MGSurvE

MGSurvE optimizes trap placement for genetic surveillance of mosquito populations to minimize the time to detect an allele of interest.

Key Features:

• Landscape resource distribution: Resources required by mosquitoes, including food sources and aquatic breeding sites, can be explicitly distributed through a landscape.
• Sex- and state-dependent movement modeling: Movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female), and resource attractiveness.
• Trap attractiveness profiles: Traps may differ in their attractiveness profile.
• Optimization for allele detection time: The framework minimizes the time to detection of an allele of interest.

Scientific Applications:

• Gene drive monitoring: Optimizes trap placement to detect unintended spread of gene drive mosquitoes beyond field sites and emergence of alternative alleles such as drive-resistant alleles or non-functional effector genes.
• Insecticide resistance surveillance: Optimizes trap placement to detect insecticide-resistance alleles as quickly as possible.
• Aedes aegypti surveillance: Demonstrated optimal trap placement for an Aedes aegypti population in a suburban landscape in Queensland, Australia.
• Anopheles gambiae surveillance: Demonstrated optimal trap placement for an Anopheles gambiae population on the island of São Tomé, São Tomé and Príncipe.

Methodology:

MGSurvE is a computational framework that optimizes trap placement by accounting for mosquito resource requirements, movement patterns, and trap attractiveness profiles.