Comparison and cost analysis of drinking water quality monitoring requirements versus practice in seven developing countries

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.

Appraisal of machine learning techniques for predicting emerging disinfection byproducts in small water distribution networks

Monitoring emerging disinfection byproducts (DBPs) is challenging for many small water distribution networks (SWDNs), and machine learning-based predictive modeling could be an alternative solution. In this study, eleven machine learning techniques, including three multivariate linear regression-based, three regression tree-based, three neural networks-based, and two advanced non-parametric regression techniques, are used to develop models for predicting three emerging DBPs (dichloroacetonitrile, chloropicrin, and trichloropropanone) in SWDNs. Predictors of the models include commonly-measured water quality parameters and two conventional DBP groups. Sampling data of 141 cases were collected from eleven SWDNs in Canada, in which 70 % were randomly selected for model training and the rest were used for validation. The modeling process was reiterated 1000 times for each model. The results show that models developed using advanced regression techniques, including support vector regression and Gaussian process regression, exhibited the best prediction performance. Support vector regression models showed the highest prediction accuracy (R² =0.94) and stability for predicting dichloroacetonitrile and trichloropropanone, and Gaussian process regression models are optimal for predicting chloropicrin (R² =0.92). The difference is likely due to the much lower concentrations of chloropicrin than dichloroacetonitrile and trichloropropanone. Advanced non-parametric regression techniques, characterized by a probabilistic nature, were identified as most suitable for developing the predictive models, followed by neural network-based (e.g., generalized regression neural network), regression tree-based (e.g., random forest), and multivariate linear regression-based techniques. This study identifies promising machine learning techniques among many commonly-used alternatives for monitoring emerging DBPs in SWDNs under data constraints.

Advances in Technological Research for Online and In Situ Water Quality Monitoring—A Review

Monitoring water quality is an essential tool for the control of pollutants and pathogens that can cause damage to the environment and human health. However, water quality analysis is usually performed in laboratory environments, often with the use of high-cost equipment and qualified professionals. With the progress of nanotechnology and the advance in engineering materials, several studies have shown, in recent years, the development of technologies aimed at monitoring water quality, with the ability to reduce the costs of analysis and accelerate the achievement of results for management and decision-making. In this work, a review was carried out on several low-cost developed technologies and applied in situ for water quality monitoring. Thus, new alternative technologies for the main physical (color, temperature, and turbidity), chemical (chlorine, fluorine, phosphorus, metals, nitrogen, dissolved oxygen, pH, and oxidation–reduction potential), and biological (total coliforms, Escherichia coli, algae, and cyanobacteria) water quality parameters were described. It was observed that there has been an increase in the number of publications related to the topic in recent years, mainly since 2012, with 641 studies being published in 2021. The main new technologies developed are based on optical or electrochemical sensors, however, due to the recent development of these technologies, more robust analyses and evaluations in real conditions are essential to guarantee the precision and repeatability of the methods, especially when it is desirable to compare the values with government regulatory standards.

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.

Iron oxide xerogels for improved water quality monitoring of arsenic(III) in resource-limited environments via solid-phase extraction, preservation, storage, transportation, and analysis of trace contaminants (SEPSTAT)

Arsenic is a widespread trace groundwater contaminant that presents a range of health risks and has an acceptable level of only 10 μg L-1 in drinking water. However, in many countries arsenic quantification in water is limited to centralized laboratories because it requires the use of elemental analysis techniques with high capital cost. As a result, routine water samples are frequently not tested for trace contaminants such as arsenic. In order to facilitate improved arsenic monitoring, we present the use of iron oxide xerogels for adsorption of arsenic(iii) from water samples at neutral pH, dry storage for over 120 days, and desorption of stored arsenic at elevated pH. Iron oxide xerogels offer high surface area (340 m2 g-1) and an As(iii) adsorption capacity of 165 mg g-1. Using an extraction solution of 100 mM sodium hydroxide and 1 mM sodium phosphate, As(iii) is reliably eluted from iron oxide xerogels for initial As(iii) concentrations from 10 μg L-1 to 1000 μg L-1, with a calculated detection limit of less than 4 μg L-1 and less than 17% difference in recovered As(iii) between test solutions with low and high interfering ion concentrations. By demonstrating the ability for iron oxide xerogels to reliably adsorb, store, and release arsenic, we enable the development of protocols for solid-phase extraction, preservation, storage, transportation, and analysis of trace contaminants (SEPSTAT), where arsenic would be adsorbed from water samples onto xerogel-based sorbents and shipped to centralized laboratories for recovery and quantification.

