Enabling or Disabling? Reflections on the Ethiopian National WASH Inventory Process

Welle, Katharina; Schaefer, Florian; Butterworth, John; Bostoen, Kristof

doi:10.1111/j.1759-5436.2012.00306.x

Cited by 4 publications

(2 citation statements)

References 7 publications

(3 reference statements)

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“…Nearly 50% of the consequences of undernutrition are caused by environmental factors that include poor hygiene and a lack of access to water supply and sanitation (Tessema 2017). Moreover, the majority of health facilities in Ethiopia lack access to clean water, and only approximately 32% have access to safe water (Welle et al 2012).…”

Section: The Context Of Drinking Water Supply In Developing Countriesmentioning

confidence: 99%

Valuing the water supply: ecosystem-based potable water supply management for the Legedadie-Dire catchments, Central Ethiopia

2019

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Background: There is a substantial interest in the values that consumers place on drinking water quality and supply. Financial resources are crucial to improving the urban potable water supply in developing countries that are characterized by low-cost recovery rates and a high and rapidly growing demand for more reliable services. This study examined households' willingness to pay (WTP) for the improvement of water services by identifying their water choice decisions and the mode of water supply that they prefer the water supply authority to use among several alternative water supply options. Stated-preference data were collected from 322 randomly selected households in Addis Ababa, who were presented with three sets of choices (three alternative bundle choices, including the reference scenario). The data were analyzed using the mixed logit WTP space model. Three approaches to modeling the distribution of WTP (fixed, uncorrelated, and correlated) using mixed logit WTP space models were compared. Results: Three-quarters of the households agreed to contribute money toward ecosystem-based water supply management (EBWSM) intervention programs on a monthly basis. The average contribution that the respondents were willing to pay was 150.5 Ethiopian Birr (ETB) as a one-off lump sum to kick off the EBWSM activities. Most of the respondents chose a bundle of water supply options that provides risk-free and high-quality water with no months of shortages than moderate water quality that is safe to drink and palatable with 1 month shortages annually. This implies that households would need to be supplied with risk-free, high-quality water without interruption at an appropriate flow pressure. The model with correlations fitted the data well with the highest simulated log-likelihoods at convergence and gave the best estimate of the households' WTP for water improvement. Nearly 46% of the sampled households were willing to pay more than 33 ETB per month, and 49% of the households were willing to pay between 21 ETB and 33 ETB per month for the monthly water bill. Overall, approximately 95% of the sampled households were willing to pay more than 21 ETB. Conclusion: Customers are willing to pay to avoid most types of water supply restrictions. Moreover, WTP is sensitive to the scope of service improvement, income, affixed price, and elicitation method. In summary, mixed logit WTP-space models can help accurately predict household-level WTP, which can be used to select improvements in drinking water access and services in the Legedadie-Dire catchments.

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Section: The Context Of Drinking Water Supply In Developing Countriesmentioning

confidence: 99%

Valuing the water supply: ecosystem-based potable water supply management for the Legedadie-Dire catchments, Central Ethiopia

2019

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“…Ideally, monitoring processes should be designed so that information also fulfils local level needs where water and sanitation service delivery is actually occurring. This can help to ensure that the collected information is put to good use, promotes ownership of data among collectors which can aid in continuing data collection compliance, and enables learning at a local level (Welle et al, 2012). Further, the HRWS framework compels governments to share information with the public in an accessible and understandable way (de Albuquerque, 2014) which is critical for enabling users to claim and exercise their rights.…”

Section: Governancementioning

confidence: 99%

Monitoring the human rights to water and sanitation: an analysis of policy in Pacific island countries

2016

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Government monitoring of water and sanitation services is a critical step in realising the human rights to water and sanitation (HRWS). In this study we investigated the national water and sanitation policies of 13 Pacific island countries (PICs) to understand how they envision monitoring the water and sanitation service delivery dimensions put forth by the HRWS framework. In particular, we analysed the policies for fundamental aspects of good monitoring governance and sought to learn how strongly monitoring of each service delivery dimension was represented in the policies. We found that delineation of roles and responsibilities and defined information flows are generally underdeveloped, and that the policies tend to give precedence to monitoring the service delivery dimensions of availability, quality, and sustainability over accessibility, affordability, acceptability, and equality. Donors have considerable influence on which dimensions receive the most emphasis in the policies. If realisation of the HRWS is to be effectively supported in PICs, PIC governments and supporting donors must continue to refine national policy to clarify aspects of good monitoring governance and to be more inclusive of monitoring a wider range of service delivery dimensions.

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Addressing gaps in data on drinking water quality through data integration and machine learning: evidence from Ethiopia

Ambel,

Bain,

Degefu

et al. 2023

npj Clean Water

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Monitoring access to safely managed drinking water services requires information on water quality. An increasing number of countries have integrated water quality testing in household surveys however it is not anticipated that such tests will be included in all future surveys. Using water testing data from the 2016 Ethiopia Socio-Economic Survey (ESS) we developed predictive models to identify households using contaminated (≥1 E. coli per 100 mL) drinking water sources based on common machine learning classification algorithms. These models were then applied to the 2013–2014 and 2018–2019 waves of the ESS that did not include water testing. The highest performing model achieved good accuracy (88.5%; 95% CI 86.3%, 90.6%) and discrimination (AUC 0.91; 95% CI 0.89, 0.94). The use of demographic, socioeconomic, and geospatial variables provided comparable results to that of the full features model whereas a model based exclusively on water source type performed poorly. Drinking water quality at the point of collection can be predicted from demographic, socioeconomic, and geospatial variables that are often available in household surveys.

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Enabling or Disabling? Reflections on the Ethiopian National WASH Inventory Process

Cited by 4 publications

References 7 publications

Valuing the water supply: ecosystem-based potable water supply management for the Legedadie-Dire catchments, Central Ethiopia

Valuing the water supply: ecosystem-based potable water supply management for the Legedadie-Dire catchments, Central Ethiopia

Monitoring the human rights to water and sanitation: an analysis of policy in Pacific island countries

Addressing gaps in data on drinking water quality through data integration and machine learning: evidence from Ethiopia

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