Comprehensive Spatiotemporal Analysis of Antimalarial Drug Resistance Markers in Mali: A Genomic Surveillance Approach

Abstract BackgroundMalaria is still the leading cause of morbidity and mortality in Mali with 40% of out-patients and 20% of deaths among children under-five attributed to the disease. Drug-resistant Plasmodium falciparum is degrading the value of recent gains in malaria control. Here we report an analysis of 2,887 clinical isolates collected between 2014 and 2022 from four epidemiologically distinct sites in Mali in the context of MalariaGEN's Pf7 and Pf8 global resources.MethodsUsing targeted amplicon sequencing, we characterized resistance markers in five key genes (pfk13, pfcrt, pfmdr1, pfdhfr, and pfdhps), following standardized Genetic Report Card protocols. Our approach combined high-throughput sequencing with advanced geospatial modeling and Bayesian statistical analyses to track spatiotemporal resistance patterns and identify emerging hotspots.ResultsOur analysis revealed alarming trends in antimalarial resistance evolution. Most concerning is the near-fixation of sulfadoxine-pyrimethamine (SP) resistance markers (pfdhfr IRNI + pfdhps AGEAA), which reached 91% prevalence by 2022 and was associated with 2.3-fold higher treatment failure rates (95% CI: 1.7–3.1). Equally worrying is the emergence of artemisinin resistance precursors (pfarps10-V127M) detected in 12.1% of isolates from Koila, suggesting potential vulnerability to artemisinin-based therapies. Furthermore, we observed the unexpected persistence of chloroquine resistance (pfcrt CVIET) showing cyclical patterns (19–29% prevalence) despite the drug's withdrawal from clinical use.ConclusionThese findings demonstrate the rapid evolution and spread of multidrug-resistant P. falciparum in Mali, with immediate implications for malaria control. Our results underscore the urgent need to transition from SP-based preventive therapies to high-prevalence areas, enhance surveillance for emerging artemisinin resistance, and implement targeted containment strategies in high-risk transmission corridors. The integrated genomic and geospatial approach developed here provides a framework for real-time resistance monitoring that can be adapted to other malaria-endemic regions.