Egocentric network data provide additional information for characterizing an individual's HIV risk profile.

OBJECTIVE: We investigated the hypothesis that partner-specific characteristics are important to improve an individual's risk characterization.
DESIGN: It has been shown that the egocentric network structure is important to establish a person's risk for infection.
METHODS: The study was cross-sectional in its design and enrolled 1231 volunteers at one HIV testing site in Rio de Janeiro, Brazil, and applied an adapted ego-network questionnaire. Each individual was interviewed about their own risk factors and those related to up to 10 sex partners. We used the dyadic data analysis method in which each relationship forms a record. Two receiver operator characteristic curves were generated, and the ability to correctly predict volunteers' HIV serostatus based on a model with characteristics of volunteers and sex partners and another with only volunteers' characteristics was evaluated.
RESULTS: Partner-related variables were associated with HIV serostatus both for men and women. The model with volunteer/sex partners' characteristics performed better in discriminating between HIV-positive and negative volunteers only for men but not for women. The c statistic for men volunteers was 0.82 [95% confidence interval (CI) 0.77-0.87] for the volunteer alone model and 0.88 (95% CI 0.86-0.91) for the combined model (P = 0.03). The values for women were 0.75 (95% CI 0.65-0.86) and 0.78 (95% CI 0.71-0.85), respectively (P = 0.71).
CONCLUSION: Ego-network theory-based approaches provide additional information for characterizing risk for HIV infection among men.