tetano
Editor, Senior Moderator
Epidemiol Infect. 2011 Nov 14:1-12. [Epub ahead of print]
Using experimental human influenza infections to validate a viral dynamic model and the implications for prediction.
Chen SC, You SH, Liu CY, Chio CP, Liao CM.
Source
Department of Public Health, Chung Shan Medical University, Taichung, Taiwan, ROC.
Abstract
SUMMARYThe aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 103-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.
PMID:
22078059
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22078059
Using experimental human influenza infections to validate a viral dynamic model and the implications for prediction.
Chen SC, You SH, Liu CY, Chio CP, Liao CM.
Source
Department of Public Health, Chung Shan Medical University, Taichung, Taiwan, ROC.
Abstract
SUMMARYThe aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 103-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.
PMID:
22078059
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/22078059