United Kingdom • • • 🌿 Progressive

Oficina gubernamental en Londres con profesionales de espaldas trabajando ante pantallas con gráficos de distribución de riesgo y barras
Oficina con modelos de riesgo en pantalla, imagen alusiva a la modelización actuarial para la preparación ante pandemias en el Reino Unido. · Imagen generada EPM

United Kingdom models uncertainty to prepare for future pandemics

The Government Actuary's Department worked with the UK Health Security Agency on a proof of concept using actuarial modelling to explore how uncertainty over…

--- The context --- The United Kingdom pandemic preparedness strategy emphasises analysis, scientific evidence and expert advice, building on wider preparedness activity. Within that framework, the Government Actuary's Department, GAD, worked with the UK Health Security Agency, UKHSA, to explore how uncertainty could shape collective public health decisions. When vaccine development timescales and the number of candidates are uncertain, relying on a single estimate leaves the public exposed to surprises that a wider range of possible outcomes can help anticipate. --- The facts --- GAD and UKHSA produced a proof of concept combining scientific input, economic evidence and actuarial techniques. Rather than a single forecast, the analysis generated a distribution of outcomes, allowing the team to examine central estimates, less likely but more severe outcomes, and the assumptions with the greatest influence. The simplified, hypothetical model represented a sequence of uncertain milestones, drawing on expert input and desk-based research, tested many plausible pathways and linked the resulting timescales to a measure of potential economic impact. The work also illustrated the public value of diversification: relying on fewer candidates could increase expected development times, and such delays could lead to higher economic costs. Making uncertainty explicit gave a consistent framework to compare options. --- The positions --- UKHSA brought public health expertise and asked GAD to test whether actuarial techniques could support understanding of uncertainty and help frame its implications for the UK economy. GAD designed the modelling approach and the interpretation of risk. Michael West, Deputy Chief Economist at UKHSA, was reported as saying that the teams worked closely together, that the analysis was useful and clearly presented within a challenging timescale, and that the technical expertise made future collaboration welcome. Both sides stressed the boundary: exploratory work to demonstrate a modelling approach, not to recommend a particular response or replace the scientific, operational and policy judgements of decision-makers. --- What remains unknown --- The proof of concept describes itself as hypothetical and non-advisory, so its achievement is to show a way of exploring outcomes, not to guide live decisions. Further research, validation and assurance would be needed before adapting it. How the risk picture would shift with observed times, a different number of candidates or revised economic assumptions also remains unclear, although a future model could be updated with that evidence. --- Unanswered questions --- Can a validated version of this model support live decisions while preserving the caution that defines the current exploratory work? How will the distribution of outcomes change when observed development times and revised economic assumptions are fed into the model? Will diversification across vaccine candidates become a practical preparedness rule, or remain a theoretical lesson from this proof of concept? --- EPM analysis --- The main contribution is cultural as well as technical: preparedness stops leaning on one reassuring figure and shows openly what is not known, what mistakes could cost and which assumptions matter most. That transparency strengthens collective protection because trade-offs and emerging evidence can be debated before urgency forces improvised responses. 📌 EPM Take: In EPM's view, preparing for a pandemic with a distribution of outcomes rather than a single forecast is a more honest and more useful way to protect the public, because it turns uncertainty into shared information for decisions, shows the cost of concentrating bets on fewer vaccines and reminds public science that it serves best when it admits its limits, updates its evidence and puts that knowledge behind better informed and more resilient collective choices.
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