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A Spatiotemporal Framework for Malaria Control Integrating Exposure Heterogeneity and Optimal Strategy Deployment

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Integrative bioinformatics model improves malaria control in human and mosquito populations, indicating optimal strategy deployment.

The model effectively integrates exposure heterogeneity and mosquito population dynamics in malaria transmission.
Sensitivity analysis highlights critical parameters like biting rate and infection probability affecting disease spread.
Numerical simulations validate targeted control measures in reducing malaria infections and exposures.
The findings support the use of bioinformatics with mathematical modeling for informing malaria policy.

Abbas et al. (2025) studied this question.

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