Viral load fluctuates during the natural course of asymptomatic HIV-1 infection. It is often assumed that these fluctuations are random around a set point or underlying growth trend. Using longitudinal data, we tested whether fluctuations in viral load can be better explained by changes in CD4+ T-cell count than by a set point or trend of exponential growth. The correspondence between viral load and CD4+ T-cell count could be described by a simple mathematical relation. Using a bootstrapping approach, the hypothesis that viral load fluctuations are random around a set point was rejected with p < .00005. The hypothesis that viral load fluctuations are random around a trend of exponential growth was rejected with p < .005. Viral load data was explained better by changes in CD4+ T-cell counts than by a set point or by a trend of exponential growth. The implications of this finding for improved prognostication are discussed.