Clean water provision is a critical component of emergency response, and chlorination is widely used in emergencies to treat water. To provide responders with practical, evidence-based recommendations for implementing chlorination programmes and recommend areas for future research, we conducted a literature review of chlorination in emergencies, supplemented with a literature review on chlorination in general. We identified 106 total documents, including 7 with information on technical efficacy, 26 on chlorine dosage, 22 on technical challenges, 21 on product options, 8 on user acceptability, 33 on programmes for emergencies, and 8 on monitoring. We found that: 1) international chlorine dosage recommendations in emergencies are highly inconsistent; 2) high-quality information from the general chlorination literature on challenges of chlorination can be adapted for emergencies; 3) many chlorine products are available for use in point-of-delivery, point-of-source, and point-of-use emergency-response program...

The current Sphere guideline for water chlorination in humanitarian emergencies fails to reliably ensure household water safety in refugee camps. We investigated post-distribution chlorine decay and household water safety in refugee camps in South Sudan, Jordan, and Rwanda between 2013-2015 with the goal of demonstrating an approach for generating site-specific and evidence-based chlorination targets that better ensure household water safety than the status quo Sphere guideline. In each of four field studies we conducted, we observed how water quality changed between distribution and point of consumption. We implemented a nonlinear optimization approach for the novel technical challenge of modelling post-distribution chlorine decay in order to generate estimates on what free residual chlorine (FRC) levels must be at water distribution points, in order to provide adequate FRC protection up to the point of consumption in households many hours later at each site. The site-specific FRC targets developed through this modelling approach improved the proportion of households having sufficient chlorine residual (i.e., ≥0.2 mg/L FRC) at the point of consumption in three out of four field studies (South Sudan 2013, Jordan 2014, and Rwanda 2015). These sites tended to be hotter (i.e., average mid-afternoon air temperatures >30°C) and/or had poorer water, sanitation, and hygiene (WASH) conditions, contributing to considerable chlorine decay between distribution and consumption. Our modelling approach did not work as well where chlorine decay was small in absolute terms (Jordan 2015). In such settings, which were cooler (20 to 30°C) and had better WASH conditions, we found that the upper range of the current Sphere chlorination guideline (i.e., 0.5 mg/L FRC) provided sufficient residual chlorine for ensuring household water safety up to 24 hours post-distribution. Site-specific and evidence-based chlorination targets generated from post-distribution chlorine decay modelling could help improve household water safety and public health outcomes in refugee camp settings where the current Sphere chlorination guideline does not provide adequate residual protection. Water quality monitoring in refugee/IDP camps should shift focus from distribution points to household points of consumption in order to monitor if the intended public health goal of safe water at the point of consumption is being achieved.

The reliance on chlorination in humanitarian operations has raised concerns among practitioners about possible health risks associated with disinfection by-products; however, to date, there has not been an evaluation of disinfection by-product (DBP) levels in an emergency water supply intervention. This study aimed to investigate DBP levels at a surface-water treatment plant serving a refugee settlement in northern Uganda using the colorimetric Hach THM Plus Method. The plant had two treatment processes: (1) Simultaneous clarification–chlorination (“rapid treatment”); and (2) pre-clarification and chlorination in separate tanks (“standard treatment”). For both standard (n = 17) and rapid (n = 3) treatment processes, DBP levels in unique parcels of water were tested at 30 min post-chlorination and after 24 h of storage (to simulate what refugees actually consume). DBP levels after 24 h did not exceed the World Health Organization (WHO) guideline limit of 300 ppb equivalent chloroform, either for standard treatment (mean: 85.1 ppb; 95% confidence interval (C.I.): 71.0–99.1 ppb; maximum: 133.7 ppb) or for rapid treatment (mean: 218.0 ppb; 95% C.I.: 151.2–284.8; maximum: 249.0 ppb). Observed DBPs levels do not appear to be problematic with respect to the general population, but may pose sub-chronic exposure risks to specifically vulnerable populations that warrant further investigation.

