Rapid social network assessment for predicting HIV and STI risk among men attending bars and clubs in San Diego, California

Objectives To test the use of a rapid assessment tool to determine social network size, and to test whether social networks with a high density of HIV/sexually transmitted infection (STI) or substance using persons were independent predictors of HIV and STI status among men who have sex with men (MSM) using a rapid tool for collecting network information. Methods We interviewed 609 MSM from 14 bars in San Diego, California, USA, using an enhanced version of the Priorities for Local AIDS Control Efforts (PLACE) methodology. Social network size was assessed using a series of 19 questions of the form ‘How many people do you know that have the name X?’, where X included specific male and female names (eg, Keith), use illicit substances, and have HIV. Generalised linear models were used to estimate average and group-specific network sizes, and their association with HIV status, STI history and methamphetamine use. Results Despite possible errors in ascertaining network size, average reported network sizes were larger for larger groups. Those who reported having HIV infection or having past STI reported significantly more HIV infected and methamphetamine or popper using individuals in their social network. There was a dose-dependent effect of social network size of HIV infected individuals on self-reported HIV status, past STI and use of methamphetamine in the last 12 months, after controlling for age, ethnicity and numbers of sexual partners in the last year. Conclusions Relatively simple measures of social networks are associated with HIV/STI risk, and may provide a useful tool for targeting HIV/STI surveillance and prevention.

[1]  Tian Zheng,et al.  How Many People Do You Know in Prison? , 2006 .

[2]  C. McCarty,et al.  Comparing Two Methods for Estimating Network Size , 2001 .

[3]  J. T. Boerma,et al.  From people to places: focusing AIDS prevention efforts where it matters most , 2003, AIDS.

[4]  J. Wasserheit,et al.  The dynamic topology of sexually transmitted disease epidemics: implications for prevention strategies. , 1996, The Journal of infectious diseases.

[5]  K. Holmes,et al.  Do People Really Know Their Sex Partners?: Concurrency, Knowledge of Partner Behavior, and Sexually Transmitted Infections Within Partnerships , 2004, Sexually transmitted diseases.

[6]  A. Ghani,et al.  Sampling biases and missing data in explorations of sexual partner networks for the spread of sexually transmitted diseases. , 1998, Statistics in medicine.

[7]  T. Farley,et al.  Networks of persons with syphilis and at risk for syphilis in Louisiana: evidence of core transmitters. , 1999, Sexually transmitted diseases.

[8]  S. Frost Using sexual affiliation networks to describe the sexual structure of a population , 2007, Sexually Transmitted Infections.

[9]  H. Russell Bernard,et al.  Investigating the Variation of Personal Network Size Under Unknown Error Conditions , 2006 .

[10]  E. Laumann,et al.  Social Network Effects on the Transmission of Sexually Transmitted Diseases , 2002, Sexually transmitted diseases.

[11]  H. Russell Bernard,et al.  A social network approach to estimating seroprevalence in the United States , 1998 .

[12]  C. Ison,et al.  Gonorrhoea in London: usefulness of first line therapies , 2002, Sexually transmitted infections.

[13]  J. Spencer,et al.  A pilot study of a rapid assessment method to identify places for AIDS prevention in Cape Town, South Africa , 2002, Sexually transmitted infections.

[14]  M. Keeling,et al.  Networks and epidemic models , 2005, Journal of The Royal Society Interface.

[15]  L Dean,et al.  Social and sexual networks: their role in the spread of HIV/AIDS among young gay men. , 1995, AIDS education and prevention : official publication of the International Society for AIDS Education.

[16]  S. Gregorich,et al.  The Influence of Social and Sexual Networks in the Spread of HIV and Syphilis Among Men Who Have Sex With Men in Shanghai, China , 2007, Journal of acquired immune deficiency syndromes.