Estimating the stage‐specific numbers of HIV infection using a markov model and back‐calculation

Abstract

The back-calculation method has been used to estimate the number of HIV infections from AIDS incidence data in a particular population. We present an extension of back calculation that provides estimates of the numbers of HIV infectives in different stages of infection. We model the staging process with a timedependent Markov process that partitions the HIV infectious period into the following progressive stages and/or substages: stage 1, infected but antibody negative; substages 2–3; antibody positive but asymptomatic; substages 4–6, pre-AIDS symptoms and/or abnormal haematologic indicator; stage 7, clinical AIDS. We also model an eighth stage, deceased due to AIDS. The model allows for time-dependent treatment effects that slow the rate of progression in substages 4–7. We use the estimated AIDS incubation period distribution from the Markov model in back calculation from AIDS incidence data to estimate the total number of HIV infections and the parameters of the infection probability distribution. We then use these estimates in the Markov model to estimate the stage-specific numbers of HIV infections over the course of the epidemic in the population under study. Example calculations employ data for the HIV epidemic in San Francisco City Clinic Cohort.