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Malaria can be prevented, diagnosed, and treated; however, every year, thereare more than 200 million cases and 200.000 preventable deaths. Malaria remainsa pressing public health concern in low- and middle-income countries,especially in sub-Saharan Africa. We describe how by means of mobile healthapplications, machine-learning-based adaptive interventions can strengthenmalaria surveillance and treatment adherence, increase testing, measureprovider skills and quality of care, improve public health by supportingfront-line workers and patients (e.g., by capacity building and encouragingbehavioral changes, like using bed nets), reduce test stockouts in pharmaciesand clinics and informing public health for policy intervention.

Adaptive Interventions for Global Health: A Case Study of Malaria