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Adaptive Interventions for Global Health: A Case Study of Malaria
- Publication Year :
- 2023
-
Abstract
- Malaria can be prevented, diagnosed, and treated; however, every year, there are more than 200 million cases and 200.000 preventable deaths. Malaria remains a pressing public health concern in low- and middle-income countries, especially in sub-Saharan Africa. We describe how by means of mobile health applications, machine-learning-based adaptive interventions can strengthen malaria surveillance and treatment adherence, increase testing, measure provider skills and quality of care, improve public health by supporting front-line workers and patients (e.g., by capacity building and encouraging behavioral changes, like using bed nets), reduce test stockouts in pharmacies and clinics and informing public health for policy intervention.<br />Comment: Accepted for ICLR 2023 Workshop on Machine Learning and Global Health
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2303.02075
- Document Type :
- Working Paper