Synthesising evidence to estimate pandemic (2009) A/H1N1 influenza severity in 2009-2011
Anne M. Presanis, Richard G. Pebody, Paul J. Birrell, Brian D. M. Tom,, Helen K. Green, Hayley Durnall, Douglas Fleming, Daniela De Angelis

TL;DR
This study uses Bayesian evidence synthesis to estimate the severity of the 2009 H1N1 influenza pandemic across three waves, revealing age-related risk patterns and changes in infection attack rates over time.
Contribution
It extends previous models to include the third pandemic wave and compares two modeling approaches for estimating severity across multiple waves.
Findings
Age-distribution of severity is 'u'-shaped, highest in children and older adults.
Infection attack rate shifts towards adults over 25 in later waves.
Average case-severity appears to increase over the three waves.
Abstract
Knowledge of the severity of an influenza outbreak is crucial for informing and monitoring appropriate public health responses, both during and after an epidemic. However, case-fatality, case-intensive care admission and case-hospitalisation risks are difficult to measure directly. Bayesian evidence synthesis methods have previously been employed to combine fragmented, under-ascertained and biased surveillance data coherently and consistently, to estimate case-severity risks in the first two waves of the 2009 A/H1N1 influenza pandemic experienced in England. We present in detail the complex probabilistic model underlying this evidence synthesis, and extend the analysis to also estimate severity in the third wave of the pandemic strain during the 2010/2011 influenza season. We adapt the model to account for changes in the surveillance data available over the three waves. We consider two…
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