A comparison of methods for extracting influenza viral titer characteristics

Viral titer data collected in vitro or in vivo is often analyzed by extracting viral titer characteristics such as peak viral titer, time of viral peak and area under the curve (AUC). Researchers compare these characteristics in the absence and presence of various concentrations of antivirals in an attempt to quantify the effect of antivirals. Often these characteristics are estimated using only measured data points, although fitting of simple mathematical models to estimate these parameters is becoming more prevalent. In this article, our aim is to compare the estimates of different viral titer characteristics using three different approaches. The first approach is the traditional method that uses estimates based on experimentally measured data. The second approach relies on the use of a linear model to fit the viral titer data. The third approach uses an exponential model for the fitting process and the parameters of interest are extracted from there. The mathematical models are tested using in vivo and in vitro influenza infection data. Estimates of viral titer characteristics using either of the two fitting approaches were similar, but differed from estimates using the traditional method.