The authors review challenges in estimating preventable AMR burden and advocate explicit counterfactuals, confounding control and principled combination of individual studies.
Key findings
- Estimates depend on preventable-burden definitions, comparators, selection, confounding and evidence synthesis. The authors argue that estimands should follow policy questions.
Why this matters globally
The framework helps policymakers avoid comparing AMR numbers that answer different questions and improves uncertainty transparency.
Thai researcher contribution
Mahidol-Oxford researchers contributed infectious-disease and causal-epidemiology expertise to a global framework.
Limitations to consider
As a Perspective, literature selection is author-driven without systematic search or quality appraisal, and proposed causal strategies need testing across data systems.