Last Updated: 14/07/2026

Unraveling the multiple drivers of malaria risk using AI in Amazon communities (MalariAI)

Objectives

This project investigates the diverse causes of the risk of malaria in Amazon communities and uses modern methods of artificial intelligence (AI) and causality analysis to unravel the complex interactions between genetic, environmental, socioeconomic and behavioral factors that influence an individual’s risk of malaria infection.

Principal Institution

University of Münster, Germany

Principal Investigators / Focal Persons

Dominik Heider

Partner Institutions

University of São Paulo (USP), Brazil

Partner Investigators

Adèle Helena Ribeiro

Rationale and Abstract

Malaria is one of the world’s most pressing global health challenges and poses a significant threat to millions of people, particularly in tropical and subtropical regions burdened by poverty, limited access to health care and adverse environmental conditions. Globally, there were an estimated 249 million malaria cases in 2022 in 85 malaria-prone countries and territories, including the Amazon region of Brazil. By using AI and causal modeling approaches, tailored prevention and control strategies for risk groups are to be developed. The research results have the potential to not only improve understanding of malaria in Brazil, but also influence global malaria control strategies. The insights gained will serve as a basis for the broader application of AI in epidemiology and thus advance the global fight against malaria.

Project Outputs