Predictive modelling of helminthic egg distribution in pit latrines: integrating multi-depth analysis with environmental and operational parameters in rural Tanzania

ABSTRACT

Despite the widespread use of pit latrines as primary sanitation infrastructure in rural areas, the spatial distribution patterns of helminth eggs within these systems remain critically under-investigated, particularly through depth-stratified analysis integrating environmental and operational parameters. This study employed a cross-sectional analytical design with multi-depth sampling (top, middle, and bottom strata) from 70 pit latrines in rural Tanzania, analysing 210 samples for helminth egg concentrations alongside comprehensive physicochemical characterisation. The results revealed consistent vertical stratification: the bottom layers (less than 0.5 m from the bottom of the pit) had the highest helminth concentrations (13.01 ± 6.31 eggs/L), representing increases of 43.5 and 17.8% compared with the surface layer (0–0.5 m below the sludge surface) and the intermediate layer (50% of the total sludge depth), respectively. Multiple linear regression modelling (R2 = 0.665) identified moisture content, chemical oxygen demand, turbidity, pit age, and structural condition as significant predictors of helminth distribution. Depth-stratified risk assessment, age-based emptying schedules, and lime-based treatment can substantially reduce pathogen exposure risks for sanitation workers and environmental contamination. This research advances evidence-based faecal sludge management practices critical for achieving Sustainable Development Goal (SDG) 6 targets while addressing persistent helminthiasis transmission challenges affecting 883 million children globally.