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Abstract:
Safe water is essential for protecting public health during humanitarian emergencies. Current humanitarian water treatment guidelines however often fail to ensure water remains protected against microbiological contamination up to the point-of-consumption, while post-distribution recontamination has been implicated in waterborne disease outbreaks in multiple refugee and internally-displaced persons (IDP) settings around the world. In this presentation, Dr. Ali and Dr. Khan will introduce the Safe Water Optimization Tool (SWOT), a web-based water quality modelling platform that responds to this challenge by generating site-specific and evidence-based water treatment guidance via machine learning (ML) and process-based modelling of routine water quality monitoring data. The SWOT has been deployed by humanitarian agencies around the world to help improve water safety outcomes in high risk settings, and there may be potential to develop and deploy similar ML-enabled engineering decision support tools in non-emergency contexts in Lower Middle Income Countries (LMICs) and in Canada.