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Prototype

AMR Policy Decision Support

Explore how antimicrobial resistance (AMR) policies perform in terms of total cost, QALYs and deaths for multiple pathogens. This is a high-level sandbox – not a full HTA – but it mirrors Markov-style cost-effectiveness thinking.

Step 1 · Scenario context
Population, horizon & WTP
Define the cohort, time horizon and willingness-to-pay (WTP).
Average cohort (e.g. hospital catchment or country sample).
AMR policy horizons are often 5–10 years.
Used to classify policies as cost-effective vs. not.
Only used for presets – you can still override pathogen parameters.
Not sure about WTP? Many European settings use 20–50k €/QALY.

Results · Scenario outputs

Costs, QALYs, deaths, ICER & incremental NMB

Ready to simulate

Configure the scenario on the left, add at least one pathogen and one policy, then click Run simulation. Results will appear here.

Literature & parameter support

Unsure about parameters? Search Google Scholar or PubMed for burden, CFRs or cost estimates. Use WHO / ECDC / OECD links for global AMR reports.

Quick links: WHO GLASS · ECDC AMR · OECD AMR