How Much Will It Cost To Monitor Microbial Drinking Water Quality in Sub-Saharan Africa?

Centralized or Onsite Testing? Examining the Costs of Water Quality Monitoring in Rural Africa

Rural water systems in Africa have room to improve water quality monitoring. However, the most cost-effective approach for microbial water testing remains uncertain. This study compared the cost per E. coli test (membrane filtration) of four approaches representing different levels of centralization: (i) one centralized laboratory serving all water systems, (ii) a mobile laboratory serving all systems, (iii) multiple semi-centralized laboratories serving clusters of systems, and (iv) decentralized analysis at each system. We employed Monte Carlo analyses to model the costs of these approaches in three real-world contexts in Ghana and Uganda and in hypothetical simulations capturing various conditions across rural Africa. Centralized testing was the lowest cost in two real-world settings and the widest variety of simulations, especially those with water systems close to a central laboratory (<36 km). Semi-centralized testing was the lowest cost in one real-world setting and in simulations with clustered water systems and intermediate sampling frequencies (1-2 monthly samples per system). The mobile lab was the lowest cost in the fewest simulations, requiring few systems and infrequent sampling. Decentralized testing was cost-effective for remote systems and frequent sampling, but only if sampling did not require a dedicated vehicle. Alternative low-cost testing methods could make decentralized testing more competitive.

A rapid and specific antimicrobial resistance detection of Escherichia coli via magnetic nanoclusters

Drinking water contamination, often caused by bacteria, leads to substantial numbers of diarrhea deaths each year, especially in developing regions. Human urine as a source of fertilizer, when handled improperly, can contaminate drinking water. One dominant bacterial pathogen in urine is Escherichia coli, which can trigger serious waterborne/foodborne diseases. Considering the prevalence of the multi-drug resistant extended-spectrum beta-lactamase (ESBL) producing E. coli, a rapid detection method for resistance is highly desired. In this work, we developed a method for quick identification of E. coli and, at the same time, capable of removal of general bacterial pathogens from human urine. A specific peptide GRHIFWRRGGGHKVAPR, reported to have a strong affinity to E. coli, was utilized to modify the PEGylated magnetic nanoclusters, resulting in a specific capture and enrichment of E. coli from the bacteria-spiked artificial urine. Subsequently, a novel luminescent probe was applied to rapidly identify the antimicrobial resistance of the collected E. coli within 30 min. These functionalized magnetic nanoclusters demonstrate a promising prospect to rapidly detect ESBL E. coli in urine and contribute to reducing drinking water contamination.

Escherichia coli Contamination of Water for Human Consumption and Its Associated Factors in Peru: A Cross-Sectional Study

The objective of the study was to determine the factors associated with the presence of Escherichia coli contamination in water supplies for human consumption in Peru. A secondary analysis of the Food and Nutrition Surveillance by Life Stages survey (VIANEV) of 2017-2018 was performed. The presence of E. coli contamination in the water samples for human consumption of the households evaluated was defined as a dependent variable. A supply was considered contaminated when there was at least 1 colony-forming unit of E. coli in 100 mL of water for human consumption. Data from 886 participants were analyzed. It was found that 25.2% of household water supply sources for human consumption had E. coli at the time of sampling. Water reservoirs such as buckets or other containers (adjusted prevalence ratio [aPR]: 1.15; 95% confidence interval [CI]: 1.18-1.93), households belonging to a poor wealth quintile (aPR: 1.82; 95% CI: 1.01-3.25), residing in a rural area (aPR: 1.36; 95% CI: 1.01-1.83), and having a low human development index (aPR: 2.12; 95% CI: 1.15-3.91) were more likely to contain E. coli in water supplies for human consumption. However, households with chlorine concentrations of 0.5 mg/L or more in water (aPR: 0.20; 95% CI: 0.11-0.33) and with household members with a higher education (aPR: 0.67; 95% CI: 0.45-0.99) were less likely to contain E. coli in drinking-water supplies. From 2017 to 2018, one in four Peruvians had contamination by E. coli in the water supply to their homes, which was associated with sociodemographic factors, management, and water treatment.

