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Article: Detection of influenza and other respiratory viruses in air sampled from a university campus: a longitudinal study

TitleDetection of influenza and other respiratory viruses in air sampled from a university campus: a longitudinal study
Authors
Keywordsinfluenza and respiratory viruses
airborne particles
human density
temporal pattern
surveillance
Issue Date2019
PublisherOxford University Press. The Journal's web site is located at http://www.oxfordjournals.org/our_journals/cid/
Citation
Clinical Infectious Diseases, 2019, Epub How to Cite?
AbstractBACKGROUND: Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at non-healthcare locations versus surveillance data obtained by conventional means has not been fully assessed. METHODS: From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time RT-PCR. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. RESULTS: Influenza A (16.9%, 117/694) and B (4.6%, 31/694) viruses were detected at higher frequencies in air than rhinovirus (2.2%, 6/270), respiratory syncytial virus (0.4%, 1/270), or human coronaviruses (0%, 0/270). Multivariate analyses showed that increased crowdedness (aOR = 2.3, 95% confidence interval, 1.5 - 3.8, P < 0.001) and higher indoor temperature (1.2, 1.1 - 1.3, P < 0.001) were associated with detection of influenza airborne particles, but absolute humidity was not (0.9, 0.7 - 1.1, P = 0.213). Higher copies of influenza viral genome were detected from airborne particles > 4 mum in spring and < 1 mum in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. CONCLUSIONS: Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community.
Persistent Identifierhttp://hdl.handle.net/10722/274533
ISSN
2019 Impact Factor: 8.313
2015 SCImago Journal Rankings: 4.742

 

DC FieldValueLanguage
dc.contributor.authorXie, C-
dc.contributor.authorLau, EHY-
dc.contributor.authorYoshida, T-
dc.contributor.authorYu, H-
dc.contributor.authorWang, X-
dc.contributor.authorWu, H-
dc.contributor.authorWei, J-
dc.contributor.authorCowling, BJ-
dc.contributor.authorPeiris, M-
dc.contributor.authorLi, Y-
dc.contributor.authorYen, HL-
dc.date.accessioned2019-08-18T15:03:35Z-
dc.date.available2019-08-18T15:03:35Z-
dc.date.issued2019-
dc.identifier.citationClinical Infectious Diseases, 2019, Epub-
dc.identifier.issn1058-4838-
dc.identifier.urihttp://hdl.handle.net/10722/274533-
dc.description.abstractBACKGROUND: Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at non-healthcare locations versus surveillance data obtained by conventional means has not been fully assessed. METHODS: From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time RT-PCR. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. RESULTS: Influenza A (16.9%, 117/694) and B (4.6%, 31/694) viruses were detected at higher frequencies in air than rhinovirus (2.2%, 6/270), respiratory syncytial virus (0.4%, 1/270), or human coronaviruses (0%, 0/270). Multivariate analyses showed that increased crowdedness (aOR = 2.3, 95% confidence interval, 1.5 - 3.8, P < 0.001) and higher indoor temperature (1.2, 1.1 - 1.3, P < 0.001) were associated with detection of influenza airborne particles, but absolute humidity was not (0.9, 0.7 - 1.1, P = 0.213). Higher copies of influenza viral genome were detected from airborne particles > 4 mum in spring and < 1 mum in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. CONCLUSIONS: Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://www.oxfordjournals.org/our_journals/cid/-
dc.relation.ispartofClinical Infectious Diseases-
dc.rightsPre-print: Journal Title] ©: [year] [owner as specified on the article] Published by Oxford University Press [on behalf of xxxxxx]. All rights reserved. Pre-print (Once an article is published, preprint notice should be amended to): This is an electronic version of an article published in [include the complete citation information for the final version of the Article as published in the print edition of the Journal.] Post-print: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version [insert complete citation information here] is available online at: xxxxxxx [insert URL that the author will receive upon publication here].-
dc.subjectinfluenza and respiratory viruses-
dc.subjectairborne particles-
dc.subjecthuman density-
dc.subjecttemporal pattern-
dc.subjectsurveillance-
dc.titleDetection of influenza and other respiratory viruses in air sampled from a university campus: a longitudinal study-
dc.typeArticle-
dc.identifier.emailLau, EHY: ehylau@hku.hk-
dc.identifier.emailCowling, BJ: bcowling@hku.hk-
dc.identifier.emailPeiris, M: malik@hkucc.hku.hk-
dc.identifier.emailLi, Y: liyg@hku.hk-
dc.identifier.emailYen, HL: hyen@hku.hk-
dc.identifier.authorityLau, EHY=rp01349-
dc.identifier.authorityCowling, BJ=rp01326-
dc.identifier.authorityPeiris, M=rp00410-
dc.identifier.authorityLi, Y=rp00151-
dc.identifier.authorityYen, HL=rp00304-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/cid/ciz296-
dc.identifier.pmid30963180-
dc.identifier.hkuros301903-
dc.publisher.placeUnited States-

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