mlsanityData to 14 Oct 2026

Adaptive Interventions for Global Health: A Case Study of Malaria

arXiv 2303.02075 ↗First posted 3 Mar 2023stat.ML cs.CY cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 101 references that are in the map. First posted on arXiv 3 Mar 2023.

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22 of 101 references.

References · 22

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10 more
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