Previous studies have suggested that following influenza virus infection, viral load rises to a peak around the time of illness onset and then, for influenza A, declines approximately log-linearly over the subsequent 5210 days to undetectable levels and, for influenza B, plateaus with a more gradual decline [6, 7] . We specified multivariable linear regression models for the log viral load on the first and third measurement (typically 0 and 7 days, respectively, after recruitment), with the same slope but separate intercepts for each individual to allow for between-person variability in peak viral loads. We fitted separate models for each study and for influenza A and B and adjusted for age and oseltamivir treatment. Interaction terms with time were included to allow the slope of the regression line to vary by age and oseltamivir treatment. Viral loads for specimens with measured load below the lower limit of quantification (LLOQ) were imputed as half the LLOQ. This random-effects regression model constructed using the first and third measurement was used to predict viral loads expected on the second measurement (typically 3 days after recruitment), which were then compared with the observed viral loads on the second swabs, which were collected by the patients in IRIS and by an HCP in the HTS. We calculated mean differences with 95% confidence intervals (CIs) based on the t distribution.