Where Does CLTS Work Best? Quantifying Predictors of CLTS Performance in Four Countries

Area of Science:

• Public Health
• Environmental Science
• Development Studies

Background:

• Rural sanitation interventions are crucial for global health and Sustainable Development Goals.
• Community-led total sanitation (CLTS) is a widely adopted strategy, but its effectiveness is inconsistent across diverse settings.
• Understanding contextual influences on CLTS outcomes is vital for optimizing its implementation.

Purpose of the Study:

• To assess how 18 contextual factors predict the achievement and sustainability of open-defecation-free (ODF) status in Cambodia, Ghana, Liberia, and Zambia.
• To identify key predictors of CLTS success using readily available datasets.
• To provide practical guidance for tailoring CLTS interventions to specific contexts.

Main Methods:

• Multilevel logistic regressions were employed to analyze the association between contextual factors and ODF status across four countries.
• Classification and regression trees were used to identify significant "split points" for contextual factors.
• Combinations of factors associated with at least 50% ODF achievement were determined.

Main Results:

• Predictors of CLTS performance varied significantly by country, with small community size being a consistent exception.
• Accessibility and literacy levels showed correlations with ODF outcomes, but the directionality differed across nations.
• Specific combinations of contextual factors were identified as being conducive to achieving ODF status.

Conclusions:

• Publicly available datasets on accessibility, socioeconomic, and environmental factors can effectively predict CLTS success.
• Leveraging these datasets allows for targeted implementation of CLTS, focusing on contexts most likely to yield positive outcomes.
• This data-driven approach can enhance the effectiveness and sustainability of rural sanitation initiatives worldwide.