A Review of Microfluidic Detection Strategies for Heavy Metals in Water

Heavy metal pollution of water has become a global issue and is especially problematic in some developing countries. Heavy metals are toxic to living organisms, even at very low concentrations. Therefore, effective and reliable heavy metal detection in environmental water is very important. Current laboratory-based methods used for analysis of heavy metals in water require sophisticated instrumentation and highly trained technicians, making them unsuitable for routine heavy metal monitoring in the environment. Consequently, there is a growing demand for autonomous detection systems that could perform in situ or point-of-use measurements. Microfluidic detection systems, which are defined by their small size, have many characteristics that make them suitable for environmental analysis. Some of these advantages include portability, high sample throughput, reduced reagent consumption and waste generation, and reduced production cost. This review focusses on developments in the application of microfluidic detection systems to heavy metal detection in water. Microfluidic detection strategies based on optical techniques, electrochemical techniques, and quartz crystal microbalance are discussed.

Proposed formulation of surface water quality and modelling using gene expression, machine learning, and regression techniques

The rising water pollution from anthropogenic factors motivates further research in developing water quality predicting models. The available models have certain limitations due to limited timespan data and the incapability to provide empirical expressions. This study is devoted to model and derive empirical equations for surface water quality of upper Indus river basin using a 30-year dataset with machine learning techniques and then to determine the most reliable model capable to accurately predict river water quality. Total dissolve solids (TDS) and electrical conductivity (EC) were used as dependent variables, whereas eight parameters were used as independent variables with 70 and 30% data for model training and testing, respectively. Various evaluation criteria, i.e., Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE), were used to assess the performance of models. The data is also validated with the help of k-fold cross-validation using R² and RMSE. The results indicated a strong correlation with NSE and R² both above 0.85 for all the developed models. Gene expression programming (GEP) outperformed both artificial neural network (ANN) and linear and non-linear regression models for TDS and EC. The sensitivity and parametric analyses revealed that bicarbonate is the most sensitive parameter influencing both TDS and EC models. Two equations were derived and formulated to represent the novel results of GEP model to help authorities in the effective monitoring of river water quality.

Water quality, sanitation, and hygiene among the tribal community residing in Jawadhi hills, Tamilnadu: An observational study from Southern India

Objectives:

To assess the water, sanitation, and hygiene (WASH) practice among the tribal population of Tamil Nadu, India and to determine the physiochemical and bacteriological quality of drinking water at the principal source and at the households along with the household-level determinants of WASH practices.

Methods:

A door-to-door survey was conducted in 150 households, distributed across six villages of Jawadhi hills, a tribal area in the state of Tamil Nadu, India. Water samples were collected from the principal sources and a subset of households for assessing water quality. A composite scoring was formulated to determine the overall WASH practices.

Results:

Overall, a poor WASH score (≤4) was found in 103 (68.7%; 95% CI: 60.7, 75.6) households. The majority (96.7%) of the household water samples showed the presence of fecal coliforms. Poor WASH score was uniformly distributed across the villages. Low per capita income (≤1000 INR) was strongly associated with the poor WASH score (Adjusted OR 2.4; 95% CI: 1.04, 5.7). The per capita income had a strong negative association with the high fecal coliform count (Adjusted OR 5.07; 95% CI: 1.08, 23.74).

Conclusions:

We conclude that WASH-related practices among the tribal population of Tamil Nadu is not acceptable. The lack of administrative function and poor economic conditions are the likely causes attributed to the poor WASH conditions and drinking water quality. Urgent action from the stakeholders is the need of the hour to improve the water quality and living standards of such marginalized populations.

