Artificial Intelligence in Mosquito and Vector Control/Behavior/Biology/Genetics
Artificial Intelligence in Mosquito and Vector Control/Behavior/Biology/Genetics
Aedes aegypti mosquitoes are increasingly spreading across California. These mosquitoes are known carriers of mosquito-borne diseases including chikungunya, dengue and Zika. The ability for vector control to act quickly if this invasive species is found is vital to slowing or stopping their propagation. Typical species identification, visual morphological taxonomy, can pose issues for certain specimens, such as atypical and damaged larva and adults and morphologically similar interspecies eggs. DNA barcoding using the mitochondrial Cytochrome Oxidase I(COI) gene can be used to assign these problematic specimens to species given its conserved regions within species and single nucleotide polymorphisms (SNP) that distinguish interspecies differences. In this study, a multiplex quantitative PCR assay was developed to classify an ambiguous sample to two species: Aedes aegypti and Aedes sierrensis. The assay demonstrated an average sensitivity of 97.29% and an average specificity of 94.69% when tested on Aedes sierrensis. For Aedes aegypti, the assay had an average sensitivity of 98.61% and an average specificity of 93.89%. We expect that this Aedes ID assay could be employed by vector control organizations to identify potentially invasive Aedes aegypti specimens, especially when conventional methods prove inadequate for atypical samples.