  Purpose: The use of cumulative measures of exposure to raised HIV viral load
(viremia copy-years) is an increasingly common in HIV prevention and treatment
epidemiology due to the high biological plausibility. We sought to estimate the
magnitude and direction of bias in a cumulative measure of viremia caused by
different frequency of sampling and duration of follow-up.
  Methods: We simulated longitudinal viral load measures and reanalysed cohort
study datasets with longitudinal viral load measurements under different
sampling strategies to estimate cumulative viremia.
  Results: In both simulated and observed data, estimates of cumulative viremia
by the trapezoidal rule show systematic upward bias when there are fewer
sampling time points and/or increased duration between sampling time points,
compared to estimation of full time series. Absolute values of cumulative
viremia vary appreciably by the patterns of viral load over time, even after
adjustment for total duration of follow up.
  Conclusions: Sampling bias due to differential frequency of sampling appears
extensive and of meaningful magnitude in measures of cumulative viremia.
Cumulative measures of viremia should be used only in studies with sufficient
frequency of viral load measures and always as relative measures.