Colorimetric Systems for the Detection of Bacterial Contamination: Strategy and Applications

Bacterial contamination is a public health concern worldwide causing enormous social and economic losses. For early diagnosis and adequate management to prevent or treat pathogen-related illnesses, extensive effort has been put into the development of pathogenic bacterial detection systems. Colorimetric sensing systems have attracted increasing attention due to their simple and single-site operation, rapid signal readout with the naked eye, ability to operate without external instruments, portability, compact design, and low cost. In this article, recent trends and advances in colorimetric systems for the detection and monitoring of bacterial contamination are reviewed. This article focuses on pathogen detection strategies and technologies based on reaction factors that affect the color change for visual readout. Reactions used in each strategy are introduced by dividing them into the following five categories: external pH change-induced pH indicator reactions, intracellular enzyme-catalyzed chromogenic reactions, enzyme-like nanoparticle (NP)-catalyzed substrate reactions, NP aggregation-based reactions, and NP accumulation-based reactions. Some recently developed colorimetric systems are introduced, and their challenges and strategies to improve the sensing performance are discussed.

A continuous, in-situ, near-time fluorescence sensor coupled with a machine learning model for detection of fecal contamination risk in drinking water: Design, characterization and field validation

We designed and validated a sensitive, continuous, in-situ, remotely reporting tryptophan-like fluorescence sensor and coupled it with a machine learning model to predict high-risk fecal contamination in water (>10 colony forming units (CFU)/100mL E. coli). We characterized the sensor's response to multiple fluorescence interferents with benchtop analysis. The sensor's minimum detection limit (MDL) of tryptophan dissolved in deionized water was 0.05 ppb (p <0.01) and its MDL of the correlation to E. coli present in wastewater effluent was 10 CFU/100 mL (p <0.01). Fluorescence response declined exponentially with increased water temperature and a correction factor was calculated. Inner filter effects, which cause signal attenuation at high concentrations, were shown to have negligible impact in an operational context. Biofouling was demonstrated to increase the fluorescence signal by approximately 82% in a certain context, while mineral scaling reduced the sensitivity of the sensor by approximately 5% after 24 hours with a scaling solution containing 8 times the mineral concentration of the Colorado River. A machine learning model was developed, with TLF measurements as the primary feature, to output fecal contamination risk levels established by the World Health Organization. A training and validation data set for the model was built by installing four sensors on Boulder Creek, Colorado for 88 days and enumerating 298 grab samples for E. coli with membrane filtration. The machine learning model incorporated a proxy feature for fouling (time since last cleaning) which improved model performance. A binary classification model was able to predict high risk fecal contamination with 83% accuracy (95% CI: 78% - 87%), sensitivity of 80%, and specificity of 86%. A model distinguishing between all World Health Organization established risk categories performed with an overall accuracy of 64%. Integrating TLF measurements into an ML model allows for anomaly detection and noise reduction, permitting contamination prediction despite biofilm or mineral scaling formation on the sensor's lenses. Real-time detection of high risk fecal contamination could contribute to a major step forward in terms of microbial water quality monitoring for human health.

From Fully Physical to Virtual Sensing for Water Quality Assessment: A Comprehensive Review of the Relevant State-of-the-Art

Rapid urbanization, industrial development, and climate change have resulted in water pollution and in the quality deterioration of surface and groundwater at an alarming rate, deeming its quick, accurate, and inexpensive detection imperative. Despite the latest developments in sensor technologies, real-time determination of certain parameters is not easy or uneconomical. In such cases, the use of data-derived virtual sensors can be an effective alternative. In this paper, the feasibility of virtual sensing for water quality assessment is reviewed. The review focuses on the overview of key water quality parameters for a particular use case and the development of the corresponding cost estimates for their monitoring. The review further evaluates the current state-of-the-art in terms of the modeling approaches used, parameters studied, and whether the inputs were pre-processed by interrogating relevant literature published between 2001 and 2021. The review identified artificial neural networks, random forest, and multiple linear regression as dominant machine learning techniques used for developing inferential models. The survey also highlights the need for a comprehensive virtual sensing system in an internet of things environment. Thus, the review formulates the specification book for the advanced water quality assessment process (that involves a virtual sensing module) that can enable near real-time monitoring of water quality.

