AUTHOR=Affognon Steeven Belvinos , Tonnang Henri E. Z. , Ngare Philip , Kiplangat Benard Kipchumba , Abelman Shirley , Herren Jeremy K. 

TITLE=Optimizing microbe-infected mosquito release: a stochastic model for malaria prevention

JOURNAL=Frontiers in Applied Mathematics and Statistics

VOLUME=Volume 10 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2024.1465153

DOI=10.3389/fams.2024.1465153

ISSN=2297-4687

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.