Publication Type

Journal Article

Journal Name

Frontiers in Applied Mathematics and Statistics

Publication Date

1-1-2024

Abstract

Malaria remains a critical public health challenge in Africa, demanding innovative control strategies. This study introduces a novel approach using Microsporidia MB-infected mosquitoes and stochastic optimal control within a Lévy process framework to regulate mosquito release strategies. The primary goal is to optimize Microsporidia MB prevalence within mosquito populations to disrupt Plasmodium transmission to humans. By incorporating Lévy noise into the modeling process, we capture the inherent randomness of mosquito dynamics, improving intervention accuracy. The model, guided by the Hamilton–Jacobi–Bellman (HJB) equation, optimizes release protocols while accounting for key environmental factors like seasonality and temperature fluctuations. Results show that intervention success depends on local climatic conditions, underscoring the need for flexible, region-specific strategies in malaria-endemic areas. Focus regions include Kenya, Ghana, Niger, and Benin, where Microsporidia MB has been confirmed. Findings suggest that targeted mosquito releases could significantly reduce malaria transmission, offering valuable insights for public health efforts.

Keywords

HJB equation, Lévy process, malaria, Microsporidia MB, stochastic control, vector control

Disciplines

Control Theory | Dynamical Systems

Funding Statement

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study, conducted by the International Centre of Insect Physiology and Ecology, is part of the Symbiont Modeling and Deployment Strategies project, generously supported by the Bill and Melinda Gates Foundation (INV-022584). The opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the donor.

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