Navigating Data Uncertainty and Modeling Assumptions in Quantitative Microbial Risk Assessment in an Informal Settlement in Kampala, Uganda

Decision-makers in developing communities often lack credible data to inform decisions related to water, sanitation, and hygiene. Quantitative microbial risk assessment (QMRA), which quantifies pathogen-related health risks across exposure routes, can be informative; however, the utility of QMRA for decision-making is often undermined by data gaps. This work integrates QMRA, uncertainty and sensitivity analyses, and household surveys in Bwaise, Kampala (Uganda) to characterize the implications of censored data management, identify sources of uncertainty, and incorporate risk perceptions to improve the suitability of QMRA for informal settlements or similar settings. In Bwaise, drinking water, hand rinse, and soil samples were collected from 45 households and supplemented with data from 844 surveys. Quantified pathogen (adenovirus, Campylobacter jejuni, and Shigella spp./EIEC) concentrations were used with QMRA to model infection risks from exposure through drinking water, hand-to-mouth contact, and soil ingestion. Health risks were most sensitive to pathogen data, hand-to-mouth contact frequency, and dose-response models (particularly C. jejuni). When managing censored data, results from upper limits of detection, half of limits of detection, and uniform distributions returned similar results, which deviated from lower limits of detection and maximum likelihood estimation imputation approaches. Finally, risk perceptions (e.g., it is unsafe to drink directly from a water source) were identified to inform risk management.

What Environmental Factors Influence the Concentration of Fecal Indicator Bacteria in Groundwater? Insights from Explanatory Modeling in Uganda and Bangladesh

Information about microbial water quality is critical for managing water safety and protecting public health. In low-income countries, monitoring all drinking water supplies is impractical because financial resources and capacity are insufficient. Data sets derived from satellite imagery, census, and hydrological models provide an opportunity to examine relationships between a suite of environmental risk factors and microbial water quality over large geographical scales. We investigated the relationships between groundwater fecal contamination and different environmental parameters in Uganda and Bangladesh. In Uganda, groundwater contamination was associated with high population density (p < 0.001; OR = 1.27), high cropland coverage (p < 0.001; OR = 1.47), high average monthly precipitation (p < 0.001; OR = 1.14), and high surface runoff (p < 0.001; OR = 1.37), while low groundwater contamination was more likely in areas further from cities (p < 0.001; OR = 0.66) and with higher forest coverage (p < 0.001; OR = 0.70). In Bangladesh, contamination was associated with higher weekly precipitation (p < 0.001; OR = 1.44) and higher livestock density (p = 0.05; OR = 1.11), while low contamination was associated with low forest coverage (p < 0.001; OR = 1.23) and high cropland coverage (p < 0.001; OR = 0.80). We developed a groundwater contamination index for each country to help decision-makers identify areas where groundwater is most prone to fecal contamination and prioritize monitoring activities. Our approach demonstrates how to harness satellite-derived data to guide water safety management.

Manual Borehole Drilling as a Cost-Effective Solution for Drinking Water Access in Low-Income Contexts

Water access remains a challenge in rural areas of low-income countries. Manual drilling technologies have the potential to enhance water access by providing a low cost drinking water alternative for communities in low and middle income countries. This paper provides an overview of the main successes and challenges experienced by manual boreholes in the last two decades. A review of the existing methods is provided, discussing their advantages and disadvantages and comparing their potential against alternatives such as excavated wells and mechanized boreholes. Manual boreholes are found to be a competitive solution in relatively soft rocks, such as unconsolidated sediments and weathered materials, as well as and in hydrogeological settings characterized by moderately shallow water tables. Ensuring professional workmanship, the development of regulatory frameworks, protection against groundwater pollution and standards for quality assurance rank among the main challenges for the future.