Predicting unregulated disinfection by-products in small water distribution networks: an empirical modelling framework

Disinfection is used to deactivate pathogens in drinking water. However, disinfectants react with natural organic matter present in water to form disinfection by-products (DBPs). While a few of these DBPs have been studied extensively and are regulated in many countries, new unregulated DBPs (UR-DBPs) have also recently been identified in drinking water. The UR-DBPs are considered to be more toxic than regulated DBPs (R-DBPs). To understand the occurrence of UR-DBPs in a water distribution network (WDN), this research presents an approach to predicting the behaviour of emerging UR-DBPs such as dichloroacetonitrile (DCAN), trichloropropanone (TCP), and trichloronitromethane (TCNM) in WDNs. Water quality data, generated by sampling and laboratory analysis of 12 small communities, was used to develop predictive models. A framework was also proposed alongside the predictive models to estimate the concentration of emerging UR-DBPs under limited water quality sampling information. Moreover, the relationship between emerging UR-DBP concentrations and their identified predictors was further observed and evaluated by developing contour profiles. DCAN and TCP predictive models have coefficient of determination (R²) > 85%, whereas for TCNM model, the R² was > 65%. Water quality parameters including water temperature, turbidity, conductivity, and dissolved organic carbon concentrations were identified as key predictors. Similarly, trichloroacetic acid and bromodichloromethane were identified as key predictors among DBP families, to predict the occurrence of emerging UR-DBPs. Developed models and relationships between the UR-DBPs and predictors can help water utilities and regulators to manage the occurrence of UR-DBPs in small WDNs.

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.

Integrated Electrochemical Biosensors for Detection of Waterborne Pathogens in Low-Resource Settings

More than 783 million people worldwide are currently without access to clean and safe water. Approximately 1 in 5 cases of mortality due to waterborne diseases involve children, and over 1.5 million cases of waterborne disease occur every year. In the developing world, this makes waterborne diseases the second highest cause of mortality. Such cases of waterborne disease are thought to be caused by poor sanitation, water infrastructure, public knowledge, and lack of suitable water monitoring systems. Conventional laboratory-based techniques are inadequate for effective on-site water quality monitoring purposes. This is due to their need for excessive equipment, operational complexity, lack of affordability, and long sample collection to data analysis times. In this review, we discuss the conventional techniques used in modern-day water quality testing. We discuss the future challenges of water quality testing in the developing world and how conventional techniques fall short of these challenges. Finally, we discuss the development of electrochemical biosensors and current research on the integration of these devices with microfluidic components to develop truly integrated, portable, simple to use and cost-effective devices for use by local environmental agencies, NGOs, and local communities in low-resource settings.

Solid-Phase Extraction, Preservation, Storage, Transport, and Analysis of Trace Contaminants for Water Quality Monitoring of Heavy Metals

Accurate quantification of trace contaminants currently requires collection, preservation, and transportation of large volumes (250-1000 mL) of water to centralized laboratories, which impedes monitoring of trace-level pollutants in many resource-limited environments. To overcome this logistical challenge, we propose a new paradigm for trace contaminant monitoring based on dry preservation: solid-phase extraction, preservation, storage, transport, and analysis of trace contaminants (SEPSTAT). We show that a few grams of low-cost, commercially available cation exchange resin can be repurposed to extract heavy metal cations from water samples even in the presence of background ions, dryly preserve these cations for at least 24 months, and release them by acid elution for accurate quantification. A compact, human-powered device incorporating the sorbent removes spiked contaminants from real water samples in a few minutes. The device can be stored and transported easily and produces a sample suitable for measurement by standard methods, predicting the original sample heavy metal concentration generally within an error of 15%. These results suggest that, by facilitating the collection, storage, handling, and transportation of water samples and by enabling cost-effective use of high-throughput capital-intensive instruments, SEPSTAT has the potential to increase the ease and reach of water quality monitoring of trace contaminants.

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.

Low Cost Wavelength Specific Water Quality Measurement Technique

Optical sensing for chemical analysis is emerging as it provides advantages such as good sensitivity, selectivity, electromagnetic immunity, etc. This work presents a low-cost, robust and easy to use technique for measurement of bulk water property changes, specifically pH, total dissolved solids (TDS), and turbidity. The designed multi-wavelength sensing mechanism is capable of measuring the absorption of light emitted by three different LEDs after passing through water. The optical responses obtained using this mechanism are then related to parameter changes of water for quality measurement. The results show that measurements for pH, TDS, and turbidity have a linear regression coefficient of 0.9691, 0.9729 and 0.76 respectively. By utilizing narrowband light sources of characteristic wavelengths for the target parameters, a compact and portable device can be designed for rapid measurements. This can work as a replacement of spectrophotometers for parameter specific measurements of water quality and a low cost prototype (costing ~ 20 $) for the same has been demonstrated.

Drinking Water Quality Monitoring: An Alternative Approach to Microbial Contamination Events

The nonstop growing of world population and consequent increase in water demands, as raise the interest in continuous and real-time drinking water monitoring systems. The following study aims to study Tryptophan Intrinsic Fluorescence as a method for detecting microbial contamination events in drinking water.

Low Power Consumption device for Biological Stability Monitoring in Drinking Water

Water monitoring has an unquestionable value for people's safety. Despite this, most systems are expensive to operate due to high power consumption or high measuring time. This translates to an inefficient system. This study proposes a design for a low power consumption system to monitor water quality. By using a simple 3D printed design that includes UV LEDs, a filter, a lens and a photosensor. The tests performed in this paper is to show the effect the lens provides and the limited power consumption of the overall system as well as the sensitivity of the system.

Continuous and Real-Time Detection of Drinking-Water Pathogens with a Low-Cost Fluorescent Optofluidic Sensor

Growing access to tap water and consequent expansion of water distribution systems has created numerous challenges to maintaining water quality between the treatment node and final consumer. Despite all efforts to develop sustainable monitoring systems, there is still a lack of low cost, continuous and real time devices that demonstrate potential for large-scale implementation in wide water distribution networks. The following work presents a study of a low-cost, optofluidic sensor, based on Trypthopan Intrinsic Fluorescence. The fluorospectrometry analysis performed (before sensor development) supports the existence of a measurable fluorescence output signal originating from the tryptophan contained within pathogenic bacteria. The sensor was mounted using a rapid prototyping technique (3D printing), and the integrated optical system was achieved with low-cost optical components. The sensor performance was evaluated with spiked laboratory samples containing E. coli and Legionella, in both continuous and non-continuous flow situations. Results have shown a linear relationship between the signal measured and pathogen concentration, with limits of detection at 1.4 × 10³ CFU/mL. The time delay between contamination and detection of the bacteria was practically null. Therefore, this study supports the potential application of tryptophan for monitoring drinking water against water pathogens.

Locally produced hydrogen sulphide detecting water quality test kits increase household level monitoring in rural Tanzania

In developing countries, rural water sources have the highest levels of faecal contamination but are the least monitored. Affordable field-based water quality tests are needed. The presence of faecal indicator bacteria can be determined with hydrogen sulphide (H₂S) detecting tests, that are inexpensive and simple to make locally. In rural Tanzania, a non-governmental organisation (NGO) designed, produced and evaluated a new H₂S water quality test kit. The H₂S test results correlated with log₁₀ Escherichia coli densities from conventional water quality tests. The production cost was US$ 1.10 and the test retailed for US$ 1.37. In total, 433 tests were sold through local pharmacies and NGOs. Additionally, 165 WaSH education meetings, reaching 3,408 community members, were conducted with the H₂S test demonstrated in over half the meetings. Pre- and post-surveys of 294 meeting participants saw an increased reporting of household level water treatment by 24%. The H₂S test was widely accepted, with 94% of those surveyed willing to buy the test in the future. International and national guidelines for drinking water monitoring need to be amended to include locally produced H₂S water quality tests. This will enable households to monitor their own water sources and make informed choices about water safety and treatment.

