Integrating mosquito genomics into simulation modeling: opportunities for better-informed biocontrol

Area of Science:

• Genomics and Mathematical Modeling
• Vector Control and Public Health

Background:

• Mosquito-borne diseases pose a significant global health threat.
• Mathematical models are crucial for evaluating novel biocontrol interventions.
• Accurate model parameterization is essential for reliable predictions.

Purpose of the Study:

• To review the integration of mosquito population genomics with biocontrol modeling.
• To highlight how genomic data improve understanding of mosquito populations and intervention outcomes.
• To identify future research directions for enhanced predictive accuracy.

Main Methods:

• Review of current literature at the intersection of mosquito genomics and biocontrol modeling.
• Analysis of how genomic data inform population structure, genetic variation, and resurgence.
• Discussion of emerging methods for quantifying gene flow, mating behavior, and inbreeding depression.

Main Results:

• Genomic data have advanced understanding of mosquito population structure and genetic variation at gene drive targets.
• Genomic insights help identify reasons for population resurgence after interventions.
• New genomic approaches are emerging to quantify key ecological factors influencing intervention success.

Conclusions:

• Integrating population genomics with mathematical modeling significantly enhances the predictive accuracy of biocontrol strategies.
• Improved models support better efficacy and risk assessment for interventions like gene drives.
• This synergy fosters evidence-based decision-making, field trial design, and public confidence in vector control efforts.