Your search found 2 records
1 Peletz, R.; Kisiangani, J.; Bonham, M.; Ronoh, P.; Delaire, C.; Kumpel, E.; Marks, S.; Khush, R. 2018. Why do water quality monitoring programs succeed or fail?: a qualitative comparative analysis of regulated testing systems in Sub-Saharan Africa. International Journal of Hygiene and Environmental Health, 221(6):907-920. [doi: https://doi.org/10.1016/j.ijheh.2018.05.010]
Water quality control ; Monitoring ; Programmes ; Water supply ; Drinking water ; Corporate culture ; Qualitative analysis ; Capacity building ; Regulations ; Case studies / Africa South of Sahara / Ethiopia / Guinea / Kenya / Senegal / Uganda / Zambia
(Location: IWMI HQ Call no: e-copy only Record No: H048841)
https://www.sciencedirect.com/science/article/pii/S1438463918300816/pdfft?md5=9d90204feefe14a1055d44b501333dd5&pid=1-s2.0-S1438463918300816-main.pdf
https://vlibrary.iwmi.org/pdf/H048841.pdf
https://vlibrary.iwmi.org/pdf/H048841.pdf
(1.43 MB) (1.43 MB)
Background:
Water quality testing is critical for guiding water safety management and ensuring public health. In many settings, however, water suppliers and surveillance agencies do not meet regulatory requirements for testing frequencies. This study examines the conditions that promote successful water quality monitoring in Africa, with the goal of providing evidence for strengthening regulated water quality testing programs.
Methods and findings:
We compared monitoring programs among 26 regulated water suppliers and surveillance agencies across six African countries. These institutions submitted monthly water quality testing results over 18 months. We also collected qualitative data on the conditions that influenced testing performance via approximately 821 h of semi-structured interviews and observations. Based on our qualitative data, we developed the Water Capacity Rating Diagnostic (WaterCaRD) to establish a scoring framework for evaluating the effects of the following conditions on testing performance: accountability, staffing, program structure, finances, and equipment & services. We summarized the qualitative data into case studies for each of the 26 institutions and then used the case studies to score the institutions against the conditions captured in WaterCaRD. Subsequently, we applied fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare these scores against performance outcomes for water quality testing. We defined the performance outcomes as the proportion of testing Targets Achieved (outcome 1) and Testing Consistency (outcome 2) based on the monthly number of microbial water quality tests conducted by each institution. Our analysis identified motivation & leadership, knowledge, staff retention, and transport as institutional conditions that were necessary for achieving monitoring targets. In addition, equipment, procurement, infrastructure, and enforcement contributed to the pathways that resulted in strong monitoring performance.
Conclusions:
Our identification of institutional commitment, comprising motivation & leadership, knowledge, and staff retention, as a key driver of monitoring performance was not surprising: in weak regulatory environments, individuals and their motivations take-on greater importance in determining institutional and programmatic outcomes. Nevertheless, efforts to build data collection capacity in low-resource settings largely focus on supply-side interventions: the provision of infrastructure, equipment, and training sessions. Our results indicate that these interventions will continue to have limited long-term impacts and sustainability without complementary strategies for motivating or incentivizing water supply and surveillance agency managers to achieve testing goals. More broadly, our research demonstrates both an experimental approach for diagnosing the systems that underlie service provision and an analytical strategy for identifying appropriate interventions.
Water quality testing is critical for guiding water safety management and ensuring public health. In many settings, however, water suppliers and surveillance agencies do not meet regulatory requirements for testing frequencies. This study examines the conditions that promote successful water quality monitoring in Africa, with the goal of providing evidence for strengthening regulated water quality testing programs.
