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Article: Did modeling overestimate the transmission potential of pandemic (H1N1-2009)? sample size estimation for post-epidemic seroepidemiological studies

TitleDid modeling overestimate the transmission potential of pandemic (H1N1-2009)? sample size estimation for post-epidemic seroepidemiological studies
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. 3 How to Cite?
AbstractBackground: Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies. Methodology/Principal Findings: Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used. Conclusions: Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion. © 2011 Nishiura et al.
Persistent Identifierhttp://hdl.handle.net/10722/133667
ISSN
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.839
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Japan Science and Technology Agency PRESTO
College of the Liberal Arts and Sciences of Arizona State University
National Science Foundation (NSF)DMS - 0502349
U.S. Department of Defense (NSA)H98230-06-1-0097
Alfred T. Sloan Foundation
Office of the Provost of Arizona State University
Funding Information:

HN was supported by the Japan Science and Technology Agency PRESTO program. GC received financial support from the College of the Liberal Arts and Sciences of Arizona State University. National Science Foundation (NSF - Grant DMS - 0502349), U.S. Department of Defense (NSA - Grant H98230-06-1-0097), the Alfred T. Sloan Foundation and the Office of the Provost of Arizona State University support CCC's research. 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.authorNishiura, Hen_HK
dc.contributor.authorChowell, Gen_HK
dc.contributor.authorCastilloChavez, Cen_HK
dc.date.accessioned2011-05-24T02:14:15Z-
dc.date.available2011-05-24T02:14:15Z-
dc.date.issued2011en_HK
dc.identifier.citationPlos One, 2011, v. 6 n. 3en_HK
dc.identifier.issn1932-6203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/133667-
dc.description.abstractBackground: Seroepidemiological studies before and after the epidemic wave of H1N1-2009 are useful for estimating population attack rates with a potential to validate early estimates of the reproduction number, R, in modeling studies. Methodology/Principal Findings: Since the final epidemic size, the proportion of individuals in a population who become infected during an epidemic, is not the result of a binomial sampling process because infection events are not independent of each other, we propose the use of an asymptotic distribution of the final size to compute approximate 95% confidence intervals of the observed final size. This allows the comparison of the observed final sizes against predictions based on the modeling study (R = 1.15, 1.40 and 1.90), which also yields simple formulae for determining sample sizes for future seroepidemiological studies. We examine a total of eleven published seroepidemiological studies of H1N1-2009 that took place after observing the peak incidence in a number of countries. Observed seropositive proportions in six studies appear to be smaller than that predicted from R = 1.40; four of the six studies sampled serum less than one month after the reported peak incidence. The comparison of the observed final sizes against R = 1.15 and 1.90 reveals that all eleven studies appear not to be significantly deviating from the prediction with R = 1.15, but final sizes in nine studies indicate overestimation if the value R = 1.90 is used. Conclusions: Sample sizes of published seroepidemiological studies were too small to assess the validity of model predictions except when R = 1.90 was used. We recommend the use of the proposed approach in determining the sample size of post-epidemic seroepidemiological studies, calculating the 95% confidence interval of observed final size, and conducting relevant hypothesis testing instead of the use of methods that rely on a binomial proportion. © 2011 Nishiura 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.titleDid modeling overestimate the transmission potential of pandemic (H1N1-2009)? sample size estimation for post-epidemic seroepidemiological studiesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1932-6203&volume=6&issue=3, article no. e17908&spage=&epage=&date=2011&atitle=Did+modeling+overestimate+the+transmission+potential+of+Pandemic+(H1N1-2009)?+sample+size+estimation+for+post-epidemic+seroepidemiological+studies-
dc.identifier.emailNishiura, H:nishiura@hku.hken_HK
dc.identifier.authorityNishiura, H=rp01488en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0017908en_HK
dc.identifier.pmid21455307-
dc.identifier.pmcidPMC3063792-
dc.identifier.scopuseid_2-s2.0-79953057804en_HK
dc.identifier.hkuros185316en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79953057804&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume6en_HK
dc.identifier.issue3en_HK
dc.identifier.isiWOS:000288811500015-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridNishiura, H=7005501836en_HK
dc.identifier.scopusauthoridChowell, G=9845935500en_HK
dc.identifier.scopusauthoridCastilloChavez, C=7003725806en_HK
dc.identifier.issnl1932-6203-

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