Where Does CLTS Work Best? Quantifying Predictors of CLTS Performance in Four Countries
Kara Stuart, Rachel Peletz, Jeff Albert, Ranjiv Khush, and Caroline Delaire. Where Does CLTS Work Best? Quantifying Predictors of CLTS Performance in Four Countries. Environmental Science & Technology. DOI: 10.1021/acs.est.0c05733
Improving the effectiveness of rural sanitation interventions is critical for meeting the United Nations’ Sustainable Development Goals and improving public health. Community-led total sanitation (CLTS) is the most widely used rural sanitation intervention globally; however, evidence shows that CLTS does not work equally well everywhere. Contextual factors outside the control of implementers may partially determine CLTS outcomes, although the extent of these influences is poorly understood.
In this study, we investigate the extent to which 18 contextual factors from readily available datasets can help predict the achievement and sustainability of open-defecation-free (ODF) status in Cambodia, Ghana, Liberia, and Zambia. Using multilevel logistic regressions, we found that the predictors of CLTS performance varied between countries, with the exception of small community size. Accessibility and literacy levels were correlated with CLTS outcomes, but the direction of correlation differed between countries.
To translate findings into practical guidance for CLTS implementers, we used classification and regression trees to identify a “split point” for each contextual factor significantly associated with ODF achievement. We also identified the combinations of factors conducive to a minimum of 50% ODF achievement. This study demonstrates that publicly available, high-resolution datasets on accessibility, socioeconomic, and environmental factors can be leveraged to target CLTS activities to the most favorable contexts.