Methods and findings:
We compared monitoring programs among 26 regulated water suppliers and surveillance agencies across six African countries. These institutions submitted monthly water quality testing results over 18 months. We also collected qualitative data on the conditions that influenced testing performance via approximately 821 h of semi-structured interviews and observations. Based on our qualitative data, we developed the Water Capacity Rating Diagnostic (WaterCaRD) to establish a scoring framework for evaluating the effects of the following conditions on testing performance: accountability, staffing, program structure, finances, and equipment & services. We summarized the qualitative data into case studies for each of the 26 institutions and then used the case studies to score the institutions against the conditions captured in WaterCaRD. Subsequently, we applied fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare these scores against performance outcomes for water quality testing. We defined the performance outcomes as the proportion of testing Targets Achieved (outcome 1) and Testing Consistency (outcome 2) based on the monthly number of microbial water quality tests conducted by each institution. Our analysis identified motivation & leadership, knowledge, staff retention, and transport as institutional conditions that were necessary for achieving monitoring targets. In addition, equipment, procurement, infrastructure, and enforcement contributed to the pathways that resulted in strong monitoring performance.
Conclusions:
Our identification of institutional commitment, comprising motivation & leadership, knowledge, and staff retention, as a key driver of monitoring performance was not surprising: in weak regulatory environments, individuals and their motivations take-on greater importance in determining institutional and programmatic outcomes. Nevertheless, efforts to build data collection capacity in low-resource settings largely focus on supply-side interventions: the provision of infrastructure, equipment, and training sessions. Our results indicate that these interventions will continue to have limited long-term impacts and sustainability without complementary strategies for motivating or incentivizing water supply and surveillance agency managers to achieve testing goals. More broadly, our research demonstrates both an experimental approach for diagnosing the systems that underlie service provision and an analytical strategy for identifying appropriate interventions.
2 Acey, C.; Kisiangani, J.; Ronoh, P.; Delaire, C.; Makena, E.; Norman, G.; Levine, D.; Khush, R.; Peletz, R. 2019. Cross-subsidies for improved sanitation in low income settlements: assessing the willingness to pay of water utility customers in Kenyan cities. World Development, 115:160-177. [doi: https://doi.org/10.1016/j.worlddev.2018.11.006]
Water supply ; Willingness to pay ; Low income groups ; Sanitation ; Water users ; Urban areas ; Financing ; User charges ; Subsidies ; Contingent valuation ; Stakeholders ; Socioeconomic environment ; Econometric models / Kenya
(Location: IWMI HQ Call no: e-copy only Record No: H049152)
https://www.sciencedirect.com/science/article/pii/S0305750X18304108/pdfft?md5=7a01086b63257e4fa7068d76e5874750&pid=1-s2.0-S0305750X18304108-main.pdf
https://vlibrary.iwmi.org/pdf/H049152.pdf
https://vlibrary.iwmi.org/pdf/H049152.pdf
(1.08 MB) (1.08 MB)
Most residents of the developing world do not have access to safely managed sanitation services, and large financial investments are required to address this need. Here we evaluate surcharges on water/sewerage tariffs as an option for supporting these investments in low-income neighborhoods. We investigated willingness-to-pay (WTP) for a pro-poor sanitation surcharge among customers of two urban water utilities in Kenya. Applying qualitative and quantitative methods, we conducted semi-structured in-depth interviews, focus-group discussions, and a double-bounded contingent valuation method for measuring WTP. We varied scenarios quasi-experimentally to study the effects of messaging and surcharge characteristics and evaluated factors associated with WTP. Our study finds that mean WTP was 290 KES (USD 2.9) per month, about 8% of the average water bill; median WTP was 100 KES (USD 1). In a multivariate analysis, WTP was significantly higher among customers that were younger, wealthier, shared toilets, and had higher water bills. WTP was also higher among customers that trusted the utility and distrusted the county government. Of our randomized scenarios, only the bill type was found to significantly influence WTP; WTP was higher if the surcharge was presented as a proportion of the customers’ last water bill vs a flat amount. Our findings suggest that in a sector that struggles to provide universal access to sanitation services, cross-subsidies may offer a means to support financing of safe sanitation for low-income households. These results indicate there are opportunities for cross-subsidies in urban Kenya that may be relevant for a wider understanding of surcharge payments that support basic services for low-income citizens.
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