ArXiv Preprint
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.
África Periáñez, Andrew Trister, Madhav Nekkar, Ana Fernández del Río, Pedro L. Alonso
2023-03-03
