Viral burden in genital secretions determines male-to-female sexual transmission of HIV-1: a probabilistic empiric model
Chakraborty, H., Sen, P. K., Helms, R. W., Vernazza, P. L., Fiscus, S. A., Eron, J. J., ... Cohen, M. S. (2001). Viral burden in genital secretions determines male-to-female sexual transmission of HIV-1: a probabilistic empiric model. AIDS, 15(5), 621-627.
Objective: To develop a model to predict transmission of HIV-1 from men to women.
Design: HIV-1 in seminal plasma, and endocervical CCR5 receptors were correlated with epidemiological studies of HIV-1 transmission to develop a probabilistic model.
Settings: Semen samples were collected from patient subjects in Seattle Washington, Chapel Hill, North Carolina, and St. Gallen, Switzerland. Endocervical biopsy specimens were obtained from women in Chicago, Illinois.
Participants: Eighty-six men (not receiving antireroviral therapy) in whom CD4 cell count and semen volume were available, and 24 women in whom the number of endocervical CCR5 receptors were determined.
Main outcome measures: Prediction of transmission of HIV-1 from men to women per episode of vaginal intercourse based on the absolute burden of HIV (volume x HIV RNA copies/ml seminal plasma).
Results: The model suggests efficient heterosexual transmission of HIV-1 when semen viral burden is high. When semen contains 100 000 copies of non-syncytium-inducing (NSI) HIV RNA the probability of HIV-1 transmission is 1 per 100 episodes of intercourse; conversely, with 1000 copies NSI HIV RNA in semen, transmission probability is 3 per 10 000 episodes of intercourse.
Conclusions: This model links biological and epidemiological data related to heterosexual HIV-1 transmission. The model can be used to estimate transmission of HIV from men with high semen viral burden from inflammation, or reduced burden after antiretroviral therapy. The results offer a biological explanation for the magnitude of the HIV epidemic in places where earlier studies have shown men have high semen viral burden, such as in sub-Saharan Africa. The model can be used to develop and test HIV-1 prevention strategies.