, Timor" sort="Saffary, Timor" uniqKey="Saffary T" first="Timor" last="Saffary">Timor Saffary</name><affiliation wicri:level="2"><nlm:aff id="aff0010">Independent Researcher, MD 20876, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Independent Researcher, MD 20876</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Adegboye, Majeed" sort="Adegboye, Majeed" uniqKey="Adegboye M" first="Majeed" last="Adegboye">Majeed Adegboye</name><affiliation wicri:level="1"><nlm:aff id="aff0015">American University of Nigeria, 640001 Yola, Nigeria</nlm:aff><country xml:lang="fr">Nigeria</country><wicri:regionArea>American University of Nigeria, 640001 Yola</wicri:regionArea><wicri:noRegion>640001 Yola</wicri:noRegion></affiliation></author><author><name sortKey="Elfaki, Faiz" sort="Elfaki, Faiz" uniqKey="Elfaki F" first="Faiz" last="Elfaki">Faiz Elfaki</name><affiliation wicri:level="1"><nlm:aff id="aff0020">Department of Mathematics, Statistics and Physics, Qatar University, 2713 Doha, Qatar</nlm:aff><country xml:lang="fr">Qatar</country><wicri:regionArea>Department of Mathematics, Statistics and Physics, Qatar University, 2713 Doha</wicri:regionArea><wicri:noRegion>2713 Doha</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30578142</idno><idno type="pmc">7102844</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102844</idno><idno type="RBID">PMC:7102844</idno><idno type="doi">10.1016/j.jiph.2018.12.002</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">000E47</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000E47</idno><idno type="wicri:Area/Pmc/Curation">000E47</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000E47</idno><idno type="wicri:Area/Pmc/Checkpoint">000559</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000559</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus</title><author><name sortKey="Adegboye, Oyelola" sort="Adegboye, Oyelola" uniqKey="Adegboye O" first="Oyelola" last="Adegboye">Oyelola Adegboye</name><affiliation wicri:level="1"><nlm:aff id="aff0005">Australian Institute of Tropical Health & Medicine, James Cook University, Townsville, QLD 4811, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Australian Institute of Tropical Health & Medicine, James Cook University, Townsville, QLD 4811</wicri:regionArea><wicri:noRegion>QLD 4811</wicri:noRegion></affiliation></author><author><name sortKey="Saffary, Timor" sort="Saffary, Timor" uniqKey="Saffary T" first="Timor" last="Saffary">Timor Saffary</name><affiliation wicri:level="2"><nlm:aff id="aff0010">Independent Researcher, MD 20876, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Independent Researcher, MD 20876</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Adegboye, Majeed" sort="Adegboye, Majeed" uniqKey="Adegboye M" first="Majeed" last="Adegboye">Majeed Adegboye</name><affiliation wicri:level="1"><nlm:aff id="aff0015">American University of Nigeria, 640001 Yola, Nigeria</nlm:aff><country xml:lang="fr">Nigeria</country><wicri:regionArea>American University of Nigeria, 640001 Yola</wicri:regionArea><wicri:noRegion>640001 Yola</wicri:noRegion></affiliation></author><author><name sortKey="Elfaki, Faiz" sort="Elfaki, Faiz" uniqKey="Elfaki F" first="Faiz" last="Elfaki">Faiz Elfaki</name><affiliation wicri:level="1"><nlm:aff id="aff0020">Department of Mathematics, Statistics and Physics, Qatar University, 2713 Doha, Qatar</nlm:aff><country xml:lang="fr">Qatar</country><wicri:regionArea>Department of Mathematics, Statistics and Physics, Qatar University, 2713 Doha</wicri:regionArea><wicri:noRegion>2713 Doha</wicri:noRegion></affiliation></author></analytic><series><title level="j">Journal of Infection and Public Health</title><idno type="ISSN">1876-0341</idno><idno type="eISSN">1876-035X</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>During outbreaks of infectious diseases, transmission of the pathogen can form networks of infected individuals connected either directly or indirectly.