Abstract

We present a data-driven typology framework for understanding patterns in drinking water accessibility across low- and middle-income countries. Further, we obtain novel typology-specific insights regarding the relationships between possible explanatory variables and typology outcomes. First, we conducted exploratory factor analysis to obtain a smaller set of interpretable factors from the initial set of 17 drinking water accessibility indicators from 73 countries. The resulting seven factors summarize the key drivers for water accessibility, and also serve as a vehicle for framing discussions on country outcomes. We clustered the countries based on their seven-dimensional water accessibility factor scores, referring to the resulting three clusters as ‘typologies,’ namely, Decentralized, Centralized and Hybrid. The typologies serve as a vehicle for analyzing water accessibility among countries with similar patterns, in contrast with geographically-based approaches. Finally, we fitted a decision tree classifier to analyze relationships between a country’s typology membership and socioeconomic, geographic and transportation explanatory variables. We found that private car ownership, population density and per-capita gross domestic product are most relevant in predicting a country’s drinking water accessibility typology.