Statistical models to estimate male-to-female HIV transmission probabilities

To develop effective public-health intervention strategies for preventing person-to-person disease transmission, it is extremely essential to know the underlying biological processes and the probability of transmission. However, it is unethical to design studies to estimate the probability of person-to-person disease transmission because such studies would involve infecting an uninfected person with a disease. Statistical modeling is a very important technique used to estimate disease transmission probabilities among individuals. By using data from different independent studies, researchers may be able to obtain enough information about an infected person's infectiousness and the susceptibility of an uninfected person to estimate disease transmission probabilities. In this paper, we developed a statistical modeling technique to estimate probabilities of person-to-person disease transmission from an infected to an uninfected person. We used this new modeling technique to estimate the probability of male-to-female, penile-vaginal human immunodeficiency virus (HIV) transmission in one sexual contact. We developed two different sets of male-to-female HIV transmission probability estimates for different infectiousness and susceptibility values using two models. This newly developed modeling technique can be used to estimate person-to-person transmission probabilities for different diseases and routes of transmission.

Duke Scholars

Author Hrishikesh Chakraborty Biostatistics & Bioinformatics, Division of Biostatistics