A data-driven approach for mitigation of fecal pathogen infections from unsafe WASH practices

TL;DR

This study identifies optimal WASH thresholds to reduce fecal pathogen infections in Thailand, showing that combined improvements in water, sanitation, and hygiene are more effective than isolated actions.

Contribution

The study introduces a data-driven method combining multilevel modeling and response surface analysis to identify optimal WASH thresholds for infection mitigation.

Findings

Infection prevalence exceeded 40 cases per 1000 in communities with unsafe WASH practices.

Coordinated WASH improvements reduced infection risks more effectively than isolated interventions.

Optimal thresholds include 40% water treatment, 35–40% fecal-sludge emptying, and 80% handwashing compliance.

Abstract

Fecal pathogen infections remain a major public health challenge in low- and middle-income countries, where unsafe water, inadequate sanitation, and poor hygiene persist. Northeastern Thailand continues to experience a high burden of helminth infections linked to deficient water, sanitation, and hygiene (WASH) conditions. Evidence-based identification of combined WASH thresholds is needed to support effective interventions and progress toward Sustainable Development Goal 6.

A cross-sectional study was conducted among 520 households across 18 communities in Tongkhop city, Sakon Nakhon Province, Thailand. Primary data from household surveys, key-informant interviews, and field observations were integrated with disease-surveillance records. A multilevel generalized linear model was applied to assess associations between WASH indicators and infection prevalence. Model-predicted outcomes were further analyzed using response surface methodology to quantify nonlinear interactions and identify optimal WASH thresholds.

Infection prevalence exceeded 40 cases per 1000 population in communities relying on untreated water, infrequent fecal-sludge emptying, and low hygiene compliance. Substantial risk reductions were observed when household water treatment exceeded 40 %, fecal-sludge emptying frequency reached 35–40 %, and handwashing compliance before meals surpassed 80 %, while raw-fish consumption remained below 50 %. The response-surface analysis revealed clear nonlinear synergies among WASH components, indicating that coordinated improvements were more effective than isolated interventions.

This study demonstrates that integrating multilevel modeling with response surface analysis enables quantitative identification of critical WASH thresholds for reducing fecal-pathogen infections. The findings highlight the importance of coordinated improvements in water safety, sanitation management, and hygiene behaviors to mitigate environmental transmission pathways. These results provide actionable, data-driven guidance for public health planning and support the environmental dimension of the One Health framework in advancing SDG 6.

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