Sexual Networks and HIV: Data, Models and Intervention
Source: NICHD , 7R29HD034957
Active: 4/25/96 - 4/30/03
Investigator: Martina Morris, PI
The purpose of this project is to link the theory and methods of epidemiological network modeling to empirical analyses of sexual networks and HIV transmission. Network modeling is used to study the impact of non-random mixing on the spread of disease. People employ complex rules for choosing sexual partners--selecting on attributes such as age, race, gender, and sexual preference, as well as a host of other socioeconomic signals--and the biases that structure their networks also operate to channel HIV. In general, the more extended and intimate the contact between partners, the stronger the selective bias in choosing them. Diseases that require intimate contact for transmission are thus affected by stronger network biases than diseases passed by casual contact. Network structure is now recognized to have an important role in the sexual spread of HIV and other STDs. While the pace of theoretical and methodological research in this area has been impressive, it has not been matched by empirical studies of network-mediated HIV transmission in different populations, or guided by the goal of finding effective and efficient interventions. These are the two goals of this project. The project will involve detailed comparative analysis of two recent sexual network studies, one from Thailand (field period 1992-93) and the other from Uganda (field period 1994). The two countries represent different phases of the epidemic, young and mature respectively. Both studies have highly comparable quantitative and qualitative data. The analysis has five specific aims: (1) to refine existing network methods for epidemiological modeling; (2) to identify the key components of network "structure" for predicting HIV transmission dynamics; (3) to investigate the interaction between biomedical and network-related behavioral aspects of transmission; (4) to investigate the impact of network-channeled disease on demographic processes of fertility and mortality; and (5) to use the network-based projection methods to identify strategic points of intervention. The comparative approach adopted here should help to distinguish both the common and the culturally-specific features that are important for understanding and intervention. Some aspects of the network transmission dynamics are expected have fairly universal applicability (the importance of age-matching, for example), and comparative analysis will highlight how these aspects operate in specific contexts. Other aspects will be culturally specific (for example, the organization of commercial sex, and the patterns of simultaneous partnerships). Here, comparative analysis will identify the effects of such culturally-specific structures on the spread of the epidemic, and highlight the context sensitivity of intervention development. The goal is to take "network modeling" beyond its current status as a metaphor standing for an ad-hoc collection of incompatible methods, and make it a more useful tool for understanding and intervention in epidemiology.
Please send comments or suggestions to
morrism@u.washington.edu.
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