Estimating the window period and incidence of recently infected HIV patients.
Incidence can be defined as the rate of occurence of new infections of a disease like HIV and is an useful estimate of trends in the epidemic. Annualised incidence can be expressed as a proportion, namely the number of recent infections per year divided by the number of people at risk of infection. This number of recent infections is dependent on the window period, which is basically the period of time from seroconversion to being classified as a long-term infection for the first time. The BED capture enzyme immunoassay was developed to provide a way to distinguish between recent and long-term infections. An optical density (OD) measurement is obtained from this assay. Window period is defined as the number of days since seroconversion, with a baseline OD value of 0, 0476 to the number of days to reach an optical density of 0, 8.The aim of this study is to describe different techniques to estimate the window period which may subsequently lead to alternative estimates of annualised incidence of HIV infection. These various techniques are applied to different subsets of the Zimbabwe Vitamin A for Mothers and Babies (ZVITAMBO) dataset. Three different approaches are described to analyse window periods: a non-parametric survival analysis approach, the fitting of a general linear mixed model in a longitudinal data setting and a Bayesian approach of assigning probability distributions to the parameters of interest. These techniques are applied to different subsets and transformations of the data and the estimated mean and median window periods are obtained and utilised in the calculation of incidence.