Project · Quantitative modelling

Comparing strategies under uncertainty

Health-economics decision model, norovirus vaccination strategies · Excel · VBA automation · Scenario & sensitivity analysis

The decision question: which strategy is the most defensible choice under uncertainty — and what conditions would change that conclusion? The model's output isn't a point estimate; it's a small set of recommendation-ready comparisons plus a transparent view of what drives the uncertainty.

What the model does

Built during my MSc, the model compares alternative vaccination strategies on cost and outcome dimensions, identifying dominated options and mapping trade-offs. Three analytical layers sit on top of the core comparison:

Dominance and trade-off mapping — which options are consistently favourable, which are dominated, and where the impact–cost balance lands
Robustness testing — scenario and sensitivity analysis showing how conclusions shift as assumptions move within plausible ranges
Risk-driver identification — which inputs are decision-sensitive and therefore worth measuring or validating first

Built for the reader, not the modeller

The outputs are designed as decision artefacts: visuals a non-technical stakeholder can read as "why this option, and what would change it". VBA automates repeated scenario runs and refreshes the visuals consistently — reducing manual handling and making the analysis auditable and reproducible.

Why it transfers beyond public health

The decision logic is domain-agnostic: choosing among competing initiatives with constrained resources and uncertain outcomes is the same problem as prioritising features, rollout strategies or investments. The value is in making trade-offs comparable and uncertainty explicit — then letting the decision-maker see which assumptions their choice hinges on.

Model walkthrough and outputs available on request — email me.

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