title: Interpreting Seroepidemiologic Studies of Influenza in a Context of Nonbracketing Sera.
abstract: BACKGROUND
  In influenza epidemiology, analysis of paired sera collected from people before and after influenza seasons has been used for decades to study the cumulative incidence of influenza virus infections in populations. However, interpretation becomes challenging when sera are collected after the start or before the end of an epidemic, and do not neatly bracket the epidemic.
  
  
  METHODS
  Serum samples were collected longitudinally in a community-based study. Most participants provided their first serum after the start of circulation of influenza A(H1N1)pdm09 virus in 2009. We developed a Bayesian hierarchical model to correct for nonbracketing sera and estimate the cumulative incidence of infection from the serological data and surveillance data in Hong Kong.
  
  
  RESULTS
  We analyzed 4,843 sera from 2,097 unvaccinated participants in the study, collected from April 2009 to December 2010. After accounting for nonbracketing, we estimated that the cumulative incidence of H1N1pdm09 virus infection was 45% (95% credible interval [CI] = 40%, 49%), 17% (95% CI = 13%, 20%), and 11% (95% CI = 6%, 18%) for children ages 0-18 years, adults 19-50 years, and older adults >50 years, respectively. Including all available data substantially increased precision compared with a simpler analysis based only on sera collected at 6-month intervals in a subset of participants.
  
  
  CONCLUSIONS
  We developed a framework for the analysis of antibody titers that accounted for the timing of sera collection with respect to influenza activity and permitted robust estimation of the cumulative incidence of infection during an epidemic.
authors.affiliation: From theaWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China;bCentre for Influenza Research, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; andcMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.
authors.forename: Tim K
authors.initials: TK
authors.lastname: Tsang
authors.forename: Vicky J
authors.initials: VJ
authors.lastname: Fang
authors.forename: Ranawaka A P M
authors.initials: RA
authors.lastname: Perera
authors.forename: Dennis K M
authors.initials: DK
authors.lastname: Ip
authors.forename: Gabriel M
authors.initials: GM
authors.lastname: Leung
authors.forename: J S Malik
authors.initials: JS
authors.lastname: Peiris
authors.forename: Simon
authors.initials: S
authors.lastname: Cauchemez
authors.forename: Benjamin J
authors.initials: BJ
authors.lastname: Cowling
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000914:Antibodies, Viral / Q000097:blood*; D001499:Bayes Theorem; D015415:Biomarkers / Q000097:blood; D002648:Child; D002675:Child, Preschool; D015340:Epidemiologic Research Design; D005260:Female; D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology*; D007251:Influenza, Human / Q000097:blood / Q000453:epidemiology* / Q000276:immunology; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016036:Seroepidemiologic Studies; D055815:Young Adult
chemical_list: D000914:Antibodies, Viral; D015415:Biomarkers