Factors affecting risk of influenza virus infections in a longitudinal serologic study

Abstract

Introduction: Hosts’ immunity status and their contact behaviours are two of the many factors that determine the transmission and infection of respiratory pathogens, such as influenza. To investigate the former factor, a longitudinal serosurvey was implemented to study risk factors for infection with the 2009 pandemic influenza A(H1N1) virus after the main wave. Epidemiological characteristics of this subsequent wave and titre changes across time were also evaluated. To investigate behavioral factors associated with risk of infection, a contact survey was used to identify the contact dimensions that are most relevant for respiratory pathogen spreading, proxied by acute respiratory illness. Method: Participants were recruited from the general community, blood specimens were drawn, and a survey was administered to measure contact patterns. Antibody level of A/Cal/7/2009, A/Perth/16/2009, B/Brisbane/60/2007 and B/Florida/5/2006 were measured by hemagglutination inhibition test for longitudinal serum specimens. Effects of individual immunity status and past infection on the infection outcome (a four-fold or greater increase in antibody titre) were estimated. To access how hosts’ behavior affects respiratory pathogens spread, incidence rate of acute respiratory illnesses were compared with contact data from three dimensions, namely number of contacts, duration and locations. Results: Adults were found to have higher chance of infection during subsequent wave than in the main wave. One year increase in age and an increase in 1-fold of HI titre of A/Cal/7/2009 lowers the infection odds in subsequent wave by 2% and 36% respectively while an increase in 1-fold of HI titre of B/Brisbane /60/2007 increases the infection risk by 20%. Children (<20y) were observed to have consistently higher titre values than other age groups regardless of the infection status throughout the observed period. Respiratory pathogen spreading, proxied by acute respiratory illnesses (ARI), was best explained by number of contacts and number of locations simultaneously. Other potential explanatory factors include having a small household size, being female and being middle-aged. Intra-household correlation of ARI risk ranges from 0.43 to 0.48. Conclusion: Since a person’s immunity status and infection history is related to their risk of infection, they should be incorporated into calculating epidemiological measures, such as forecasting the cumulative incidence of infection in the future. Meanwhile, parameterization which encompasses interplay of contact dimensions will improve modeling of transmission dynamics of respiratory pathogens.