MistraL: Mitigation Strategies for Communities With COVID-19 Transmission in Lesotho Using Artificial Intelligence on Chest X-rays and Novel Rapid Diagnostic Tests

Problem description:

For mitigation strategies to be effective and efficient against COVID-19, they must be context-specific and take local conditions into account. In low- and middle-income countries, limited resources and fragile healthcare systems often dictate what is feasible. The MistraL project, commencing in the early stages of the COVID-19 pandemic addresses the issue of early detection of COVID-19 in Lesotho, a lower-middle-income country with limitations on healthcare infrastructure and spending. Early detection of COVID-19 mitigates against high transmission rates, limiting the number of severe cases, which is of particular importance in countries with limited or no intensive care facilities.

Project summary

In this project, researchers combine artificial intelligence, portable chest X-ray machines and antigen-based diagnostic tests to enable and improve the diagnosis of COVID-19 patients in settings with limited resources. The CAD4COVID AI system for detection of COVID-19 pneumonia on chest X-ray will be utilised along with point-of-care blood testing and antigen testing to determine the optimal methods for early detection of COVID-19.


This research project is funded by the Botnar Research Center for Child Health. The project is implemented by a consortium of partners from Swiss Tropical and Public Health Institute, SolidarMed, Swiss NGO for Health in Africa, Radboud University Medical Center and FIND


Keelin Murphy

Keelin Murphy

Assistant Professor