Project Summary/Abstract Sexual and social networks impact the spread of HIV and STIs and can be used as a tool for public health prevention efforts. The impact of HIV prevention strategies, such as PrEP, and prevention interventions for STIs depend on the characteristics of these sexual and social networks. Within sexual and social networks, people are linked by their sexual or social ties to form clusters. Genomic data from infectious organisms can be used to construct transmission networks which, in the case of sexually transmitted organisms, can provide information about the sexual network. Neisseria gonorrhoeae (NG) infection is one of the most common STIs in the world, and a potential driver of HIV acquisition. NG transmission may represent a more recent contact than the HIV transmission network. NG sequence data have been successfully used to study transmission and can be used to reveal insights into sexual networks. In Aim 1, we will characterize NG transmission networks using whole genome sequencing data from the bacterial isolates which will be merged with detailed patient metadata and social network data from a sample of participants accessing STI testing at the largest San Diego Public Health clinic. We will construct combined social and transmission networks using named social contacts and NG genetic distances and collection dates of NG isolates. We will then assess bridging of HIV positive and HIV negative groups in the social-molecular network to evaluate HIV transmission risk. In Aim 2, we will identify correlates of being in a cluster with at least one person living with HIV and will assess risk of HIV acquisition to identify candidates for PrEP. By combining connections from each network to create a more complete picture of contact, we can identify those who may be at risk for both STIs and HIV. These results will provide evidence for public health researchers and practitioners on how best to prioritize HIV PrEP and other services. The proposed study will be carried out as an extension of work that the PI conducted as part of a K01 project at the University of California San Diego, which aimed to combine HIV transmission network data and NG transmission network data. That project was conducted in a different clinical setting as the present proposal, however the methodology developed and piloted through that project provides a basis for the current proposal, which now also includes social networks. The present proposed study will be the first to simultaneously examine NG transmission networks combined with social networks. The results from this study will contribute to improved strategies to curb the spread of HIV and STIs.