Waterborne illnesses are a leading health concern in refugee and internally displaced person (IDP) settlements where waterborne pathogens often spread through household recontamination of stored water. Ensuring sufficient chlorine residual is important for protecting drinking water against recontamination and ensuring water remains safe up to the point-of-consumption. We used ensembles of artificial neural networks (ANNs) to probabilistically forecast the point-of-consumption free residual chlorine (FRC) concentration and to develop point-of-distribution FRC targets based on the risk of insufficient FRC at the point-of consumption. We built ANN ensemble models using data from three refugee settlements and found that the risk-based FRC targets generated by the ensemble models were consistent with an empirical water safety evaluation, indicating that the models accurately predicted the risk of low point-of-consumption FRC despite all ensemble forecasts being underdispersed even after post-processing. This demonstrates the usefulness of ANN ensembles for generating risk-based point-of-distribution FRC targets to ensure safe drinking water in humanitarian operations.

While standard methods for chlorine taste and odor (T&O) detection and rejection thresholds exist, little rigorous research has been conducted on T&O thresholds in humanitarian settings. To fill this gap, we estimated chlorine T&O detection and rejection thresholds using the Forced-Choice Triangle Test (FCT) and Flavor Rating Assessment (FRA) standard methods in a Ugandan refugee settlement. We conducted these tests with 410 male and female participants, aged 5–72 years, using piped and trucked surface water and bottled water. We also conducted 30 focus group discussions and 37 surveys with data collectors. Median chlorine detection thresholds were 0.56, 1.40, and 1.67 mg/L, for piped, trucked, and bottled water, respectively. Rejection was calculated using ratings (as per the method) and five different previously-used thresholds, and was 1.6, 2.0, and 1.6 mg/L (ratings) and 2.19, 1.85, and 1.67 mg/L (using the FCT threshold method with FRA data) for piped, trucked, and bottled water, respectively. Detection and rejection thresholds were significantly associated with water quality (including turbidity, pH, electrical conductivity, and temperature), participant age and education. We observed high intra- and inter-individual variability, which decreased with participant experience. We found the method used to calculate rejection thresholds influenced results, highlighting the need for a standard method to analyze FRA data. Data collectors and participants recommended shortening protocols and evaluating fewer concentrations, and highlighted difficulties in creating accurate FRC concentrations for testing. This study provides insights on using standard methods to assess T&O thresholds in untrained populations, and results are being used to develop rapid field T&O protocols for humanitarian settings.

Ensuring sufficient free residual chlorine (FRC) up to the time and place water is consumed in refugee settlements is essential for preventing the spread of waterborne illnesses. Water system operators need accurate forecasts of FRC during the household storage period. However, factors that drive FRC decay after water leaves the piped distribution system vary substantially, introducing significant uncertainty when modelling point-of-consumption FRC. Artificial neural network (ANN) ensemble forecasting systems (EFS) can account for this uncertainty by generating probabilistic forecasts of point-of-consumption FRC. ANNs are typically trained using symmetrical error metrics like mean squared error (MSE), but this leads to forecast underdispersion forecasts (the spread of the forecast is smaller than the spread of the observations). This study proposes to solve forecast underdispersion by training an ANN-EFS using cost functions that combine alternative metrics (Nash-Sutcliffe efficiency, Kling Gupta Efficiency, Index of Agreement) with cost-sensitive learning (inverse FRC weighting, class-based FRC weighting, inverse frequency weighting). The ANN-EFS trained with each cost function was evaluated using water quality data from refugee settlements in Bangladesh and Tanzania by comparing the percent capture, confidence interval reliability diagrams, rank histograms, and the continuous ranked probability. Training the ANN-EFS using the cost functions developed in this study produced up to a 70% improvement in forecast reliability and dispersion compared to the baseline cost function (MSE), with the best performance typically obtained by training the model using Kling-Gupta Efficiency and inverse frequency weighting. Our findings demonstrate that training the ANN-EFS using alternative metrics and cost-sensitive learning can improve the quality of forecasts of point-of-consumption FRC and better account for uncertainty in post-distribution chlorine decay. These techniques can enable humanitarian responders to ensure sufficient FRC more reliably at the point-of-consumption, thereby preventing the spread of waterborne illnesses.