Hotspots of unimproved sources of drinking water in Ethiopia: Mapping and Spatial analysis of Ethiopia Demographic and Health Survey Data 2016

Abstract

Background: More than 35% of Ethiopian population is using drinking water from unimproved sources.As per the United Nations' Sustainable Development Goals, Ethiopia is aspiring to achieve universal and equitable access to safe and affordable drinking water for all by 2030. For these goals to be accomplished, it is important to map the country's hotspot areas of unimproved source of drinkingwater so that resource allocation and disease control can be optimized there.Methods: A population based cross-sectional study was conducted in Ethiopia from January 18 to June 27, 2016. Data were collected from 10,064 households using a pretested and structured questionnaire. A stratified two-stage cluster sampling was employed where the enumeration areas were primary sampling units and households were secondary sampling units. Systematic sampling with probability proportional to size was employed to select samples. Data were cleaned in spreadsheet and entered in to SaTScan and ArcGIS soft-wares for mapping and analysis. The Global Moran's I and spatial scan statistical tests (Bernoulli model) were done to explore the presence of clustering in the study area and local spatial clusters (hotspots) of unimproved sources of drinking water using ArcGIS version 10.3 and Kuldorff's SaTScan version 9.4 soft-wares, respectively. Moran's I value closer to +1 declared presence of clustering at national level and Log-Likelihood ratio (LLR) greater than the critical value with p<0.05 declared statistical significant hotspots across the regions.Results: In this study, unimproved sources of drinking water were spatially clustered at the study area (Moran's I: 0.35, p<0.05). A total of 143 significant clusters were identified. Of which, eight were most likely (primary) clusters and the rest 135 were secondary clusters. The first spatial window which contains primary clusters was located in Amhara and Afar regions (LLR: 78.89, at p<0.001). The rest 33 spatial windows which contain secondary clusters were found in all regions, except Gambela region and Addis Abeba city administration (with a range of LLR: 10.09-78.89, p<0.001).Conclusions: This study identified non-random clusters and hot spots of unimproved sources of drinking water. Therefore, the result helps decision makers for their geographical interventions to combat problems related to hotspots.

Households with unimproved water sources in Ethiopia: spatial variation and point-of-use treatment based on 2016 Demographic and Health Survey

“…But, evidence on the spatial distribution of households which depend on unimproved water sources has been incomplete or ignored in most of the studies [2,17]. In this regard, few studies were conducted in Ethiopia to locate or map areas with highest unimproved water source coverage among different wealth categories and local levels [18,19]. Moreover, data on how POU water treatment practices of populations dependent on unimproved water sources is scarce.…”

Unimproved water sources in Ethiopia: Spatial variation and household point-of-use treatment practice based on 2016 Demographic and Health Survey

“…But, evidence on the spatial distribution of households which depends on unimproved water sources has been incomplete or ignored in most of the studies [15,16]. In this regard, few studies were conducted in Ethiopia to locate or map areas with highest unimproved water source coverage among different wealth categories and local level [17,18]. Moreover, data on how point-of-use water treatment practices of populations dependent on unimproved water sources look like is scarce.…”