title: Epidemiological characteristics of 2009 (H1N1) pandemic influenza based on paired sera from a longitudinal community cohort study.
abstract: BACKGROUND
  While patterns of incidence of clinical influenza have been well described, much uncertainty remains over patterns of incidence of infection. The 2009 pandemic provided both the motivation and opportunity to investigate patterns of mild and asymptomatic infection using serological techniques. However, to date, only broad epidemiological patterns have been defined, based on largely cross-sectional study designs with convenience sampling frameworks.
  
  
  RESULTS
  We conducted a paired serological survey of a cohort of households in Hong Kong, recruited using random digit dialing, and gathered data on severe confirmed cases from the public hospital system (>90% inpatient days). Paired sera were obtained from 770 individuals, aged 3 to 103, along with detailed individual-level and household-level risk factors for infection. Also, we extrapolated beyond the period of our study using time series of severe cases and we simulated alternate study designs using epidemiological parameters obtained from our data. Rates of infection during the period of our study decreased substantially with age: for 3-19 years, the attack rate was 39% (31%-49%); 20-39 years, 8.9% (5.3%-14.7%); 40-59 years, 5.3% (3.5%-8.0%); and 60 years or older, 0.77% (0.18%-4.2%). We estimated parameters for a parsimonious model of infection in which a linear age term and the presence of a child in the household were used to predict the log odds of infection. Patterns of symptom reporting suggested that children experienced symptoms more often than adults. The overall rate of confirmed pandemic (H1N1) 2009 influenza (H1N1pdm) deaths was 7.6 (6.2-9.5) per 100,000 infections. However, there was substantial and progressive increase in deaths per 100,000 infections with increasing age from 0.66 (0.65-0.86) for 3-19 years up to 220 (50-4,000) for 60 years and older. Extrapolating beyond the period of our study using rates of severe disease, we estimated that 56% (43%-69%) of 3-19 year olds and 16% (13%-18%) of people overall were infected by the pandemic strain up to the end of January 2010. Using simulation, we found that, during 2009, larger cohorts with shorter follow-up times could have rapidly provided similar data to those presented here.
  
  
  CONCLUSIONS
  Should H1N1pdm evolve to be more infectious in older adults, average rates of severe disease per infection could be higher in future waves: measuring such changes in severity requires studies similar to that described here. The benefit of effective vaccination against H1N1pdm infection is likely to be substantial for older individuals. Revised pandemic influenza preparedness plans should include prospective serological cohort studies. Many individuals, of all ages, remained susceptible to H1N1pdm after the main 2009 wave in Hong Kong. Please see later in the article for the Editors' Summary.
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, United Kingdom. s.riley@imperial.ac.uk
authors.forename: Steven
authors.initials: S
authors.lastname: Riley
authors.forename: Kin O
authors.initials: KO
authors.lastname: Kwok
authors.forename: Kendra M
authors.initials: KM
authors.lastname: Wu
authors.forename: Danny Y
authors.initials: DY
authors.lastname: Ning
authors.forename: Benjamin J
authors.initials: BJ
authors.lastname: Cowling
authors.forename: Joseph T
authors.initials: JT
authors.lastname: Wu
authors.forename: Lai-Ming
authors.initials: LM
authors.lastname: Ho
authors.forename: Thomas
authors.initials: T
authors.lastname: Tsang
authors.forename: Su-Vui
authors.initials: SV
authors.lastname: Lo
authors.forename: Daniel K W
authors.initials: DK
authors.lastname: Chu
authors.forename: Edward S K
authors.initials: ES
authors.lastname: Ma
authors.forename: J S Malik
authors.initials: JS
authors.lastname: Peiris
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D006723:Hong Kong / Q000453:epidemiology; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000502:physiology*; D007251:Influenza, Human / Q000097:blood* / Q000453:epidemiology* / Q000821:virology; D008137:Longitudinal Studies; D008875:Middle Aged; D058873:Pandemics / Q000706:statistics & numerical data*; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D012720:Severity of Illness Index; D013997:Time Factors; D055815:Young Adult