Assessment of baseline age-specific antibody prevalence and incidence of infection to novel influenza A/HINI 2009

Objectives: The objectives of the HINI 2009 serological surveillance project were twofold: to document (1) the prevalence of cross-reactive antibodies to HINI 2009 by age group in the population of England prior to arrival of the pandemic strain virus in the UK and (2) the age-specific incidence of infection by month as the pandemic progressed by measuring increases in the proportion of individuals with antibodies to HINI 2009 by age. Methods: Residual aliquots of samples submitted to 16 microbiology laboratories in eight regions in England in defined age groups in 2008 and stored by the Health Protection Agency serological surveillance programme were used to document age-stratified prevalence of antibodies to HINI 2009 prior to the arrival of the pandemic in the UK. Functional antibodies to the HINI 2009 virus were measured by haemagglutination inhibition (HI) and microneutralisation (MN) assays. For timely measurement of monthly incidence of infection with HINI 2009 between August 2009 and April 2010, the microbiology serum collections were supplemented by collection of residual sera from chemical pathology laboratories in England. Monthly seroincidence samples were tested by HI only, apart from the final sera collected post pandemic in 2010, which were also tested by MN. Incidence during the pandemic was estimated from changes in prevalence between time points and also by a likelihood-based method. Setting: Eight regions of England. Participants: Serum samples from patients accessing health care in England from whom blood samples were taken for unrelated microbiological or chemical pathology testing. Interventions: None. Main outcome measures: Baseline age-specific prevalence of functional antibodies to the HI NI 2009 virus prior to the arrival of the pandemic; changes in antibody prevalence during the period August 2009 to April 2010. Results: Pre-existing cross-reactive antibodies to HINI 2009 were detected in the baseline sera and increased with age, particularly in those born before 1950. The prediction of immunological protection derived from the baseline serological analysis was consistent with the lower clinical attack rates in older age groups. The high levels of susceptibility in children < 15 years, together with their mixing within school, resulted in the highest attack rates in this age group. Serological analysis by region confirms that there were geographical differences in timing of major pandemic waves. London had a big first wave among the 5- to 14-year age group, with the rest of the country reducing the gap after the second wave. Cumulative incidence in London remained higher throughout the pandemic in each age group. By the end of the second wave it is estimated that as many as 70% of school-aged children in London had been infected. Taken together, these observations are consistent with observations from previous pandemics in 1918, 1957 and 1968 that the major impact of influenza pandemics is on younger age groups, with a pattern of morbidity and mortality distinct from seasonal influenza epidemics. Conclusions: Serological analysis of appropriately structured, age-stratified and geographically representative samples can provide an immense amount of information to set in context other measures of pandemic impact in a population, and provide the most accurate measures of population exposure. National scale seroepidemiology studies require cross-agency coordination, multidisciplinary working, and considerable scientific resource.