Building evidence to support scaling of a machine learning-enabled safe water optimization tool (SWOT) for humanitarian response

Principal investigator

Topic

Water & sanitation
Methodology

Mixed-methods study
Reference

OCA021-15
Views

229
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Purpose of study

The core purpose of the Safe Water Optimization Tool, or SWOT is to help assure quality of safe water interventions in order to maximum public health benefits among populations in humanitarian settings. This research wants to integrate participato...

Study status

Concept
Protocol & ERB
Implementation
Completion
Archived

Study timeline

Documents

Concept_paper_SWOT_evidence_HIF_2021_submitted_modified_RC.docx 72.1 KB
Appendix1_Tools_v2.docx 99.1 KB
Appendix2_Recruitment_material_v2.docx 31.6 KB
Appendix3_Consent_v3.docx 55.6 KB
Appendix4_Data_Protection_Notice.docx 37.7 KB
Appendix5_ToR_v2.docx 29.5 KB
Protocol_SWOT_v4.docx 355 KB
MSF_ERB_2159_ethics_approval_07Dec2021.pdf 114 KB

Publications

Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?

De Santi, Michael "–" Public Library of Science (PLoS) "(2022)"

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