Abstract / Summary
Malaria remains a major global public health challenge, with a substantial burden of morbidity and mortality concentrated in sub-Saharan Africa and other tropical and subtropical regions. The complex transmission process involving Plasmodium parasites, Anopheles mosquito vectors, and human hosts makes mathematical modeling an important tool for understanding transmission dynamics and evaluating control strategies. This review provides a comprehensive synthesis of mathematical modeling approaches for malaria transmission and control, including deterministic compartmental models, stochastic models, optimal control frameworks, spatial models, and cost-effectiveness analyses. Particular attention is given to major intervention strategies, including vector control, vaccination, antimalarial treatment, and other integrated control approaches. The review also examines the effects of seasonality, climate variability, drug and insecticide resistance, spatial heterogeneity, and human movement on malaria transmission and intervention outcomes. A bibliography-based keyword frequency analysis and word-cloud visualization are used to identify dominant research themes, followed by a comparative assessment of modeling approaches and intervention strategies. The findings highlight the importance of integrating multiple interventions with context-specific epidemiological and environmental conditions. Overall, mathematical models provide valuable support for optimizing malaria control strategies and addressing important challenges toward malaria elimination.