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A receding horizon control approach for integrated vector management of Aedes aegypti using chemical and biological control: A mono and a multiobjective approach
Author(s) -
Jesus Tales,
Wanner Elizabeth,
Cardoso Rodrigo
Publication year - 2020
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.6115
Subject(s) - chikungunya , mathematical optimization , optimal control , aedes aegypti , multi objective optimization , time horizon , population , control theory (sociology) , pareto principle , control (management) , set (abstract data type) , computer science , mathematics , dengue fever , ecology , artificial intelligence , medicine , biology , larva , environmental health , immunology , programming language
This paper addresses an integrated vector management (IVM) approach for combating Aedes aegypti , the transmission vector of dengue, zika, and chikungunya diseases, some of the most important viral epidemics worldwide. In order to tackle this problem, a receding horizon control (RHC) strategy is adopted, considering a mono‐objective and a multiobjective version of the optimal control model of combating the mosquito using chemical and biological control. RHC is essentially a suboptimal scheme of classical optimal control strategies considering discrete‐time approximations. The integrated vector control actions used in this work consist in applying insecticides and inserting sterile males produced by irradiation in the population of mosquitoes. The cost function is defined in terms of social and economic costs, in order to quantify the effectiveness of the proposed epidemiological control throughout a time window of 4 months. Numerical simulations show that the obtained results are better than those from the optimal control strategies found in literature. Furthermore, through the application of the multiobjetive approach, varying the scenarios in the mono‐objective formulation is no longer necessary and a set of optimal strategies can be obtained at once. Finally, in order to help health authorities in the choice of the best solution of the Pareto‐optimal set to be implemented in practice, a cost‐effectiveness analysis is performed and a strategy representing the most cost‐effective control policy is obtained.