Inference of age‐dependent case‐fatality ratios for seasonal influenza virus subtypes A(H3N2) and A(H1N1)pdm09 and B lineages using data from the Netherlands

Abstract

AbstractBackgroundDespite the known relatively high disease burden of influenza, data are lacking regarding a critical epidemiological indicator, the case‐fatality ratio. Our objective was to infer age‐group and influenza (sub)type specific values by combining modelled estimates of symptomatic incidence and influenza‐attributable mortality.MethodsThe setting was the Netherlands, 2011/2012 through 2019/2020 seasons. Sentinel surveillance data from general practitioners and laboratory testing were synthesised to supply age‐group specific estimates of incidence of symptomatic infection, and ecological additive modelling was used to estimate influenza‐attributable deaths. These were combined in an Bayesian inferential framework to estimate case‐fatality ratios for influenza A(H3N2), A(H1N1)pdm09 and influenza B, per 5‐year age‐group.ResultsCase‐fatality estimates were highest for influenza A(H3N2) followed by influenza B and then A(H1N1)pdm09 and were highest for the 85+ years age‐group, at 4.76% (95% credible interval [CrI]: 4.52–5.01%) for A(H3N2), followed by influenza B at 4.08% (95% CrI: 3.77–4.39%) and A(H1N1)pdm09 at 2.51% (95% CrI: 2.09–2.94%). For 55–59 through 85+ years, the case‐fatality risk was estimated to double with every 3.7 years of age.ConclusionsThese estimated case‐fatality ratios, per influenza sub(type) and per age‐group, constitute valuable information for public health decision‐making, for assessing the retrospective and prospective value of preventative interventions such as vaccination and for health economic evaluations.