File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Theoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak

TitleTheoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peak
Authors
Issue Date2011
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.tbiomed.com/home/
Citation
Theoretical Biology And Medical Modelling, 2011, v. 8 n. 1 How to Cite?
AbstractBackground. While many pandemic preparedness plans have promoted disease control effort to lower and delay an epidemic peak, analytical methods for determining the required control effort and making statistical inferences have yet to be sought. As a first step to address this issue, we present a theoretical basis on which to assess the impact of an early intervention on the epidemic peak, employing a simple epidemic model. Methods. We focus on estimating the impact of an early control effort (e.g. unsuccessful containment), assuming that the transmission rate abruptly increases when control is discontinued. We provide analytical expressions for magnitude and time of the epidemic peak, employing approximate logistic and logarithmic-form solutions for the latter. Empirical influenza data (H1N1-2009) in Japan are analyzed to estimate the effect of the summer holiday period in lowering and delaying the peak in 2009. Results. Our model estimates that the epidemic peak of the 2009 pandemic was delayed for 21 days due to summer holiday. Decline in peak appears to be a nonlinear function of control-associated reduction in the reproduction number. Peak delay is shown to critically depend on the fraction of initially immune individuals. Conclusions. The proposed modeling approaches offer methodological avenues to assess empirical data and to objectively estimate required control effort to lower and delay an epidemic peak. Analytical findings support a critical need to conduct population-wide serological survey as a prior requirement for estimating the time of peak. © 2011 Omori and Nishiura; licensee BioMed Central Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/133671
ISSN
2015 Impact Factor: 1.033
2015 SCImago Journal Rankings: 0.444
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Japan Science and Technology Agency
Japan Society for the Promotion of Science
Funding Information:

We would like to thank three anonymous reviewers for helpful comments on earlier draft of this paper. HN is supported by the Japan Science and Technology Agency PRESTO program. RO is financially supported by Research Fellowship of Japan Society for the Promotion of Science.

References

 

DC FieldValueLanguage
dc.contributor.authorOmori, Ren_HK
dc.contributor.authorNishiura, Hen_HK
dc.date.accessioned2011-05-24T02:14:16Z-
dc.date.available2011-05-24T02:14:16Z-
dc.date.issued2011en_HK
dc.identifier.citationTheoretical Biology And Medical Modelling, 2011, v. 8 n. 1en_HK
dc.identifier.issn1742-4682en_HK
dc.identifier.urihttp://hdl.handle.net/10722/133671-
dc.description.abstractBackground. While many pandemic preparedness plans have promoted disease control effort to lower and delay an epidemic peak, analytical methods for determining the required control effort and making statistical inferences have yet to be sought. As a first step to address this issue, we present a theoretical basis on which to assess the impact of an early intervention on the epidemic peak, employing a simple epidemic model. Methods. We focus on estimating the impact of an early control effort (e.g. unsuccessful containment), assuming that the transmission rate abruptly increases when control is discontinued. We provide analytical expressions for magnitude and time of the epidemic peak, employing approximate logistic and logarithmic-form solutions for the latter. Empirical influenza data (H1N1-2009) in Japan are analyzed to estimate the effect of the summer holiday period in lowering and delaying the peak in 2009. Results. Our model estimates that the epidemic peak of the 2009 pandemic was delayed for 21 days due to summer holiday. Decline in peak appears to be a nonlinear function of control-associated reduction in the reproduction number. Peak delay is shown to critically depend on the fraction of initially immune individuals. Conclusions. The proposed modeling approaches offer methodological avenues to assess empirical data and to objectively estimate required control effort to lower and delay an epidemic peak. Analytical findings support a critical need to conduct population-wide serological survey as a prior requirement for estimating the time of peak. © 2011 Omori and Nishiura; licensee BioMed Central Ltd.en_HK
dc.languageengen_US
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.tbiomed.com/home/en_HK
dc.relation.ispartofTheoretical Biology and Medical Modellingen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsTheoretical Biology and Medical Modelling. Copyright © BioMed Central Ltd.en_US
dc.titleTheoretical basis to measure the impact of short-lasting control of an infectious disease on the epidemic peaken_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1742-4682&volume=8, article no. 2&spage=&epage=&date=2011&atitle=Theoretical+basis+to+measure+the+impact+of+short-lasting+control+of+an+infectious+disease+on+the+epidemic+peak-
dc.identifier.emailNishiura, H:nishiura@hku.hken_HK
dc.identifier.authorityNishiura, H=rp01488en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/1742-4682-8-2en_HK
dc.identifier.pmid21269441-
dc.identifier.pmcidPMC3040699-
dc.identifier.scopuseid_2-s2.0-78951486438en_HK
dc.identifier.hkuros185320en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78951486438&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume8en_HK
dc.identifier.issue1en_HK
dc.identifier.isiWOS:000287455500001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridOmori, R=35088528100en_HK
dc.identifier.scopusauthoridNishiura, H=7005501836en_HK
dc.identifier.citeulike8764346-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats