Quantifying Uncertainty in ESBL Enterobacterales Transmission from Animals and Environment to Humans in Singapore: A Structured Expert Judgment Approach

ObjectivesTo estimate daily transmission rates of ESBL-producing Enterobacterales across hospital environment surface, animal, and community environmental settings in Singapore to address scarce empirical data that constrains One Health modelling and policy design. MethodsA structured expert elicitation was conducted with a panel of eight experts: three for the clinical sector, three for the environmental sector, and two for the animal sector. Expert judgments were aggregated using both equal-weighting and Cookes Classical Model (performance-weighting) for hospital and companion-animal pathways, but only equal-weighting was used for the community-environment pathway. ResultsUnder performance weighting, the daily transmission rate was 2.19 per person-day (95% Credible Interval [CrI] 0.16-10.47) for the hospital-surface pathway and 0.03 (95% CrI 0.00-0.11) for the companion-animal pathway. The corresponding equal-weighted estimates were 0.20 (95% CrI 0.01-2.77) and 2.13 (95% CrI 0.09-24.02), respectively. For the community-environment pathway (equal-weighted only), the rate was 0.81 (95% CrI 0.10-4.12). ConclusionsThese findings suggest that environmental and hospital pathways may represent important but uncertain contributors to ESBL-producing Enterobacterales spread in urban contexts, whereas animal-associated transmission appears limited. This study demonstrates that structured expert elicitation can provide systematic probabilistic priors for transmission and cost-effectiveness models, directly informing future resource allocation and the development of prevention and control strategies. HighlightsO_LIWe addressed the lack of empirical data on ESBL-producing Enterobacterales cross-setting transmission by using Structured Expert Elicitation to generate systematic, probabilistic priors for One Health models. C_LIO_LIEstimated daily transmission rates suggest that environmental and hospital pathways are uncertain but potentially significant contributors to ESBL spread, whereas animal-associated transmission appears limited in the urban context. C_LIO_LIThese novel probabilistic priors can be directly embedded into cost-effectiveness models to inform future resource allocation and the development of data-driven antimicrobial resistance control strategies. C_LI