Disease burden estimation to support policy decision-making and research prioritization for arsenic mitigation

Abstract

The main response to arsenic contamination of shallow tubewells in Bangladesh is the provision of alternative water supplies. To support decision-making in relation to alternative water supply selection, the Arsenic Policy Support Unit commissioned the development of a tool for estimating disease burdens for specific options using disability-adjusted life years as the metric. This paper describes the assumptions in dose-responses, relationships between microbial indicators and pathogens, water consumed and population characteristics used, and presents a case study of how the tool was applied. Water quality data and dose-response models were used to predict disease burdens due to microbial pathogens and arsenic. Disease burden estimates predicted by the tool were based on evidence in the published literature. There were uncertainties in key assumptions of water consumed and the ratio of microbial indicators and pathogens, which led to broad confidence intervals and the need to consider the results in a wider context and further research needs. Deep tubewells and rainwater harvesting had the lowest disease burden estimates, while pond sand filters and dug wells had much higher predicted disease burden due to frequent microbial contamination. The need for rigorous water supply protection through water safety plans was highlighted. At present, the risk assessment is useful for informing judgement by experienced water and health professionals and identifying key research questions. Improved arsenic dose-response models and a better understanding of the relationship between microbial indicators and pathogens in tropical settings are required.

Critical review of methodology and application of risk ranking for prioritisation of food and feed related issues, on the basis of the size of anticipated health impact

“…Thirteen references ranked different chemical and microbiological food hazards, of which three references ranked both chemical and microbial hazards (Howard, 2007;Lim, 2012;Newsome, 2009). Three of the references used alternative methods of estimating clinical severity (Fosse et al, 2008a(Fosse et al, , 2008bNewsome, 2009).…”

“…DALYs or QALYs are then calculated based on the disability weights and duration of the health outcomes. This methodology was applied by Howard et al (2007), Risk ranking for prioritisation of food and feed related issues EFSA supporting publication 2015:EN-710…”

Diarrhoeal Health Risks Attributable to Water-Borne-Pathogens in Arsenic-Mitigated Drinking Water in West Bengal are Largely Independent of the Microbiological Quality of the Supplied Water

“…We estimated the pathogen-attributable health risks in terms of DALYs using the QMRA model of Howard [10] (Figure 1) and compared it to arsenic-attributable DALYs calculated using the risk model of Mondal [16] (Figure 2). In the absence of comprehensive dose-response data for sequela arising from exposure to water-borne pathogens and to arsenic, we have restricted our calculations to sequelae considered to be the dominant detrimental health outcomes arising from each agent, viz.…”

“…Following Howard [10], no distinction is made between pathogen concentrations arising from post-supply contamination outside the household and that arising from within the household. The dose-response relationships for the model reference pathogens based on the reported human-feeding-trial data are summarized in Table 2 along with the µDALYs per reference pathogen microbial infection applied to the QMRA model based on the data by Havelaar and Melse [19] and Howard [10]. The outcome, severity, duration and probability of infection data are based on the values given by Havelaar and Melse [19] while the susceptible fraction data were obtained from Howard [10] for the population of Bangladesh.…”

“…Esrey [8] and Clasen and Cairncross [9] both conclude that the prevalence of diarrheal diseases in developing countries, similar to (peri-)rural Bengal, is not related to improvements in water supply but rather to the status of improvements in sanitation and hygiene. In contrast, Howard et al [10], using quantitative microbial risk assessment (QMRA) based upon measurements of pathogens in water supplies from arsenic mitigation schemes in Bangladesh, calculated that disease burden arising from water-borne pathogens, especially for waters from pond sand filters and rain water harvesting, were typically orders of magnitude more important than that arising from groundwater arsenic.…”