Designing the Next Generation of Fe0-Based Filters for Decentralized Safe Drinking Water Treatment: A Conceptual Framework

The ambitious United Nations Sustainable Development Goal for 2030 to “leave no one behind” concerning safe drinking water calls for the development of universally applicable and affordable decentralized treatment systems to provide safe drinking water. Published results suggest that well-designed biological sand filters (BSFs) amended with metallic iron (Fe0-BSFs) have the potential to achieve this goal. Fe0-BSFs quantitatively remove pathogens and a myriad of chemical pollutants. The available data were achieved under various operating conditions. A comparison of independent research results is almost impossible, especially because the used Fe0 materials are not characterized for their intrinsic reactivity. This communication summarizes the state-of-the-art knowledge on designing Fe0-BSFs for households and small communities. The results show that significant research progress has been made on Fe0-BSFs. However, well-designed laboratory and field experiments are required to improve the available knowledge in order to develop the next generation of adaptable and scalable designs of Fe0-BSFs in only two years. Tools to alleviate the permeability loss, the preferential flow, and the use of exhausted filters are presented.

How we assess water safety: A critical review of sanitary inspection and water quality analysis

Sanitary inspection is used in low-, medium- and high-income settings to assess the risk of microbial contamination at water sources. However, the relationship between sanitary inspection and water quality is not well understood. We conducted a critical literature review and synthesized the findings of 25 studies comparing the results of sanitary inspection and microbial water quality analysis. Most studies used sub-standard sanitary inspection and water quality analysis methods, and applied simplistic comparisons that do not characterize the complexity of the relationship. Sanitary risk score was used to represent sanitary inspection results in 21 (84%) studies; of which 12 (57%) found a significant association between score and microbial water quality and nine (43%) did not. Participatory sanitary inspection (12%) and reporting results back to communities (24%) were uncommon. Most studies relied on laboratory-based water quality analysis as an independently sufficient measure of safety, but reported inadequate quality control (52%) and/or sub-standard sample processing methods (66%). We found that sanitary inspections could contribute to improving water safety through four mechanisms: guiding remedial action at individual water sources, allowing operators and external support programs to prioritize repairs, identifying programmatic issues, and contributing to research. The purpose of the sanitary inspection should be considered when planning sanitary inspection execution, data analysis, and reporting to ensure appropriate methods are employed and results are fit for purpose. Further exploration should recognize that sanitary risk factors represent sources of contamination, pathways for contaminants to enter water supplies, and breakdowns in barriers to contamination. These different sanitary risk factor types have different and inter-dependent effects on water quality.

Demonstration of Tryptophan-Like Fluorescence Sensor Concepts for Fecal Exposure Detection in Drinking Water in Remote and Resource Constrained Settings

Low-cost, field-deployable, near-time methods for assessing water quality are not available when and where waterborne infection risks are greatest. We describe the development and testing of a novel device for the measurement of tryptophan-like fluorescence (TLF), making use of recent advances in deep-ultraviolet light emitting diodes (UV-LEDs) and sensitive semiconductor photodiodes and photomultipliers. TLF is an emerging indicator of water quality that is associated with members of the coliform group of bacteria and therefore potential fecal contamination. Following the demonstration of close correlation between TLF and E. coli in model waters and proof of principle with sensitivity of 4 CFU/mL for E. coli, we further developed a two-LED flow-through configuration capable of detecting TLF levels corresponding to “high risk” fecal contamination levels (>10 CFU/100 mL). Findings to date suggest that this device represents a scalable solution for remote monitoring of drinking water supplies to identify high-risk drinking water in near-time. Such information can be immediately actionable to reduce risks.

Capacity challenges in water quality monitoring: understanding the role of human development

Monitoring the qualitative status of freshwaters is an important goal of the international community, as stated in the Sustainable Development Goal (SDGs) indicator 6.3.2 on good ambient water quality. Monitoring data are, however, lacking in many countries, allegedly because of capacity challenges of less-developed countries. So far, however, the relationship between human development and capacity challenges for water quality monitoring have not been analysed systematically. This hinders the implementation of fine-tuned capacity development programmes for water quality monitoring. Against this background, this study takes a global perspective in analysing the link between human development and the capacity challenges countries face in their national water quality monitoring programmes. The analysis is based on the latest data on the human development index and an international online survey amongst experts from science and practice. Results provide evidence of a negative relationship between human development and the capacity challenges to meet SDG 6.3.2 monitoring requirements. This negative relationship increases along the course of the monitoring process, from defining the enabling environment, choosing parameters for the collection of field data, to the analytics and analysis of five commonly used parameters (DO, EC, pH, TP and TN). Our assessment can be used to help practitioners improve technical capacity development activities and to identify and target investment in capacity development for monitoring.

