Based on WHO Data
#19,128
While the popular press likes to quote the scary `roughly 50% CFR (case fatality rate)' of H5N1 in humans (based on WHO reporting of 477 deaths among 993 confirmed cases (48%)), confirmed cases are usually restricted to those sick enough to be hospitalized and lucky enough to be tested for the virus.
It is assumed that some number of mild (or asymptomatic) cases occur but are never detected. It is also likely that some number of serious (or even fatal) cases go unrecognized, and unreported.
We've also seen dozens of strains of HPAI H5N1 spillover to humans over the past 30 years, with varying levels of apparent virulence in humans. As the chart above illustrates, some regions of the world have reported far lower fatality rates than others.
All of which makes it exceedingly difficult to make blanket statements about the likely impact of an H5N1 pandemic. Particularly since we can't even say, with any degree of certainty, how many people have died from COVID.
Suffice to say, anything over a 5% IFR (Infection Fatality Rate) would be catastrophic, and would exceed the death toll of the 1918 influenza pandemic by a wide margin.
While they have come up with a significantly lower IFR estimate (median 15.3%), this is simply their best guess - based on their model and assumptions - and they warn the reality could be significantly higher or lower (range 0.5% to 64.2%).While there are a great many unknowns that must be considered, today we've a preprint from researchers at the UK Health Security Agency and the University of Manchester, which attempts to model a more realistic IFR number from a future H5N1 pandemic.
This is, admittedly, much higher than my personal guesstimate (5%-7%), which is based primarily on wishful thinking.
Since I'm notoriously out of my depth when it comes to statistics and modeling, I'll simply post the abstract and urge you to read the report in its entirety. I'll have a bit more after the break.
Robustly Quantifying Uncertainty in International Avian Influenza A(H5N1) Infection Fatality Ratios
Leonardo Gada, Mwandida, Kamba Afuleni, Michael Noble, Thomas House, Thomas Finnie
doi: https://doi.org/10.64898/2026.04.22.26351373
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.
Key Messages
1. We adopted a disease-agnostic and adaptable Bayesian model, embedding scientific knowledge on A(H5N1) in the priors informed by published literature, to estimate the Infection Fatality Ratio (IFR) of avian influenza A(H5N1).
2. Accounting for underreporting of cases and deaths, we estimate the IFR of avian influenza A(H5N1) at 15.3%, albeit with wide uncertainty ([0.5%, 64.2%] 95% Credible Intervals).
3. Due to the uncertainty in the estimate, 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%.
Anyone looking for certainty or serenity from this preprint will likely come away disappointed, but it does remind us that we can't assume the next pandemic will be like the last one . . . or like any that we've seen in living history.
In our current climate of pandemic denial, the author's advice to prepare for a 15% IFR - but have contingencies for up to 70% - are likely to fall on deaf ears. Frankly, I'm not sure how any government would plan for a > 15% IFR, even if they could summon the political will to do so.
Which is why I've already got my supply of masks, hand sanitizer, and OTC meds in the hall closet, and have stayed current with all of my vaccines. If you aren't similarly prepared, you may want to revisit:Since even a 2% IFR would be devastating, and bring many critical services to the breaking point, I can only recommend that people (and businesses) take individual pandemic planning seriously.
