The challenge we are addressing
The increased incidences of infectious diseases such as malaria, attributed to climate change, pose a growing challenge to health systems across the globe. Malaria remains a problem in Limpopo province in South Africa, particularly in Vhembe districts. People die each year because of malaria. Vhembe and Limpopo at large lack an intelligent tool that can alert the community of the upcoming malaria outbreaks.
Our Solution
MOEWS integrates indigenous knowledge with machine learning and big climate data to predict malaria outbreaks. Integrating IKSs with advanced Machine Learning and climate data presents a novel approach that may enhance the robustness of early warning systems for infectious diseases. This approach addresses a critical gap in local health responses to infectious diseases such as malaria. By boosting IK with computational power, this research study develops a more accurate and contextually relevant disease prediction system that may contribute to reducing malaria outbreaks in South Africa and Sub Sahara Africa.
For a comprehensive overview of MOEWS, visit our Who We Are page.
Our Partners
