Examining Sexual Concurrency and Sexual Networks among Married Fishermen Couples in Kisumu District, Kenya
Parent Project: UCSF-Gladstone Center for AIDS Research (CFAR)
Determining the prevalence of sexual concurrent partnerships among married couples and the structure and characteristics of the resultant sexual networks is crucial in designing appropriate HIV prevention interventions. In this study we seek to: (a) identify the types and extent of concurrent sexual partnerships and, (b) elucidate the structure and characteristics of sexual networks that result from concurrent sexual partnerships among married fishermen couples in Kisumu, Kenya. To achieve these aims, we are proposing a quantitative crosssectional study with a sample of 545 married fishermen couples. We will use existing beach management structures and lists of registered fishermen to enroll our sample of index participants. We will use face-to-face structured interviews by gender-matched interviewers to collect data--couples will be introduced to the study and consented together and thereafter separated to different rooms to be interviewed simultaneously. We will collect socio-economic, demographic and sexual relationship information. Specifically, we will gather information on their sexual partners in the three months preceding the study in respect to relationship start and end dates, its status (on-going or not) and condom use. We will also test couples for HIV separately and encourage and/or facilitate sharing of results; providing referrals for further counseling and care. We will use both descriptive and inferential statistics to describe the extent and types of concurrent sexual relationships in this population. For sexual network analysis, we will use the R program to compute centrality and structural attributes that describe the position of individuals in the component and morphology of the network components, respectively. We will also do network simulation and creation of visualized networks. The proposed study will be completed in 12-months. These data will be used to generate hypotheses about the associations of concurrency and sexual networks with HIV transmission and develop tailored HIV prevention interventions.