A multiobjective optimization approach for combating Aedes aegypti using chemical and biological alternated step-size...

Area of Science:

• Vector-borne disease control
• Mathematical modeling
• Optimization techniques

Background:

• Dengue epidemics pose a significant global health threat.
• Controlling the Aedes aegypti mosquito is crucial for prevention.
• Existing control methods require optimization for cost-effectiveness.

Purpose of the Study:

• To analyze dengue vector control using a multiobjective optimization approach.
• To minimize social and economic costs associated with vector control.
• To determine optimal control policies combining chemical and biological methods.

Main Methods:

• Development of a dynamic mathematical model for mosquito populations.
• Application of genetic algorithms for multiobjective optimization.
• Analysis of alternated step-size control policies.

Main Results:

• Optimal policies involve initial insecticide application followed by sterile male releases.
• Genetic algorithms effectively identified trade-offs between control strategies.
• The multiobjective approach demonstrated statistical effectiveness in parameter variation.

Conclusions:

• A single-run methodology can determine optimal application schedules for insecticides and sterile males.
• The approach balances cost, insecticide use, sterile male deployment, and transmission.
• This provides decision-makers with effective tools for dengue vector management.