Friday, April 24, 2026

Robustly Quantifying #Uncertainty in #International Avian #Influenza #H5N1 Infection #Fatality Ratios

 


Abstract

Knowing the mortality rates associated with infection by a pathogen is essential for effective preparedness and response. Here, harnessing the flexibility of a Bayesian approach, we produce an estimate of the Infection Fatality Ratio (IFR) for A(H5N1) conditional on explicit assumptions, and quantify the uncertainty thereof. We also apply the method to first-wave COVID-19 data up to March 2020, demonstrating the estimates that could be obtained were the model available then. Our analysis uses World Development Indicators (WDI) from the World Bank, the A(H5N1) WHO confirmed cases and deaths tracker by country (2003-2024), and COVID-19 cases and deaths data from John Hopkins University (January and February 2020). Since infectious disease dynamics are typically influenced by local socio-economic factors rather than political borders, individual countries are placed within clusters of countries sharing similar WDIs relevant to respiratory viral diseases, with clusters derived by performing Hierarchical Clustering. To estimate the IFR, we fit a Negative Binomial Bayesian Hierarchical Model for A(H5N1) and COVID-19 separately. We explicitly modelled key unobserved parameters with informative priors from expert opinion and literature. By modelling underreporting, our analysis suggests lower fatality (15.3%) compared to WHO's Case Fatality Ratio estimate (54%) on lab-confirmed cases. However, credible intervals are wide ([0.5%, 64.2%] 95% CrI). Therefore, good preparedness for a potential A(H5N1) pandemic implies adopting scenario planning under our central estimate, as well as for IFRs as high as 70%. Our approach also returns a COVID-19 IFR estimate of 2.8% with [2.5%, 3.1%] 95% CrI which is consistent with literature.


Competing Interest Statement

The authors have declared no competing interest.


Funding Statement

MKA is supported by the Schlumberger Foundation Faculty for the Future. TH is supported by the Wellcome Trust (Ref: 227438/Z/23/Z) and Medical Research Council (Ref: UKRI483). LG, MN, TF are employed by UKHSA. The research leading to these results received UK Government grant-in-aid funding to UKHSA. The views expressed in this publication are those of the authors and not necessarily those of UKHSA or Department for Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Link: https://www.medrxiv.org/content/10.64898/2026.04.22.26351373v1

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