Modelling the transmission and burden of ESBL-producing Enterobacterales from a One Health perspective in Singapore

Abstract

The long-term burden of antimicrobial resistance (AMR) in hyper-urbanised settings, shaped by complex, multi-sectoral transmission dynamics across human, animal, and environmental reservoirs, remains poorly understood. Using Singapore as a case study, we applied a dynamic One Health modelling framework to explore how ESBL-producing Enterobacterales infections and deaths may evolve over the next decade and identify critical control pathways. We developed a deterministic, compartmental One Health transmission model, the first to integrate hospital, community, companion animal, and environmental reservoirs, calibrated to ten years of national hospital surveillance data (2012-2021) using Markov Chain Monte Carlo Bayesian methods. We projected the baseline disease burden over a 10-year reporting horizon and compared it with counterfactual scenarios while employing global and local sensitivity analyses to identify influential parameters. Over this period, the model projected a total burden of 208,179 clinical ESBL-producing Enterobacterales infections (95% uncertainty interval [UI] 121,669-307,053) and 5567 (95% UI 3660-7806) deaths, with 3491 deaths specifically attributable to ESBL-producing Enterobacterales. Community decolonization strongly influenced infection burdens in both community and hospital settings; a 100% reduction in this process was projected to add nearly 1.8 million additional infections and more than 45,000 resistant-infection deaths across hospital and community settings in Singapore over 10 years. Our dynamic One Health model quantifies these inter-sectoral transmission pathways and identifies clear intervention priorities. While preventing progression from colonisation to infection is vital for reducing hospital-specific mortality, comprehensive system-wide control may benefit from targeting the community reservoir. Ultimately, the modelling framework developed here provides a robust, transferable tool for other global cities to design and evaluate integrated One Health AMR control strategies to mitigate urgent public health threats and associated socio-economic consequences for urban populations and global healthcare systems.

The authors' abstract, as published at the source. One Health, 2026 · DOI ↗