Groundwater is an attractive source of drinking water particularly in developing countries, as it can be supplied untreated. To avoid waterborne pathogenic diseases, governments and NGOs encouraged installation of millions of tubewells, low-cost mechanical hand-pump wells, in Bangladesh. This has inadvertently exposed ca. 40% consumers to arsenic, which is naturally present in the groundwater. Using over 10 million tubewells, over 20 million Bangladeshi people are exposed to this insidious toxin. Switching to a safe well is a major mitigation option for rural inhabitants, but 6 million wells are yet to be tested. Screening of these untested wells requires trained personnel with a chemical test kit that are outside reach of most rural inhabitants, and testing kits typically produce toxic by-products. Building on existing research, we use computer modelling and digital technology to solve this issue. We used the existing dataset of ca. 4 million tubewells in a web based application to estimate arsenic levels in untested (or disremembered) wells, based on a geochemical indicator (staining of the tubewell platform) coupled with a 3D location indicator (produced using the well depth and street address) input by the user. Provided with the above-mentioned indicators, our model gives the user a high-confidence estimate of arsenic risk in their tubewell. Communicating the research directly with the user, particularly in an actionable format, is a key factor overlooked so far in arsenic mitigation efforts. The widespread internet coverage and increasing use of smartphones in Bangladesh provide a powerful opportunity both for gathering data and for disseminating information on arsenic pollution directly to the users. The app will not only allow users to make an informed decision about continuation of the use of the tubewell for drinking (saving people from ingesting arsenic); it will also help the government save screening costs, and adopt risk-based mitigation strategies.
|Number of pages||1|
|Publication status||Published - 27 Dec 2019|
|Event||2nd International Conference on Applied Statistics: Emerging challenges in a data-centric world - Dhaka, Bangladesh|
Duration: 27 Dec 2019 → 29 Dec 2019
|Conference||2nd International Conference on Applied Statistics|
|Abbreviated title||ICAS 2019|
|Period||27/12/19 → 29/12/19|