Network analysis and network theory have emerged in various strands of research on HIV. Epidemiological research has used network analysis to map and predict the course of the HIV and STI epidemics among Gay men (Doherty et al. 2005; Piqueira et al. 2004). It constitutes an advance on cruder epidemiological models of random mixing (see Keeling & Eames 2005). Social network analysis and social attachment have been important concepts in informing more recent HIV prevention interventions (see Fernandez et al. 2003; Latkin and Knowlton 2005) and have had specific applications in the case of disadvantaged communities such as injecting drug users and sex workers (Latkin et al. 2003; Rhodes et al. 2005). Moreover, network analysis has been useful in understanding social support of disadvantaged groups living with HIV such as African migrants and ethnic minority women (Hough et al. 2005; Asander et al. 2004; Sivaram et al. 2005).
Considering a Gay man as part of a social network involves engaging with the social and cultural factors that shape his experience. Rather than thinking of his relationships as essentially random, we characterise them as being profoundly influenced by his social environment; an environment made up by other individuals who share common understandings and social norms. This social network is generally self-perpetuating and limited. Individuals come into contact and hence derive friends and partners from this finite network. Network analysis is especially valuable when examining a population that is highly heterogeneous and made up of individuals who enter that population as autonomous adults. Gay men are such a population being made up of socially mobile individuals deriving from a range of social, ethnic and geographical backgrounds.
Social networks are central to our understanding of the dynamics of HIV risk among Gay men. The nature and density of social networks have been found to be connected to sexual risk practices and susceptibility to HIV infection in Gay men (Smith et al. 2004). Moreover, networks influence Gay men’s perceptions and understandings of the HIV epidemic (Grierson 2005). In addition, social networks may have a role in influencing an individuals’ knowledge and understandings of, and access to new technologies such as PEP (see Dodds & Hammond 2006; Korner et al. 2005). Social norms have been found to be important in influencing Gay men’s attitudes towards safer sex and risk-taking especially among groups that have been traditionally disempowered or marginalised such as young Gay men (see Amirkhanian et al. 2005a) and Black/ethnic minority Gay men (see Wilson et al. 2002; Peterson et al. 2003; Zea et al. 2005). Finally social network analysis has been useful in describing social support for Gay men living with HIV and their carers (Shippy et al. 2003; White and Cant 2003; Cant 2004; Zea et al. 2005).
A range of HIV prevention interventions have been based around social networks and innovation diffusion theory (see Amirkhanian et al. 2005a). Such interventions would seem to have most salience with disadvantaged groups of Gay and Bisexual men and have achieved some success (see Amirkhanian et al. 2005b). Other authors point out the limitations of network interventions in reaching men at relatively low risk or stress limitations in their efficacy over time (see Martin et al. 2003).
Findings from the 2003 Gay Men’s Sex Survey (GMSS) highlight the importance of proximity to HIV. That is, men in certain social and cultural networks had limited experience of HIV in their social network and these men tended to have greater HIV prevention need (see Reid et al. 2004). GMSS 2003 established a range of indicators to measure personal and social proximity to the epidemic.
These included:
• Having tested for HIV.
• Not having tested positive, but believing you are or could be infected.
• Being in or having had a sero-discordant relationship.
• Personally knowing someone with HIV.
At the population level proximity to HIV was mediated by a range of demographic factors.
• Area of residence: Men resident in London had greater proximity than men resident elsewhere, although men with low proximity to HIV were present in every city and town and in every area of the UK.
• Age: Men in their 30's and 40's had greater proximity than either older or younger men.
• Ethnicity: Black men and White men of ethnicities other than British had greater proximity than men in other ethnic groups.
• Education: Better educated men had greater proximity (even though less well educated men were more likely to have HIV).
• Income: Men in higher income brackets had greater proximity than men in lower income brackets.
• Gender of sexual partners: Exclusively homosexually active men had greater proximity to HIV than men who were behaviourally bisexual.
• Numbers of male partners: Men with greater numbers of partners had greater proximity than men with fewer partners.
While these differences are important it is essential to note that they denote difference at the population level. In fact, there are men with low proximity to HIV in every city and town in the UK (including London); in every age group and ethnic group; with every level of formal education and at every income level; and with a range of sexual identities and sexual practices.
These population differences in proximity to HIV present an interesting health promotion dilemma. Those men with greatest proximity have less unmet needs but are more likely to be involved in HIV exposure. Those with less proximity have the greatest unmet need and will therefore be vulnerable if they do come into contact with HIV (either knowingly or unknowingly) but they are probably less likely to do so. In response, the original research recommends “a diverse portfolio of interventions that are encountered by men with a wide variety of relationships to HIV” (Reid et al. 2004).
The study presented in this report is in response to these findings. That is, a qualitative examination of social proximity to the epidemic among Gay men. However, we must start with a caveat. Neither GMSS nor this study measures actual proximity to HIV, that is the numbers of social and sexual contacts an individual has who are actually HIV positive, or the percentages of a social network who are actually positive. Rather, GMSS sets up a range of proxy markers to indicate proximity (such as testing history, beliefs about one’s own status and beliefs about the HIV status of social and sexual partners). Likewise, this study measures perceptions of proximity to the epidemic rather than actual proximity (to study actual proximity would require an ambitious network analysis where we recruited all the social and sexual contacts of respondents and asked them about their actual or known HIV status). Studying men’s perceptions of their proximity to the epidemic allows us to examine the ways in which men’s perceptions of their social surroundings influence how they experience and negotiate sexual risk. Moreover, an individual’s perception of the world around him influences the types of information and messages he is likely to notice. The purpose of this study is to inform the nature of interventions targeting men based on their perceived proximity to the epidemic. We will do so by exploring how their perceptions of proximity influence management of HIV-related sexual risk among men who assume or know themselves to be HIV negative