Efficacy of microbial sampling recommendations and practices in sub-Saharan Africa

Current guidelines for testing drinking water quality recommend that the sampling rate, which is the number of samples tested for fecal indicator bacteria (FIB) per year, increases as the population served by the drinking water system increases. However, in low-resource settings, prevalence of contamination tends to be higher, potentially requiring higher sampling rates and different statistical methods not addressed by current sampling recommendations. We analyzed 27,930 tests for FIB collected from 351 piped water systems in eight countries in sub-Saharan Africa to assess current sampling rates, observed contamination prevalences, and the ability of monitoring agencies to complete two common objectives of sampling programs: determine regulatory compliance and detect a change over time. Although FIB were never detected in samples from 75% of piped water systems, only 14% were sampled often enough to conclude with 90% confidence that the true contamination prevalence met an example guideline (≤5% chance of any sample positive for FIB). Similarly, after observing a ten percentage point increase in contaminated samples, 43% of PWS would still require more than a year before their monitoring agency could be confident that contamination had actually increased. We conclude that current sampling practices in these settings may provide insufficient information because they collect too few samples. We also conclude that current guidelines could be improved by specifying how to increase sampling after contamination has been detected. Our results suggest that future recommendations should explicitly consider the regulatory limit and desired confidence in results, and adapt when FIB is detected.

Physicochemical parameters affecting the perception of borehole water quality in Ghana

Rural Ghanaian communities continue using microbiologically contaminated surface water sources due in part to undesirable organoleptic characteristics of groundwater from boreholes. Our objective was to identify thresholds of physical and chemical parameters associated with consumer complaints related to groundwater. Water samples from 94 boreholes in the dry season and 68 boreholes in the rainy season were analyzed for 18 parameters. Interviews of consumers were conducted at each borehole regarding five commonly expressed water quality problems (salty taste, presence of particles, unfavorable scent, oily sheen formation on the water surface, and staining of starchy foods during cooking). Threshold levels of water quality parameters predictive of complaints were determined using the Youden index maximizing the sum of sensitivity and specificity. The probability of complaints at various parameter concentrations was estimated using logistic regression. Exceedances of WHO guidelines were detected for pH, turbidity, chloride, iron, and manganese. Concentrations of total dissolved solids (TDS) above 172mg/L were associated with salty taste complaints. Although the WHO guideline is 1000mg/L, even at half the guideline, the likelihood of salty taste complaint was 75%. Iron concentrations above 0.11, 0.14 and 0.43mg/L (WHO guideline value 0.3mg/L) were associated with complaints of unfavorable scent, oily sheen, and food staining, respectively. Iron and TDS concentrations exhibited strong spatial clustering associated with specific geological formations. Improved groundwater sources in rural African communities that technically meet WHO water quality guidelines may be underutilized in preference of unimproved sources for drinking and domestic uses, compromising human health and sustainability of improved water infrastructure.

Household Microbial Water Quality Testing in a Peruvian Demographic and Health Survey: Evaluation of the Compartment Bag Test for Escherichia coli

AbstractThe Joint Monitoring Program relies on household surveys to classify access to improved water sources instead of measuring microbiological quality. The aim of this research was to pilot a novel test for Escherichia coli quantification of household drinking water in the 2011 Demographic and Health Survey (DHS) in Peru. In the Compartment Bag Test (CBT), a 100-mL water sample is supplemented with chromogenic medium to support the growth of E. coli, poured into a bag with compartments, and incubated. A color change indicates E. coli growth, and the concentration of E. coli/100 mL is estimated as a most probable number. Triplicate water samples from 704 households were collected; one sample was analyzed in the field using the CBT, another replicate sample using the CBT was analyzed by reference laboratories, and one sample using membrane filtration (MF) was analyzed by reference laboratories. There were no statistically significant differences in E. coli concentrations between the field and laboratory CBT results, or when compared with MF results. These results suggest that the CBT for E. coli is an effective method to quantify fecal bacteria in household drinking water. The CBT can be incorporated into DHS and other national household surveys as a direct measure of drinking water safety based on microbial quality to better document access to safe drinking water.

