Mathematical Modeling and Computational Approaches for Malaria Transmission and Control

Malaria remains one of the most significant global health challenges, causing hundreds of thousands of deaths annually, particularly in sub-Saharan Africa. Despite decades of intervention, progress toward elimination has plateaued in several regions due to emerging threats such as insecticide resistance, antimalarial drug evasion, and the impacts of climate change on vector distribution. Traditional epidemiological surveillance alone often struggles to capture the complex, non-linear interactions between the Plasmodium parasite, Anopheles mosquitoes, and human hosts. In this context, mathematical modeling and computational frameworks have become indispensable tools for synthesizing data, testing hypotheses, and predicting the outcomes of public health interventions in a cost-effective manner.This Research Topic aims to bridge the gap between theoretical modeling and practical public health application. By integrating multi-source data - ranging from genomic surveillance to satellite climate imagery - this collection seeks to provide insights into how transmission can be disrupted. We invite original research, reviews, and methodological papers that utilize quantitative approaches to study malaria. Potential themes include, but are not limited to:• Spatial and Temporal Dynamics: Models that account for human mobility and the seasonal fluctuations of vector populations.• Climate-Driven Transmission Models: Analyzing the impact of temperature, rainfall, and environmental shifts on malaria risk.• Evolutionary Modeling: Investigating the spread of drug resistance and insecticide resistance, and the potential impact of gene-drive technologies.• Intervention Optimization: Computational assessment of the efficacy and cost-effectiveness of combined interventions (e.g., bed nets, seasonal malaria chemoprevention, and new vaccines like R21/Matrix-M). Topic editors: Sulaimon Femi Abimbade, Akanni John Olajide Source: https://www.frontiersin.org/research-topics/83125/mathematical-modeling-and-computational-approaches-for-malaria-transmission-and-control