Increased transmissibility explains the third wave of infection by the 2009 H1N1 pandemic virus in England

Abstract

In the 2009 H1N1 pandemic, the United Kingdom experienced two waves of infection, the first in the late spring and the second in the autumn. Given the low level of susceptibility to the pandemic virus expected to be remaining in the population after the second wave, it was a surprise that a substantial third epidemic occurred in the UK population between November 2010 and February 2011, despite no evidence for any significant antigenic evolution of the pandemic virus. Here, we use a mathematical model of influenza transmission embedded within a Bayesian synthesis inferential framework to jointly analyze syndromic, virological, and serological surveillance data collected in England in 2009–2011 and thereby assess epidemiological mechanisms which might have generated the third wave. We find that substantially increased transmissibility of the H1N1pdm09 virus is required to reproduce the third wave, suggesting that the virus evolved and increased fitness in the human host by the end of 2010, or that the very cold weather experienced in the United Kingdom at that time enhanced transmission rates. We also find some evidence that the preexisting heterologous immunity which reduced attack rates in adults during 2009 had substantially decayed by the winter of 2010, thus increasing the susceptibility of the adult population to infection. Finally, our analysis suggests that a pandemic vaccination campaign targeting adults and school-age children could have mitigated or prevented the third wave even at moderate levels of coverage.

Longevity and Determinants of Protective Humoral Immunity after Pandemic Influenza Infection

“…Our results, using longitudinal data from individuals, are the first to provide robust evidence that repeat pandemic waves prior to antigenic drift (18) are not driven by waning humoral immunity. Rather, our results suggest that third waves of A(H1N1)pdm09 may have been caused by not-yet-characterized large susceptible populations at the end of initial pandemic waves, possibly in addition to other explanations, such as increased intrinsic transmissibility (19). Furthermore, if similar patterns of antibody persistence occur during the interpandemic period, they may explain the apparent cycling of H1N1 and H3N2 subtypes (20) and consequently the persistence of H1N1 as a minor subtype.…”

Determinants of Influenza Transmission in South East Asia: Insights from a Household Cohort Study in Vietnam

“…However, it has long been acknowledged that HI titers are only an imperfect correlate of protection. For example, in 2009, the proportion of elderly people estimated to be protected against H1N1pdm09 influenza was much higher than had been suggested by pre-pandemic HI titers [6]. In the first study that characterized the protective effect of HI titers, Hobson et al [4] used a challenge design to ensure all subjects in the study had the same level of exposure to influenza; but such approach is expensive and can only be applied to healthy adults.…”

Model-based reconstruction of an epidemic using multiple datasets: understanding influenza A/H1N1 pandemic dynamics in Israel

“…Such external data are not available to us. In [22,24], the estimation of the many extra parameters was avoided by assuming a prior distribution for these parameters (in the prior distribution, the parameters are independently distributed according to a gamma distribution), and using this prior distribution to integrate out the extra parameters, so that only the two parameters of the gamma prior need to be estimated. In our approach, we opted to avoid the problem of the unknowns introduced by the ILI data by not fitting the clinical data altogether and therefore use the conditional likelihood approach as described above.…”