Multifunctional Water Sensors for pH, ORP, and Conductivity Using Only Microfabricated Platinum Electrodes

Monitoring of the pH, oxidation-reduction-potential (ORP), and conductivity of aqueous samples is typically performed using multiple sensors. To minimize the size and cost of these sensors for practical applications, we have investigated the use of a single sensor constructed with only bare platinum electrodes deposited on a glass substrate. The sensor can measure pH from 4 to 10 while simultaneously measuring ORP from 150 to 800 mV. The device can also measure conductivity up to 8000 μS/cm in the range of 10 °C to 50 °C, and all these measurements can be made even if the water samples contain common ions found in residential water. The sensor is inexpensive (i.e., ~$0.10/unit) and has a sensing area below 1 mm², suggesting that the unit is cost-efficient, robust, and widely applicable, including in microfluidic systems.

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

Microbial water quality monitoring is crucial for managing water resources and protecting public health. However, institutional testing activities in sub-Saharan Africa are currently limited. Because the economics of water quality testing are poorly understood, the extent to which cost may be a barrier to monitoring in different settings is unclear. This study used cost data from 18 African monitoring institutions (piped water suppliers and health surveillance agencies in six countries) and estimates of water supply type coverage from 15 countries to assess the annual financial requirements for microbial water testing at both national and regional levels, using World Health Organization recommendations for sampling frequency. We found that a microbial water quality test costs 21.0 ± 11.3 USD, on average, including consumables, equipment, labor, and logistics, which is higher than previously calculated. Our annual cost estimates for microbial monitoring of piped supplies and improved point sources ranged between 8 000 USD for Equatorial Guinea and 1.9 million USD for Ethiopia, depending primarily on the population served but also on the distribution of piped water system sizes. A comparison with current national water and sanitation budgets showed that the cost of implementing prescribed testing levels represents a relatively modest proportion of existing budgets (<2%). At the regional level, we estimated that monitoring the microbial quality of all improved water sources in sub-Saharan Africa would cost 16.0 million USD per year, which is minimal in comparison to the projected annual capital costs of achieving Sustainable Development Goal 6.1 of safe water for all (14.8 billion USD).

Can Sanitary Surveys Replace Water Quality Testing? Evidence from Kisii, Kenya

Information about the quality of rural drinking water sources can be used to manage their safety and mitigate risks to health. Sanitary surveys, which are observational checklists to assess hazards present at water sources, are simpler to conduct than microbial tests. We assessed whether sanitary survey results were associated with measured indicator bacteria levels in rural drinking water sources in Kisii Central, Kenya. Overall, thermotolerant coliform (TTC) levels were high: all of the samples from the 20 tested dug wells, almost all (95%) of the samples from the 25 tested springs, and 61% of the samples from the 16 tested rainwater harvesting systems were contaminated with TTC. There were no significant associations between TTC levels and overall sanitary survey scores or their individual components. Contamination by TTC was associated with source type (dug wells and springs were more contaminated than rainwater systems). While sanitary surveys cannot be substituted for microbial water quality results in this context, they could be used to identify potential hazards and contribute to a comprehensive risk management approach.

Quantifying tap-to-household water quality deterioration in urban communities in Vellore, India: The impact of spatial assumptions

Municipal water sources in India have been found to be highly contaminated, with further water quality deterioration occurring during household storage. Quantifying water quality deterioration requires knowledge about the exact source tap and length of water storage at the household, which is not usually known. This study presents a methodology to link source and household stored water, and explores the effects of spatial assumptions on the association between tap-to-household water quality deterioration and enteric infections in two semi-urban slums of Vellore, India. To determine a possible water source for each household sample, we paired household and tap samples collected on the same day using three spatial approaches implemented in GIS: minimum Euclidean distance; minimum network distance; and inverse network-distance weighted average. Logistic and Poisson regression models were used to determine associations between water quality deterioration and household-level characteristics, and between diarrheal cases and water quality deterioration. On average, 60% of households had higher fecal coliform concentrations in household samples than at source taps. Only the weighted average approach detected a higher risk of water quality deterioration for households that do not purify water and that have animals in the home (RR=1.50 [1.03, 2.18], p=0.033); and showed that households with water quality deterioration were more likely to report diarrheal cases (OR=3.08 [1.21, 8.18], p=0.02). Studies to assess contamination between source and household are rare due to methodological challenges and high costs associated with collecting paired samples. Our study demonstrated it is possible to derive useful spatial links between samples post hoc; and that the pairing approach affects the conclusions related to associations between enteric infections and water quality deterioration.

