Use of Bayseain networks to identify risk factors associated with worm infections

Data on the prevalence of soil transmitted helminths (STH) and risk factors for infection (sanitation, water, hygiene) have been collected during the WASH for WORMS study, a randomized controlled trial investigating the impact of an integrated WASH and deworming intervention on STH infection in Timor-Leste. Surprisingly, analysis of the baseline data using regression models has identified few associations between STH infection and WASH variables. On the other hand, a spatial analysis has identified several environmental factors that are associated with increased risk of STH infection.  The use of Bayesian networks (BN) in infectious diseases epidemiology has so far been limited, but could potentially provide a powerful analytical method for identify risk factors and understanding causal relationships, especially for diseases with multiple and/or complex transmission dynamics. The aim of this project is to use BN to further explore the WASH for WORMS data, together with available environmental data, to further understand transmission pathways for STH infections in Timor-Leste.