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BMC Public Health. 2011; 11(Suppl 1): S10.
Published online 2011 February 25. doi:  10.1186/1471-2458-11-S1-S10
PMCID: PMC3317580

Exploring the effect of biological delays in kinetic models of influenza within a host or cell culture

Abstract

Background

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.

Results

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.

Conclusions

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.


Articles from BMC Public Health are provided here courtesy of BioMed Central