To What Extent is Drinking Water Tested in Sub-Saharan Africa? A Comparative Analysis of Regulated Water Quality Monitoring

Water quality information is important for guiding water safety management and preventing water-related diseases. To assess the current status of regulated water quality monitoring in sub-Saharan Africa, we evaluated testing programs for fecal contamination in 72 institutions (water suppliers and public health agencies) across 10 countries. Data were collected through written surveys, in-person interviews, and analysis of microbial water quality testing levels. Though most institutions did not achieve the testing levels specified by applicable standards or World Health Organization (WHO) Guidelines, 85% of institutions had conducted some microbial water testing in the previous year. Institutions were more likely to meet testing targets if they were suppliers (as compared to surveillance agencies), served larger populations, operated in urban settings, and had higher water quality budgets (all p < 0.05). Our results indicate that smaller water providers and rural public health offices will require greater attention and additional resources to achieve regulatory compliance for water quality monitoring in sub-Saharan Africa. The cost-effectiveness of water quality monitoring should be improved by the application of risk-based water management approaches. Efforts to strengthen monitoring capacity should pay greater attention to program sustainability and institutional commitment to water safety.

Evaluation of an Inexpensive Growth Medium for Direct Detection of Escherichia coli in Temperate and Sub-Tropical Waters

The cost and complexity of traditional methods for the detection of faecal indicator bacteria, including E. coli, hinder widespread monitoring of drinking water quality, especially in low-income countries and outside controlled laboratory settings. In these settings the problem is exacerbated by the lack of inexpensive media for the detection of E. coli in drinking water. We developed a new low-cost growth medium, aquatest (AT), and validated its use for the direct detection of E. coli in temperate and sub-tropical drinking waters using IDEXX Quanti-Tray^®. AT was compared with IDEXX Colilert-18^® and either EC-MUG or MLSB for detecting low levels of E. coli from water samples from temperate (n = 140; Bristol, UK) and subtropical regions (n = 50, Pretoria/Tshwane, South Africa). Confirmatory testing (n = 418 and 588, respectively) and the comparison of quantitative results were used to assess performance. Sensitivity of AT was higher than Colilert-18^® for water samples in the UK [98.0% vs. 86.9%; p<0.0001] and South Africa [99.5% vs. 93.2%; p = 0.0030]. There was no significant difference in specificity, which was high for both media (>95% in both settings). Quantitative results were comparable and within expected limits. AT is reliable and accurate for the detection of E. coli in temperate and subtropical drinking water. The composition of the new medium is reported herein and can be used freely.

Understanding handpump sustainability: Determinants of rural water source functionality in the Greater Afram Plains region of Ghana

Safe drinking water is critical to human health and development. In rural sub-Saharan Africa, most improved water sources are boreholes with handpumps; studies suggest that up to one third of these handpumps are nonfunctional at any given time. This work presents findings from a secondary analysis of cross-sectional data from 1509 water sources in 570 communities in the rural Greater Afram Plains (GAP) region of Ghana; one of the largest studies of its kind. 79.4% of enumerated water sources were functional when visited; in multivariable regressions, functionality depended on source age, management, tariff collection, the number of other sources in the community, and the district. A Bayesian network (BN) model developed using the same data set found strong dependencies of functionality on implementer, pump type, management, and the availability of tools, with synergistic effects from management determinants on functionality, increasing the likelihood of a source being functional from a baseline of 72% to more than 97% with optimal management and available tools. We suggest that functionality may be a dynamic equilibrium between regular breakdowns and repairs, with management a key determinant of repair rate. Management variables may interact synergistically in ways better captured by BN analysis than by logistic regressions. These qualitative findings may prove generalizable beyond the study area, and may offer new approaches to understanding and increasing handpump functionality and safe water access.