Different Anopheles spp. are able to transmit the Plasmodium parasite, the causative agent of malaria. Malaria results in over 600,000 deaths a year, predominantly in children and the immunocompromised. To combat malaria, disease control relies heavily on strategies targeting the vectors populations, including the application of insecticides for indoor residual spraying, and treated bed-nets. These interventions are believed to be responsible for >65% of the reduction in malaria cases observed over the last 15 years. However, resistance to commonly used insecticides is rapidly rising, threatening the World Health Organization targets of reducing global malaria. The detection of insecticide resistance in mosquitoes relies either on time-consuming phenotypic bioassays or expensive and limited-target molecular assays. To address this, I have developed three species-specific multi-target amplicon sequencing (amp-seq) panels for high-throughput surveillance of insecticide resistance in An.darlingi, An. funestus, and An. stephensi. The assays were validated using field isolates for each species, Ethiopian An. stephensi, Brazilian An. darlingi, and An. funestus from the Democratic Republic of Congo. This work resulted in the detection of known SNPs associated with insecticide resistance, including a pyrethroid resistance associated 2bp deletion in the CYP6P9a gene in An. funestus, alongside the kdr-L1014F and rdl-A296S SNPs in An. stephensi. Several putatively novel missense SNPs were also identified in genes associated with resistance for all three species. The availability of genomic data for many Anopheles spp is limited but can be used to provide insights into ongoing selective pressure, potentially due to insecticides, as well as unravelling population dynamics. This thesis expands the available sequence data for An. stephensi and An. darlingi to provide insights into the genomic landscape of these vectors. I generated whole genome sequencing (WGS) data and performed population genetics analysis on An. darlingi (n=31) and An. stephensi (n=72) isolates. For An. stephensi, the study includedisolates from Ethiopia (n=27), India (field 21; colony 16) and Pakistan (n=8). An ancestral analysis revealed shared ancestry between Ethiopian and Indian field isolates. Further, insecticide resistance linked mutations were identified, including the kdr- L1014F and rdl-A296S in the Ethiopian isolates, and the rdl-A296S and rdl-V327I in the Indian isolates. For An. darlingi, the study included samples from Rondônia state in Brazil (colony 8, field 23). No known insecticide resistance associated mutations were identified in the Brazilian An. darlingi, either by amp￾seq or WGS. To find other mechanisms, population genetic tests of selection were applied, and identified candidate regions for insecticide resistance, such as CYP4c1, CYP4c3, and CYP307a1. Overall, these investigations have increased our understanding of An. darlingi and An. stephensi genomic diversity and provide baseline data and analysis for much needed larger studies. The high-throughout sequencing-based assays developed will inform insecticide resistance surveillance. Their utility was demonstrated through their role in identifying putative novel mutations involved in insecticide susceptibility, which can be followed up in functional studies. Overall, genomics-based approaches, such as those developed here, have the potential to inform control strategies across a range of vector borne diseases. Through the integration of low-cost and high-throughput approaches within vector control programs, it will assist with the urgent need to disrupt transmission, and thereby reduce the high burden of disease.