1. Vector-borne disease outbreak control via instant releases.
- Author
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Almeida L, Bellver-Arnau J, Privat Y, and Rebelo C
- Subjects
- Animals, Humans, Male, Pest Control, Biological methods, Pest Control, Biological statistics & numerical data, Algorithms, Dengue prevention & control, Dengue epidemiology, Dengue transmission, Computer Simulation, Female, Malaria prevention & control, Malaria transmission, Malaria epidemiology, Zika Virus Infection epidemiology, Zika Virus Infection prevention & control, Zika Virus Infection transmission, Mathematical Concepts, Disease Outbreaks prevention & control, Disease Outbreaks statistics & numerical data, Vector Borne Diseases prevention & control, Vector Borne Diseases epidemiology, Vector Borne Diseases transmission, Mosquito Vectors virology, Mosquito Vectors microbiology, Wolbachia physiology, Models, Biological, Mosquito Control methods, Mosquito Control statistics & numerical data
- Abstract
This paper is devoted to the study of optimal release strategies to control vector-borne diseases, such as dengue, Zika, chikungunya and malaria. Two techniques are considered: the sterile insect one (SIT), which consists in releasing sterilized males among wild vectors in order to perturb their reproduction, and the Wolbachia one (presently used mainly for mosquitoes), which consists in releasing vectors, that are infected with a bacterium limiting their vectorial capacity, in order to replace the wild population by one with reduced vectorial capacity. In each case, the time dynamics of the vector population is modeled by a system of ordinary differential equations in which the releases are represented by linear combinations of Dirac measures with positive coefficients determining their intensity. We introduce optimal control problems that we solve numerically using ad-hoc algorithms, based on writing first-order optimality conditions characterizing the best combination of Dirac measures. We then discuss the results obtained, focusing in particular on the complexity and efficiency of optimal controls and comparing the strategies obtained. Mathematical modeling can help testing a great number of scenarios that are potentially interesting in future interventions (even those that are orthogonal to the present strategies) but that would be hard, costly or even impossible to test in the field in present conditions., Competing Interests: Declarations Conflict of interest The authors have no conflict of interest to declare that are relevant to the content of this article., (© 2024. The Author(s).)
- Published
- 2024
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