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Article: Modelling the proportion of influenza infections within households during pandemic and non-pandemic years

TitleModelling the proportion of influenza infections within households during pandemic and non-pandemic years
Authors
Issue Date2011
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
Plos One, 2011, v. 6 n. 7 How to Cite?
AbstractBackground: The key epidemiological difference between pandemic and seasonal influenza is that the population is largely susceptible during a pandemic, whereas, during non-pandemic seasons a level of immunity exists. The population-level efficacy of household-based mitigation strategies depends on the proportion of infections that occur within households. In general, mitigation measures such as isolation and quarantine are more effective at the population level if the proportion of household transmission is low. Methods/Results: We calculated the proportion of infections within households during pandemic years compared with non-pandemic years using a deterministic model of household transmission in which all combinations of household size and individual infection states were enumerated explicitly. We found that the proportion of infections that occur within households was only partially influenced by the hazard h of infection within household relative to the hazard of infection outside the household, especially for small basic reproductive numbers. During pandemics, the number of within-household infections was lower than one might expect for a given h because many of the susceptible individuals were infected from the community and the number of susceptible individuals within household was thus depleted rapidly. In addition, we found that for the value of h at which 30% of infections occur within households during non-pandemic years, a similar 31% of infections occur within households during pandemic years. Interpretation: We suggest that a trade off between the community force of infection and the number of susceptible individuals in a household explains an apparent invariance in the proportion of infections that occur in households in our model. During a pandemic, although there are more susceptible individuals in a household, the community force of infection is very high. However, during non-pandemic years, the force of infection is much lower but there are fewer susceptible individuals within the household. © 2011 Kwok et al.
Persistent Identifierhttp://hdl.handle.net/10722/137610
ISSN
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.839
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
University of Hong Kong
Funding Information:

This research is part of the PhD studies of Kin On Kwok, whose studentship was financed by the University of Hong Kong. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

 

DC FieldValueLanguage
dc.contributor.authorKwok, KOen_HK
dc.contributor.authorLeung, GMen_HK
dc.contributor.authorRiley, Sen_HK
dc.date.accessioned2011-08-26T14:29:02Z-
dc.date.available2011-08-26T14:29:02Z-
dc.date.issued2011en_HK
dc.identifier.citationPlos One, 2011, v. 6 n. 7en_HK
dc.identifier.issn1932-6203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137610-
dc.description.abstractBackground: The key epidemiological difference between pandemic and seasonal influenza is that the population is largely susceptible during a pandemic, whereas, during non-pandemic seasons a level of immunity exists. The population-level efficacy of household-based mitigation strategies depends on the proportion of infections that occur within households. In general, mitigation measures such as isolation and quarantine are more effective at the population level if the proportion of household transmission is low. Methods/Results: We calculated the proportion of infections within households during pandemic years compared with non-pandemic years using a deterministic model of household transmission in which all combinations of household size and individual infection states were enumerated explicitly. We found that the proportion of infections that occur within households was only partially influenced by the hazard h of infection within household relative to the hazard of infection outside the household, especially for small basic reproductive numbers. During pandemics, the number of within-household infections was lower than one might expect for a given h because many of the susceptible individuals were infected from the community and the number of susceptible individuals within household was thus depleted rapidly. In addition, we found that for the value of h at which 30% of infections occur within households during non-pandemic years, a similar 31% of infections occur within households during pandemic years. Interpretation: We suggest that a trade off between the community force of infection and the number of susceptible individuals in a household explains an apparent invariance in the proportion of infections that occur in households in our model. During a pandemic, although there are more susceptible individuals in a household, the community force of infection is very high. However, during non-pandemic years, the force of infection is much lower but there are fewer susceptible individuals within the household. © 2011 Kwok et al.en_HK
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.actionen_HK
dc.relation.ispartofPLoS ONEen_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.meshDisease Outbreaks - statistics and numerical data-
dc.subject.meshFamily Characteristics-
dc.subject.meshHumans-
dc.subject.meshInfluenza, Human - epidemiology-
dc.subject.meshPandemics - statistics and numerical data-
dc.titleModelling the proportion of influenza infections within households during pandemic and non-pandemic yearsen_HK
dc.typeArticleen_HK
dc.identifier.emailLeung, GM:gmleung@hku.hken_HK
dc.identifier.emailRiley, S:sriley@hkucc.hku.hk, steven.riley@hku.hken_HK
dc.identifier.authorityLeung, GM=rp00460en_HK
dc.identifier.authorityRiley, S=rp00511en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0022089en_HK
dc.identifier.pmid21779380-
dc.identifier.pmcidPMC3136504-
dc.identifier.scopuseid_2-s2.0-79960306780en_HK
dc.identifier.hkuros189255en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79960306780&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.issue7en_HK
dc.identifier.spagee22089en_US
dc.identifier.epagee22089en_US
dc.identifier.isiWOS:000292811300039-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridKwok, KO=35983448100en_HK
dc.identifier.scopusauthoridLeung, GM=7007159841en_HK
dc.identifier.scopusauthoridRiley, S=7102619416en_HK
dc.identifier.issnl1932-6203-

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