Background: 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. Â\copyright 2011 Nishiura et al.
Nishiura, H.; PRESTO, Japan Science and Technology Agency, Saitama, Japan; email: nishiura@hku.hk
affiliation
PRESTO, Japan Science and Technology Agency, Saitama, Japan; Theoretical Epidemiology, University of Utrecht, Utrecht, Netherlands; School of Public Health, The University of Hong Kong, Hong Kong, China; Mathematical and Computational Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States; Fogarty International Center, National Institutes of Health, Bethesda, MD, United States; Santa Fe Institute, Santa Fe, NM, United States
%0 Journal Article
%1 Nishiura2011
%A Nishiura, H.
%A Chowell, G.
%A Castillo-Chavez, C.
%D 2011
%J PLoS ONE
%K 2009 A H1N1 H1N1; Human; Humans; Influenza Influenza, Pandemics; Sample Seroepidemiologic Size; Studies Subtype; Virus, article; blood computing; confidence disease epidemiology; experimental human; hypothesis; incidence; influenza; interval; mathematical methodology; model; pandemic pandemic; pathogenicity, prediction; sample sampling; seroepidemiology; size; transmission; validity; virus
%N 3
%R http://dx.doi.org/10.1371/journal.pone.0017908
%T Did modeling overestimate the transmission potential of pandemic (H1N1-2009)? sample size estimation for post-epidemic seroepidemiological studies
%U http://dx.doi.org/10.1371/journal.pone.0017908
%V 6
%X Background: 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. Â\copyright 2011 Nishiura et al.
@article{Nishiura2011,
abstract = {Background: 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. {\^A}{\copyright} 2011 Nishiura et al.},
added-at = {2017-11-10T22:48:29.000+0100},
affiliation = {PRESTO, Japan Science and Technology Agency, Saitama, Japan; Theoretical Epidemiology, University of Utrecht, Utrecht, Netherlands; School of Public Health, The University of Hong Kong, Hong Kong, China; Mathematical and Computational Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States; Fogarty International Center, National Institutes of Health, Bethesda, MD, United States; Santa Fe Institute, Santa Fe, NM, United States},
art_number = {e17908},
author = {Nishiura, H. and Chowell, G. and Castillo-Chavez, C.},
biburl = {https://www.bibsonomy.org/bibtex/202726b2c9d5bddc191cb59fd2bcbca70/ccchavez},
correspondence_address1 = {Nishiura, H.; PRESTO, Japan Science and Technology Agency, Saitama, Japan; email: nishiura@hku.hk},
date-added = {2017-11-10 21:45:26 +0000},
date-modified = {2017-11-10 21:45:26 +0000},
document_type = {Article},
doi = {http://dx.doi.org/10.1371/journal.pone.0017908},
interhash = {6b515b2e6e7ee1372699382b7e5c5dd7},
intrahash = {02726b2c9d5bddc191cb59fd2bcbca70},
issn = {19326203},
journal = {PLoS ONE},
keywords = {2009 A H1N1 H1N1; Human; Humans; Influenza Influenza, Pandemics; Sample Seroepidemiologic Size; Studies Subtype; Virus, article; blood computing; confidence disease epidemiology; experimental human; hypothesis; incidence; influenza; interval; mathematical methodology; model; pandemic pandemic; pathogenicity, prediction; sample sampling; seroepidemiology; size; transmission; validity; virus},
language = {English},
number = 3,
pubmed_id = {21455307},
timestamp = {2017-11-10T22:48:29.000+0100},
title = {Did modeling overestimate the transmission potential of pandemic (H1N1-2009)? sample size estimation for post-epidemic seroepidemiological studies},
url = {http://dx.doi.org/10.1371/journal.pone.0017908},
volume = 6,
year = 2011
}