Fieldwork-based determination of design priorities for point-of-use drinking water quality sensors for use in resource-limited environments

Improved capabilities in microfluidics, electrochemistry, and portable assays have resulted in the development of a wide range of point-of-use sensors intended for environmental, medical, and agricultural applications in resource-limited environments of developing countries. However, these devices are frequently developed without direct interaction with their often-remote intended user base, creating the potential for a disconnect between users' actual needs and those perceived by sensor developers. As different analytical techniques have inherent strengths and limitations, effective measurement solution development requires determination of desired sensor attributes early in the development process. In this work, we present our findings on design priorities for point-of-use microbial water sensors based on fieldwork in rural India, as well as a guide to fieldwork methodologies for determining desired sensor attributes. We utilized group design workshops for initial identification of design priorities, and then conducted choice-based conjoint analysis interviews for quantification of user preferences among these priorities. We found the highest user preference for integrated reporting of contaminant concentration and recommended actions, as well as significant preferences for mostly reusable sensor architectures, same-day results, and combined ingredients. These findings serve as a framework for future microbial sensor development and a guide for fieldwork-based understanding of user needs.

The efficiency of a low-cost hydrogen sulphide (H2S) kit as an early warning test for assessing microbial rainwater quality and its correlation with standard indicators microorganisms

Testing microbial quality of the harvested rainwater remains a challenge in many countries. The H2S test kit is a low-cost microbiological field-based test which can be used in areas where water testing facilities are limited. This study compares its efficiency with the standard indicators microorganisms in the detection of faecal contamination of rainwater in South Africa. A total of 88 rainwater samples were collected from various tanks in the Eastern Cape, South Africa over three months in 2016. The collected samples were analysed for faecal bacterial contamination using the H2S test kit, Colilert-18/Quanti-tray®/2000 and the membrane filtration technique for faecal coliforms (MFT). The correspondence rate of the H2S test kit with MFT was 88 %, while for the Colilert®it was 76 %. The H2S test kit confirmed faecal contamination when concentrations of standards indicators microorganisms were 5 most-probable number of cells/100 cm3or higher. Overall, the best correspondence of the H2S test kit with Colilert®was observed atE. coliconcentrations above 50 most-probable number of cells/100 cm3. Results of the H2S test kit correlated better with MTF, while the medium used has strongly influenced the enumeration of faecal contamination. Results point to strong effect of media used and revealed the need to calibrate the correspondence between the standard indicator microorganisms and the H2S test kit under local conditions for specific settings.

Making Rainwater Harvesting a Key Solution for Water Management: The Universality of the Kilimanjaro Concept

Rainwater is conventionally perceived as an alternative drinking water source, mostly needed to meet water demand under particular circumstances, including under semi-arid conditions and on small islands. More recently, rainwater has been identified as a potential source of clean drinking water in cases where groundwater sources contain high concentrations of toxic geogenic contaminants. Specifically, this approach motivated the introduction of the Kilimanjaro Concept (KC) to supply fluoride-free water to the population of the East African Rift Valley (EARV). Clean harvested rainwater can either be used directly as a source of drinking water or blended with polluted natural water to meet drinking water guidelines. Current efforts towards the implementation of the KC in the EARV are demonstrating that harvesting rainwater is a potential universal solution to cover ever-increasing water demands while limiting adverse environmental impacts such as groundwater depletion and flooding. Indeed, all surface and subsurface water resources are replenished by precipitation (dew, hail, rain, and snow), with rainfall being the main source and major component of the hydrological cycle. Thus, rainwater harvesting systems entailing carefully harvesting, storing, and transporting rainwater are suitable solutions for water supply as long as rain falls on earth. Besides its direct use, rainwater can be infiltrating into the subsurface when and where it falls, thereby increasing aquifer recharge while minimizing soil erosion and limiting floods. The present paper presents an extension of the original KC by incorporating Chinese experience to demonstrate the universal applicability of the KC for water management, including the provision of clean water for decentralized communities.

