Indices to measure risk of HIV acquisition in Rakai, Uganda.
BACKGROUND
Targeting most-at-risk individuals with HIV preventive interventions is cost-effective. We developed gender-specific indices to measure risk of HIV among sexually active individuals in Rakai, Uganda.


METHODS
We used multivariable Cox proportional hazards models to estimate time-to-HIV infection associated with candidate predictors. Reduced models were determined using backward selection procedures with Akaike's information criterion (AIC) as the stopping rule. Model discrimination was determined using Harrell's concordance index (c index). Model calibration was determined graphically. Nomograms were used to present the final prediction models.


RESULTS
We used samples of 7,497 women and 5,783 men. 342 new infections occurred among females (incidence 1.11/100 person years,) and 225 among the males (incidence 1.00/100 person years). The final model for men included age, education, circumcision status, number of sexual partners, genital ulcer disease symptoms, alcohol use before sex, partner in high risk employment, community type, being unaware of a partner's HIV status and community HIV prevalence. The Model's optimism-corrected c index was 69.1 percent (95% CI = 0.66, 0.73). The final women's model included age, marital status, education, number of sex partners, new sex partner, alcohol consumption by self or partner before sex, concurrent sexual partners, being employed in a high-risk occupation, having genital ulcer disease symptoms, community HIV prevalence, and perceiving oneself or partner to be exposed to HIV. The models optimism-corrected c index was 0.67 (95% CI = 0.64, 0.70). Both models were well calibrated.


CONCLUSIONS
These indices were discriminative and well calibrated. This provides proof-of-concept that population-based HIV risk indices can be developed. Further research to validate these indices for other populations is needed.
Rakai Health Sciences Program, Entebbe, Uganda; Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Joseph
J
Kagaayi
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Ronald H
RH
Gray
Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States of America.
Christopher
C
Whalen
Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Pingfu
P
Fu
Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Duncan
D
Neuhauser
Department of Anthropology, Case Western Reserve University, Cleveland, Ohio, United States of America.
Janet W
JW
McGrath
Makerere University College of Health Sciences, Kampala, Uganda.
Nelson K
NK
Sewankambo
Makerere University College of Health Sciences, Kampala, Uganda.
David
D
Serwadda
Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Godfrey
G
Kigozi
Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Fred
F
Nalugoda
Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America; Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
Steven J
SJ
Reynolds
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Maria J
MJ
Wawer
Deparment of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Mendel E
ME
Singer
D000293:Adolescent; D000328:Adult; D015331:Cohort Studies; D005260:Female; D015658:HIV Infections / Q000453:epidemiology / Q000209:etiology*; D015497:HIV-1; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012737:Sex Factors; D012725:Sexual Behavior / Q000706:statistics & numerical data; D014454:Uganda / Q000453:epidemiology; D055815:Young Adult