Jacob Norton

Predicting HIV seroconversion in discordant couples

Often the risk of disease acquisition from a single event, such as an 
unprotected sex act, is small and difficult to interpret. However, when 
risky behaviors are repeated it is possible to forecast disease 
acquisition. In our study we consider the development of HIV 
seroconversion trajectories based on risk-bearing events that can occur 
at different time scales. We consider existing estimates of HIV 
transmission risks through injecting and sexual contacts to develop a 
predictive seroconversion model for an individual who is exposed to HIV 
primarily through intimate relationships with a partner known to have 
HIV, known as a discordant couple or discordant pair. We simulate 
time-to-event curves for a number of behavioral scenarios and 
particularly focus on sources of simulated uncertainty. In particular, 
we consider uncertainty in estimates of transmission risk and 
uncertainty in study subject responses. We apply the model to a 
longitudinal study of HIV-discordant pairs and discuss model validation 
based on order statistics.