Bacterial contamination of drinking water sources in rural villages of Mohale Basin, Lesotho: exposures through neighbourhood sanitation and hygiene practices

Background

Bacterial contamination of drinking water is a major public health problem in rural areas of sub-Saharan Africa. Unimproved water sources are a major reservoir of Escherichia coli (E. coli) causing severe diarrhoea in humans. This study assessed E. coli counts in drinking water from different sources and their relationship with water source protection status and neighbourhood sanitation and hygiene practices in rural villages of Mohale Basin in Lesotho.

Methods

Thirty drinking water sources were purposively sampled and their water analysed for E. coli counts. The types of water sources, their protection status and neighbourhood sanitation and hygiene practices in their proximity were also assessed. E. coli counts in water samples were compared to water source protection status, neighbourhood sanitation, hygiene practices, livestock faeces and latrine proximity to water sources.

Results

E. coli counts were found in all water samples and ranged from less than 30 colony-forming units (cfu)/100 ml to 4800 cfu/100 ml in protected sources to 43,500,000 cfu/100 ml in unprotected sources. A significant association between E. coli counts in drinking water samples and lack of water source protection, high prevalence of open defecation (59%, n = 100), unhygienic practices, livestock faeces and latrine detections in proximity to water sources was found in the study (P < 0.05).

Conclusion

Water sources in studied villages were contaminated with faeces and posed a health risk to consumers of that water. Community-led sanitation and hygiene education and better water source protection are urgently needed.

Near real-time enumeration of live and dead bacteria using a fibre-based spectroscopic device

A rapid, cost-effective and easy method that allows on-site determination of the concentration of live and dead bacterial cells using a fibre-based spectroscopic device (the optrode system) is proposed and demonstrated. Identification of live and dead bacteria was achieved by using the commercially available dyes SYTO 9 and propidium iodide, and fluorescence spectra were measured by the optrode. Three spectral processing methods were evaluated for their effectiveness in predicting the original bacterial concentration in the samples: principal components regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR). Without any sample pre-concentration, PCR achieved the most reliable results. It was able to quantify live bacteria from 108 down to 106.2 bacteria/mL and showed the potential to detect as low as 105.7 bacteria/mL. Meanwhile, enumeration of dead bacteria using PCR was achieved between 108 and 107 bacteria/mL. The general procedures described in this article can be applied or modified for the enumeration of bacteria within populations stained with fluorescent dyes. The optrode is a promising device for the enumeration of live and dead bacterial populations particularly where rapid, on-site measurement and analysis is required.

Are Presence/Absence Microbial Tests Appropriate for Monitoring Large Urban Water Supplies in Sub-Saharan Africa?

Screening for fecal contamination via microbial water quality monitoring is a critical component of safe drinking water provision and public health protection. Achieving adequate levels of microbial water quality testing, however, is a challenge in resource-limited settings. One strategy for addressing this challenge is to improve the efficiency of monitoring programs. In African countries, quantitative microbial testing methods are commonly used to monitor chlorinated piped water systems. However, presence/absence (P/A) tests may provide an appropriate alternative for water supplies that generally show negative fecal contamination results. This study compares 1048 water quality test results for samples collected from five African urban water systems. The operators of the systems conducted parallel tests on the 1048 samples using their standard quantitative methods (e.g., most probable number or membrane filtration) and the Colitag™ method in P/A format. Combined data demonstrates agreement rates of 97.9% (1024/1046) for detecting total coliforms and 97.8% (1025/1048) for detecting E. coli. We conclude that the P/A test offers advantages as a simpler and similarly sensitive measure of potential fecal contamination for large, urban chlorinated water systems. P/A tests may also offer a cost-effective alternative to quantitative methods, as they are quicker to perform and require less laboratory equipment.

Why do water quality monitoring programs succeed or fail? A qualitative comparative analysis of regulated testing systems in sub-Saharan Africa

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.