Article

Sexual networks and the transmission of HIV in London.

Department of Epidemiology and Public Health, Imperial College of Science, Technology and Medicine, University of London, UK.
Journal of Biosocial Science (Impact Factor: 0.98). 02/1998; 30(1):63-83. DOI: 10.1017/S0021932098000637
Source: PubMed

ABSTRACT This paper discusses ways in which empirical research investigating sexual networks can further understanding of the transmission of HIV in London, using information from a 24-month period of participant observation and 53 open-ended, in-depth interviews with eighteen men and one woman who have direct and indirect sexual links with each other. These interviews enabled the identification of a wider sexual network between 154 participants and contacts during the year August 1994-July 1995. The linked network data help to identify pathways of transmission between individuals who are HIV+ and those who are HIV-, as well as sexual links between 'older' and 'younger' men, and with male prostitutes. There appears to be considerable on-going transmission of HIV in London. The majority of participants reported having had unprotected anal and/or vaginal sex within a variety of relationships. The implications of these findings for policies designed to prevent the transmission of HIV are discussed.

0 Bookmarks
 · 
53 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article explores the relationship between sexual network structure and epidemic phase in sexually transmitted disease epidemiology, and discusses how this may be used to inform prevention strategies at the population level. There are relatively few empirical studies of sexual networks, and even fewer that track the evolution of networks over time. Most studies focus on networks in the context of disease transmission and will miss the network structure in the wider population. Results from disease-related studies in the early epidemic phase show densely connected networks with multiple short loops. In later hyperendemic phases, networks appear more loosely connected with a dominance of long branching structures. The latter structure has also been described from non-diseased populations. These structures evolve over time, both of the epidemic curve and as a cohort ages and undergoes demographic change. Population strategies for prevention should vary depending on network structure and epidemic phase. In early and late epidemic phases, interventions focusing on high-risk populations--that is, dense areas of a sexual network--will have a large population effect. In contrast, for established endemic diseases a smaller change (of behaviour or interruption of transmission through screening) in a larger proportion of the population could have the largest population impact. Further empirical work on the way network structures relate to epidemic phase, and how this changes with age and social development will help to inform intervention strategies at the population level.
    Sexually Transmitted Infections 08/2007; 83 Suppl 1:i43-49. · 3.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: : This article reviews the current issues and advancements in social network approaches to HIV prevention and care. Social network analysis can provide a method to understand health disparities in HIV rates, treatment access, and outcomes. Social network analysis is a valuable tool to link social structural factors to individual behaviors. Social networks provide an avenue for low-cost and sustainable HIV prevention interventions that can be adapted and translated into diverse populations. Social networks can be utilized as a viable approach to recruitment for HIV testing and counseling, HIV prevention interventions, optimizing HIV medical care, and medication adherence. Social network interventions may be face-to-face or through social media. Key issues in designing social network interventions are contamination due to social diffusion, network stability, density, and the choice and training of network members. There are also ethical issues involved in the development and implementation of social network interventions. Social network analyses can also be used to understand HIV transmission dynamics.
    JAIDS Journal of Acquired Immune Deficiency Syndromes 06/2013; 63 Suppl 1:S54-8. · 4.39 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Many models of infectious disease ignore the underlying contact structure through which the disease spreads. However, in order to evaluate the efficacy of certain disease control interventions, it may be important to include this network structure. We present a network modeling framework of the spread of disease and a methodology for inferring important model parameters, such as those governing network structure and network dynamics, from readily available data sources. This is a general and flexible framework with wide applicability to modeling the spread of disease through sexual or close contact networks. To illustrate, we apply this modeling framework to evaluate HIV control programs in sub-Saharan Africa, including programs aimed at concurrent partnership reduction, reductions in risky sexual behavior, and scale up of HIV treatment.
    Health Care Management Science 03/2011; 14(2):174-88. · 1.05 Impact Factor

Full-text (2 Sources)

Download
13 Downloads
Available from
May 29, 2014