</p></sec><sec><title>Methods</title><p>Network centrality metrics were used to characterize hospital-acquired Middle East Respiratory Syndrome Coronavirus (HA-MERS) outbreaks in the Kingdom of Saudi Arabia between 2012 and 2016. Covariate-adjusted multivariable logistic regression models were applied to assess the effect of individual level risk factors and network level metrics associated with increase in length of hospital stay and risk of deaths from MERS.</p></sec><sec><title>Results</title><p>About 27% of MERS cases were hospital acquired during the study period. The median age of healthcare workers and hospitalized patients were 35 years and 63 years, respectively, Although HA-MERS were more connected, we found no significant difference in degree centrality metrics between HA-MERS and non-HA-MERS cases. Pre-existing medical conditions (adjusted Odds ratio (aOR) = 2.43, 95% confidence interval: (CI) [1.11–5.33]) and hospitalized patients (aOR = 29.99, 95% CI [1.80–48.65]) were the strongest risk predictors of death from MERS. The risk of death associated with 1-day increased length of stay was significantly higher for patients with comorbidities.</p></sec><sec><title>Conclusion</title><p>Our investigation also revealed that patients with an HA-MERS infection experienced a significantly longer hospital stay and were more likely to die from the disease. Healthcare worker should be reminded of their potential role as hubs for pathogens because of their proximity to and regular interaction with infected patients. On the other hand, this study has shown that while healthcare workers acted as epidemic attenuators, hospitalized patients played the role of an epidemic amplifier.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Chowell, G" uniqKey="Chowell G">G. Chowell</name></author><author><name sortKey="Abdirizak, F" uniqKey="Abdirizak F">F. Abdirizak</name></author><author><name sortKey="Lee, S" uniqKey="Lee S">S. 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Dick</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Christley, R M" uniqKey="Christley R">R.M. Christley</name></author><author><name sortKey="Pinchbeck, G" uniqKey="Pinchbeck G">G. Pinchbeck</name></author><author><name sortKey="Bowers, R" uniqKey="Bowers R">R. Bowers</name></author><author><name sortKey="Clancy, D" uniqKey="Clancy D">D. Clancy</name></author><author><name sortKey="French, N" uniqKey="French N">N. French</name></author><author><name sortKey="Bennett, R" uniqKey="Bennett R">R. Bennett</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Infect Public Health</journal-id><journal-id journal-id-type="iso-abbrev">J Infect Public Health</journal-id><journal-title-group><journal-title>Journal of Infection and Public Health</journal-title></journal-title-group><issn pub-type="ppub">1876-0341</issn><issn pub-type="epub">1876-035X</issn><publisher><publisher-name>Elsevier</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30578142</article-id><article-id pub-id-type="pmc">7102844</article-id><article-id pub-id-type="publisher-id">S1876-0341(18)30318-6</article-id><article-id pub-id-type="doi">10.1016/j.jiph.2018.12.002</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus</article-title></title-group><contrib-group><contrib contrib-type="author" id="aut0005"><name><surname>Adegboye</surname><given-names>Oyelola</given-names></name><email>oyelola.adegboye@jcu.edu.au</email><xref rid="aff0005" ref-type="aff">a</xref><xref rid="cor0005" ref-type="corresp">⁎</xref></contrib><contrib contrib-type="author" id="aut0010"><name><surname>Saffary</surname><given-names>Timor</given-names></name><xref rid="aff0010" ref-type="aff">b</xref></contrib><contrib contrib-type="author" id="aut0015"><name><surname>Adegboye</surname><given-names>Majeed</given-names></name><xref rid="aff0015" ref-type="aff">c</xref></contrib><contrib contrib-type="author" id="aut0020"><name><surname>Elfaki</surname><given-names>Faiz</given-names></name><xref rid="aff0020" ref-type="aff">d</xref></contrib></contrib-group><aff id="aff0005"><label>a</label>Australian Institute of Tropical Health & Medicine, James Cook University, Townsville, QLD 4811, Australia</aff><aff id="aff0010"><label>b</label>Independent Researcher, MD 20876, USA</aff><aff id="aff0015"><label>c</label>American University of Nigeria, 640001 Yola, Nigeria</aff><aff