HIV infection dynamics in rural Andhra Pradesh south India: a sexual-network analysis exploratory study

AIDS Care. 2007 Oct;19(9):1171-6. doi: 10.1080/09540120701336392.


The southern state of Andhra Pradesh (AP) has one of the highest rates of HIV-1 infection in India. Estimates of HIV infection in rural areas have begun to approximate the urban. Methods of HIV transmission in rural India are poorly understood. We examined risk factors for HIV transmission in a group of rural villages in AP through the use of a sexual-network analysis survey - the Indian Health and Family Life Survey (IHFLS). The study sample included 20 HIV-positive and 40 HIV-negative matched controls randomly selected from a population-based, voluntary counselling and testing program in rural AP. HIV-1 status was confirmed by Western Blot. The 405-item IHFLS is based upon the National Health and Life Survey which has been validated in the US and China. The sample mean age was 37 years and 22% were of a tribal caste. Among female respondents, none were commercial sex workers (CSWs) and there were no significant social or behavioral associations with HIV infection. Among male respondents, ever having bought sex and having more than one lifetime partner were found to be significantly associated with HIV infection (p=0.002 and p=0.017). Amongst sub-populations, all men who had sex with men (MSM) were married. Tribals were more likely to report a concurrent sexual relationship (p=0.04). All high-risk men, including MSM, men who buy sex and men with multiple lifetime female partners did not use condoms. Public health interventions aimed at reducing HIV transmission in rural AP should consider targeting sub-populations of men who engage in covert MSM or CSW, high-risk tribal caste members and at-risk wives.

Publication types

  • Multicenter Study

MeSH terms

  • Adolescent
  • Adult
  • Case-Control Studies
  • Female
  • HIV Infections / epidemiology
  • HIV Infections / transmission*
  • Humans
  • India / epidemiology
  • Male
  • Odds Ratio
  • Risk Factors
  • Rural Health*
  • Sexual Behavior / statistics & numerical data*