Multiobjective approach to optimal control for a dengue transmission model

TL;DR

This paper models dengue transmission dynamics and employs multiobjective optimization to identify optimal control strategies that balance reducing infections and minimizing costs, providing comprehensive insights into disease management.

Contribution

It introduces a multiobjective optimization framework for controlling dengue transmission, considering both health and economic factors, which is a novel approach in this context.

Findings

Multiobjective optimization effectively identifies optimal control strategies.

Trade-off solutions offer a range of scenarios for decision-making.

Results vary with different model parameter values.

Abstract

During the last decades, the global prevalence of dengue progressed dramatically. It is a disease which is now endemic in more than one hundred countries of Africa, America, Asia and the Western Pacific. This study addresses a mathematical model for the dengue disease transmission and finding the most effective ways of controlling the disease. The model is described by a system of ordinary differential equations representing human and vector dynamics. Multiobjective optimization is applied to find the optimal control strategies, considering the simultaneous minimization of infected humans and costs due to insecticide application. The obtained results show that multiobjective optimization is an effective tool for finding the optimal control. The set of trade-off solutions encompasses a whole range of optimal scenarios, providing valuable information about the dynamics of infection transmissions. The results are discussed for different values of model parameters.