Leveraging artificial intelligence to improve malaria epidemics’ response

International summary

Abstract

As the world advances toward malaria elimination, the elimination management paradigm has to change to address early case detection in more local and remote areas. Remote areas face additional difficulties in both detection and treatment demanding innovative approaches. Malaria elimination needs evidence-based decision-making with real-time access to malaria-cases data. Years of endeavor towards malaria elimination have created several databases, which often lack interoperability, making the crossing of data difficult. The access to early alerts can promote decision-makers quick action in launching early interventions particularly in a low-resources settings. Therefore, a smart, comprehensive, sustainable and integrated information system is required. We propose a collaborative-design implementation strategy, combining elements of gamification, Geographical Information System (GIS) and Artificial Intelligence (AI) to enable early-detection and risk of epidemics alerts, and to direct interventions around detected cases. These technologies can be combined to further reinforce the sustainability of data collection and the behavioral change of public health decision- -makers. The success of such a system depends mostly on how elimination actions will be improved in real settings. Therefore design-science research methodology could engage health professionals and use evidence-based knowledge in the design of an innovative system that responds to what public health professionals’ real needs.