Bayesian Estimation of True Prevalence and Associated Risk Factors for <i>Leptospira</i> spp. Among Slaughterhouse Workers and Slaughtered Cattle in the Bahr El Ghazal Region of South Sudan

Abstract

This study provides the first Bayesian-based estimates of leptospiral exposure in slaughterhouse settings in Western Bahr El Ghazal. The findings underscore the need to improve occupational safety, strengthen surveillance, and apply One Health approaches to reduce zoonotic transmission. Despite limitations, including lack of environmental data, the Bayesian framework proved effective for generating robust prevalence estimates in a resource-limited setting. Expanded geographic coverage and incorporation of environmental assessments are recommended to inform targeted leptospirosis control strategies.