Cellular turnover rates in the immune system can be determined by labelling dividing cells with 5-bromo-2'-deoxyuridine (BrdU) or deuterated glucose ((2)H-glucose). To estimate the turnover rate from such measurements one has to fit a particular mathematical model to the data. The biological assumptions underlying various models developed for this purpose are controversial. Here, we fit a series of different models to BrdU data on CD4(+) T cells from SIV(-) and SIV(+) rhesus macaques. We first show that the parameter estimates obtained using these models depend strongly on the details of the model. To resolve this lack of generality we introduce a new parameter for each model, the 'average turnover rate', defined as the cellular death rate averaged over all subpopulations in the model. We show that very different models yield similar estimates of the average turnover rate, i.e. ca. 1% day(-1) in uninfected monkeys and ca. 2% day(-1) in SIV-infected monkeys. Thus, we show that one can use BrdU data from a possibly heterogeneous population of cells to estimate the average turnover rate of that population in a robust manner.