Mair L. H. Thomas-Possee, Andrew A. Channon, Robert E. S. Bain, James A. Wright
{"title":"赞比亚城市和城郊地区家庭、邻里和服务提供商造成自来饮用水间断的风险因素:横截面分析","authors":"Mair L. H. Thomas-Possee, Andrew A. Channon, Robert E. S. Bain, James A. Wright","doi":"10.1371/journal.pwat.0000127","DOIUrl":null,"url":null,"abstract":"Given nearly one third of sub-Saharan Africa’s population lack access to an improved water source that is available when needed, service continuity restricts access to safely managed services. Household surveys, water regulators, and utilities all gather data on service continuity, but few studies have integrated these disparate datasets to quantify continuity-related risk factors and inequalities. This study aimed to assess the added value of utility and regulator data for international monitoring by assessing factors affecting piped water availability in urban and peri-urban Zambia. Household ‘user’ data from the 2018 Demographic and Health Survey (n = 3047) were spatially linked to provider data from an international utility database and regulator reports. Multilevel modelling quantified provider-related and socio-economic risk factors for households reporting water being unavailable for at least one day in the previous fortnight. 47% (95% CI: 45%, 49%) of urban and peri-urban households reported water being unavailable for at least one full day, ranging from 18% (95% CI: 14%, 23%) to 76% (95% CI: 70%, 81%) across providers. Controlling for provider, home ownership (odds ratio (OR) = 1.31; p <0.01), speaking Luvale, Kaonde, Lunda (OR = 2.06; p <0.05) or Tonga (OR = 1.78; p <0.1) as an ethnicity proxy, and dry season interview dates (OR = 1.91; p <0.05) were associated with household-reported interruptions. Households using a neighbour’s tap (OR = 1.33; p <0.1) and in mid-wealth neighbourhoods (OR = 4.31; p <0.1) were more likely to report interruptions. For every $1000 increase in utility-level GDP per capita, the odds of an interruption were 0.51 times less (p<0.01). Substantial inequalities in drinking-water availability were found between provider coverage areas. Spatial integration of user, provider and regulator data enriches analysis, providing a finer-scale perspective than otherwise possible. However, wider use of utility or regulator data requires investment in monitoring of small-scale community supply intermittency and utility coverage area data.","PeriodicalId":93672,"journal":{"name":"PLOS water","volume":"97 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Household, neighbourhood and service provider risk factors for piped drinking-water intermittency in urban and peri-urban Zambia: A cross-sectional analysis\",\"authors\":\"Mair L. H. Thomas-Possee, Andrew A. Channon, Robert E. S. Bain, James A. Wright\",\"doi\":\"10.1371/journal.pwat.0000127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given nearly one third of sub-Saharan Africa’s population lack access to an improved water source that is available when needed, service continuity restricts access to safely managed services. Household surveys, water regulators, and utilities all gather data on service continuity, but few studies have integrated these disparate datasets to quantify continuity-related risk factors and inequalities. This study aimed to assess the added value of utility and regulator data for international monitoring by assessing factors affecting piped water availability in urban and peri-urban Zambia. Household ‘user’ data from the 2018 Demographic and Health Survey (n = 3047) were spatially linked to provider data from an international utility database and regulator reports. Multilevel modelling quantified provider-related and socio-economic risk factors for households reporting water being unavailable for at least one day in the previous fortnight. 47% (95% CI: 45%, 49%) of urban and peri-urban households reported water being unavailable for at least one full day, ranging from 18% (95% CI: 14%, 23%) to 76% (95% CI: 70%, 81%) across providers. Controlling for provider, home ownership (odds ratio (OR) = 1.31; p <0.01), speaking Luvale, Kaonde, Lunda (OR = 2.06; p <0.05) or Tonga (OR = 1.78; p <0.1) as an ethnicity proxy, and dry season interview dates (OR = 1.91; p <0.05) were associated with household-reported interruptions. Households using a neighbour’s tap (OR = 1.33; p <0.1) and in mid-wealth neighbourhoods (OR = 4.31; p <0.1) were more likely to report interruptions. For every $1000 increase in utility-level GDP per capita, the odds of an interruption were 0.51 times less (p<0.01). Substantial inequalities in drinking-water availability were found between provider coverage areas. Spatial integration of user, provider and regulator data enriches analysis, providing a finer-scale perspective than otherwise possible. 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Household, neighbourhood and service provider risk factors for piped drinking-water intermittency in urban and peri-urban Zambia: A cross-sectional analysis
Given nearly one third of sub-Saharan Africa’s population lack access to an improved water source that is available when needed, service continuity restricts access to safely managed services. Household surveys, water regulators, and utilities all gather data on service continuity, but few studies have integrated these disparate datasets to quantify continuity-related risk factors and inequalities. This study aimed to assess the added value of utility and regulator data for international monitoring by assessing factors affecting piped water availability in urban and peri-urban Zambia. Household ‘user’ data from the 2018 Demographic and Health Survey (n = 3047) were spatially linked to provider data from an international utility database and regulator reports. Multilevel modelling quantified provider-related and socio-economic risk factors for households reporting water being unavailable for at least one day in the previous fortnight. 47% (95% CI: 45%, 49%) of urban and peri-urban households reported water being unavailable for at least one full day, ranging from 18% (95% CI: 14%, 23%) to 76% (95% CI: 70%, 81%) across providers. Controlling for provider, home ownership (odds ratio (OR) = 1.31; p <0.01), speaking Luvale, Kaonde, Lunda (OR = 2.06; p <0.05) or Tonga (OR = 1.78; p <0.1) as an ethnicity proxy, and dry season interview dates (OR = 1.91; p <0.05) were associated with household-reported interruptions. Households using a neighbour’s tap (OR = 1.33; p <0.1) and in mid-wealth neighbourhoods (OR = 4.31; p <0.1) were more likely to report interruptions. For every $1000 increase in utility-level GDP per capita, the odds of an interruption were 0.51 times less (p<0.01). Substantial inequalities in drinking-water availability were found between provider coverage areas. Spatial integration of user, provider and regulator data enriches analysis, providing a finer-scale perspective than otherwise possible. However, wider use of utility or regulator data requires investment in monitoring of small-scale community supply intermittency and utility coverage area data.