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Using cluster analysis on municipal statistical data to configure public policies about Water, Sanitation and Hygiene in Venezuela

Published 30 Jan 2023 in math.NA and cs.NA | (2301.12604v1)

Abstract: Objective: The aim of this research is to demonstrate how the use of hierarchical cluster analysis on 366 municipalities and other minor entities (parishes) of Venezuela, could be useful to consider regional differences and similarities between territorial entities when designing national public policies of Water, Sanitation and Hygiene (WASH) based on evidence. Methods and results: Consider data from various sources to characterize the population of Venezuela through their territorial entities. Select variables at the level of the territorial entities to cover demographic characteristics, mortality and nutrition, coverage of reliable water and sanitation services, access to education, and access to information and communication technologies. Classify the territorial entities into a limited number of mutually exclusive groups using hierarchical clustering techniques and based on proximity in the multi-dimensional space. Adjust of assignments, reallocating some entities into a different group based on the specialists' opinion about its hierarchy in the cities regional system and its geographic location. Define an indicator to verify the consistency of the groups built. Conduct a statistical analysis to confirm separation of the groups. Demonstrate the utility of the results with some examples of common analysis when building a sanitary public policy, using seven distinct groups of recommendations depending on each cluster. Conclusions: Cluster analysis can be a useful method to analyse relevant differences between territorial entities when designing national public policies based on evidence.

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