Determinants of influenza transmission in South East Asia: insights from a household cohort study in Vietnam

Abstract

To guide control policies, it is important that the determinants of influenza transmission are fully characterized. Such assessment is complex because the risk of influenza infection is multifaceted and depends both on immunity acquired naturally or via vaccination and on the individual level of exposure to influenza in the community or in the household. Here, we analyse a large household cohort study conducted in 2007-2010 in Vietnam using innovative statistical methods to ascertain in an integrative framework the relative contribution of variables that influence the transmission of seasonal (H1N1, H3N2, B) and pandemic H1N1pdm09 influenza. Influenza infection was diagnosed by haemagglutination-inhibition (HI) antibody assay of paired serum samples. We used a Bayesian data augmentation Markov chain Monte Carlo strategy based on digraphs to reconstruct unobserved chains of transmission in households and estimate transmission parameters. The probability of transmission from an infected individual to another household member was 8% (95% CI, 6%, 10%) on average, and varied with pre-season titers, age and household size. Within households of size 3, the probability of transmission from an infected member to a child with low pre-season HI antibody titers was 27% (95% CI 21%-35%). High pre-season HI titers were protective against infection, with a reduction in the hazard of infection of 59% (95% CI, 44%-71%) and 87% (95% CI, 70%-96%) for intermediate (1∶20-1∶40) and high (≥1∶80) HI titers, respectively. Even after correcting for pre-season HI titers, adults had half the infection risk of children. Twenty six percent (95% CI: 21%, 30%) of infections may be attributed to household transmission. Our results highlight the importance of integrated analysis by influenza sub-type, age and pre-season HI titers in order to infer influenza transmission risks in and outside of the household.

Figure 1. Final size data and methods to estimate transmission parameters.

A. Example of final size data for a household of size 4. Subjects 1 and 4 were infected; subject 3 was not; diagnostic for subject 2 was missing. B. Example of digraph consistent with the final size data. For inference, data are augmented with a digraph (blue arrows) that informs on the transmission process. If there is an edge from the community to subject i, subject i was infected (this is the case for subject 1). If there is an edge from subject j to subject i, it means that if subject j was infected then subject i was infected too. C. Another example of digraph consistent with the data. We note that certain digraphs may allow more than 1 possible route of transmission. For example, subject 4 could have been infected in the community or by subject 2. D. Example of digraph that is not consistent with the data. This is because this digraph would imply that subject 3 was infected but subject 4 was not.

Figure 2. Determinants of influenza transmission in and out of the household.

A. Probability of influenza infection from the community for children with low pre-season titres. The season is indicated by the color (blue: 2008; pink: Spring 2009; red: Autumn 2009). B. Relative risk of infection for intermediate (1∶20–1∶40) and high (≥1∶80) pre-season HI titres relative to low (≤1∶10) pre-season HI titres (in the household and in the community). C. Relative risk of infection of adults relative to children after correcting for pre-season HI titres (in the household and in the community).