id="aff0020"><label>d</label>Department of Mathematics, Statistics and Physics, Qatar University, 2713 Doha, Qatar</aff><author-notes><corresp id="cor0005"><label>⁎</label>Corresponding author. <email>oyelola.adegboye@jcu.edu.au</email></corresp></author-notes><pub-date pub-type="pmc-release"><day>19</day><month>12</month><year>2018</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub" iso-8601-date="2019-06-01"><season>May-June</season><year>2019</year></pub-date><pub-date pub-type="epub"><day>19</day><month>12</month><year>2018</year></pub-date><volume>12</volume><issue>3</issue><fpage>343</fpage><lpage>349</lpage><history><date date-type="received"><day>16</day><month>7</month><year>2018</year></date><date date-type="rev-recd"><day>31</day><month>10</month><year>2018</year></date><date date-type="accepted"><day>5</day><month>12</month><year>2018</year></date></history><permissions><copyright-statement>© 2018 The Authors</copyright-statement><copyright-year>2018</copyright-year><license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p></license></permissions><abstract id="abs0005"><sec><title>Background</title><p>During outbreaks of infectious diseases, transmission of the pathogen can form networks of infected individuals connected either directly or indirectly.</p></sec><sec><title>Methods</title><p>Network centrality metrics were used to characterize hospital-acquired Middle East Respiratory Syndrome Coronavirus (HA-MERS) outbreaks in the Kingdom of Saudi Arabia between 2012 and 2016. Covariate-adjusted multivariable logistic regression models were applied to assess the effect of individual level risk factors and network level metrics associated with increase in length of hospital stay and risk of deaths from MERS.</p></sec><sec><title>Results</title><p>About 27% of MERS cases were hospital acquired during the study period. The median age of healthcare workers and hospitalized patients were 35 years and 63 years, respectively, Although HA-MERS were more connected, we found no significant difference in degree centrality metrics between HA-MERS and non-HA-MERS cases. Pre-existing medical conditions (adjusted Odds ratio (aOR) = 2.43, 95% confidence interval: (CI) [1.11–5.33]) and hospitalized patients (aOR = 29.99, 95% CI [1.80–48.65]) were the strongest risk predictors of death from MERS. The risk of death associated with 1-day increased length of stay was significantly higher for patients with comorbidities.</p></sec><sec><title>Conclusion</title><p>Our investigation also revealed that patients with an HA-MERS infection experienced a significantly longer hospital stay and were more likely to die from the disease. Healthcare worker should be reminded of their potential role as hubs for pathogens because of their proximity to and regular interaction with infected patients. On the other hand, this study has shown that while healthcare workers acted as epidemic attenuators, hospitalized patients played the role of an epidemic amplifier.</p></sec></abstract><kwd-group id="kwd0005"><title>Keywords</title><kwd>Hospital-acquired infections</kwd><kwd>MERS</kwd><kwd>Healthcare workers</kwd><kwd>Network analysis</kwd></kwd-group></article-meta></front></pmc><affiliations><list><country><li>Australie</li><li>Nigeria</li><li>Qatar</li><li>États-Unis</li></country><region><li>Maryland</li></region></list><tree><country name="Australie"><noRegion><name sortKey="Adegboye, Oyelola" sort="Adegboye, Oyelola" uniqKey="Adegboye O" first="Oyelola" last="Adegboye">Oyelola Adegboye</name></noRegion></country><country name="États-Unis"><region name="Maryland"><name sortKey="Saffary, Timor" sort="Saffary, Timor" uniqKey="Saffary T" first="Timor" last="Saffary">Timor Saffary</name></region></country><country name="Nigeria"><noRegion><name sortKey="Adegboye, Majeed" sort="Adegboye, Majeed" uniqKey="Adegboye M" first="Majeed" last="Adegboye">Majeed Adegboye</name></noRegion></country><country name="Qatar"><noRegion><name sortKey="Elfaki, Faiz" sort="Elfaki, Faiz" uniqKey="Elfaki F" first="Faiz" last="Elfaki">Faiz Elfaki</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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