This article is part of the supplement: Mathematical Modelling of Influenza
Exploring the effect of biological delays in kinetic models of influenza within a host or cell culture
Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada
BMC Public Health 2011, 11(Suppl 1):S10 doi:10.1186/1471-2458-11-S1-S10Published: 25 February 2011
For a typical influenza infection in vivo, viral titers over time are characterized by 1–2 days of exponential growth followed by an exponential decay. This simple dynamic can be reproduced by a broad range of mathematical models which makes model selection and the extraction of biologically-relevant infection parameters from experimental data difficult.
We analyze in vitro experimental data from the literature, specifically that of single-cycle viral yield experiments, to narrow the range of realistic models of infection. In particular, we demonstrate the viability of using a normal or lognormal distribution for the time a cell spends in a given infection state (e.g., the time spent by a newly infected cell in the latent state before it begins to produce virus), while exposing the shortcomings of ordinary differential equation models which implicitly utilize exponential distributions and delay-differential equation models with fixed-length delays.
By fitting published viral titer data from challenge experiments in human volunteers, we show that alternative models can lead to different estimates of the key infection parameters.