Biological and Chemical Control of Mosquito Population by Optimal Control Approach

Abstract

This paper focuses on the design and analysis of short-term control intervention measures seeking to suppress local populations of Aedes aegypti mosquitoes, the major transmitters of dengue and other vector-borne infections. Besides traditional measures involving the spraying of larvicides and/or insecticides, we include biological control based on the deliberate introduction of predacious species feeding on the aquatic stages of mosquitoes. From the methodological standpoint, our study relies on application of the optimal control modeling framework in combination with the cost-effectiveness analysis. This approach not only enables the design of optimal strategies for external control intervention but also allows for assessment of their performance in terms of the cost-benefit relationship. By examining numerous scenarios derived from combinations of chemical and biological control measures, we try to find out whether the presence of predacious species at the mosquito breeding sites may (partially) replace the common practices of larvicide/insecticide spraying and thus reduce their negative impact on non-target organisms. As a result, we identify two strategies exhibiting the best metrics of cost-effectiveness and provide some useful insights for their possible implementation in practical settings.

Mathematical Model for the Biological Control of the Coffee Berry Borer Hypothenemus hampei through Ant Predation

“…This assumption was admissible given that in the CBBs’ absence, the ants are not extinguished, because they have other sources of food in the coffee plantations. Following the methodology proposed in [ 18 , 20 , 21 , 22 ], an additional increase was considered for the intrinsic growth of the ants attributed to the predation of adult CBBs and immature CBBs , where parameter corresponds to the biomass conversion rate through predation and indicates that there is no total consumption of the adult and immature CBBs that die due to attacks by ants. According to the aforementioned, the population dynamics of the ants were modeled by the following differential equation: …”

Bifurcation Analysis in a Coffee Berry-Borer-and-Ants Prey–Predator Model

“…For the ant population, denoted by the letter R, logistic growth is also assumed, with r representing the intrinsic growth rate and k representing the carrying capacity. Furthermore, an additional increase in the intrinsic growth of ants, attributed to predation, is assumed-a hypothesis incorporated in population dynamics works such as [24][25][26][27] in the context of Aedes aegypti and in [5] within the context of CBB. As is customary in prey-predator models, it should be noted that not all prey biomass is converted into predator biomass, so a biomass conversion rate denoted by ε is considered.…”