{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T09:58:48Z","timestamp":1775901528211,"version":"3.50.1"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Appl. Math. Stat."],"abstract":"<jats:p>Malaria remains a critical public health challenge in Africa, demanding innovative control strategies. This study introduces a novel approach using <jats:italic>Microsporidia MB<\/jats:italic>-infected mosquitoes and stochastic optimal control within a L\u00e9vy process framework to regulate mosquito release strategies. The primary goal is to optimize <jats:italic>Microsporidia MB<\/jats:italic> prevalence within mosquito populations to disrupt <jats:italic>Plasmodium<\/jats:italic> transmission to humans. By incorporating L\u00e9vy noise into the modeling process, we capture the inherent randomness of mosquito dynamics, improving intervention accuracy. The model, guided by the Hamilton\u2013Jacobi\u2013Bellman (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 <jats:italic>Microsporidia MB<\/jats:italic> has been confirmed. Findings suggest that targeted mosquito releases could significantly reduce malaria transmission, offering valuable insights for public health efforts.<\/jats:p>","DOI":"10.3389\/fams.2024.1465153","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T06:40:23Z","timestamp":1732689623000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimizing microbe-infected mosquito release: a stochastic model for malaria prevention"],"prefix":"10.3389","volume":"10","author":[{"given":"Steeven Belvinos","family":"Affognon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Henri E. 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