Difference between revisions of "SARS: Dose Response Models"
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+  === '''<sup>*</sup>Recommended Model''' ===  
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+  It is recommended that the pooled experiments 1 and 2 should be used as the best doseresponse model. Both strains are common in outbreaks. The pooling narrows the range of the confidence region of the parameter estimates and enhances the statistical precision.  
==='''Optimized Models and Fitting Analyses'''===  ==='''Optimized Models and Fitting Analyses'''=== 
Revision as of 15:42, 5 October 2011
Contents
SARS
General overview
Coronaviruses cause acute and chronic respiratory, enteric, and central nervous system (CNS) diseases in humans and many species of animals. Coronaviruses are divided into three groups based on the genome sequences, including SARSCoV (a member of group II) as well as murine hepatitis virus (MHV), bovine coronavirus, porcine hemagglutinating encephalomyelitis virus (HEV), equine coronavirus, and human coronavirues OC43 and NL63, which also cause respiratory infections. SARSCoV, the causal pathogen of severe acute respiratory syndrome (SARS), caused a large outbreak of this severe pneumonia occurred in Hong Kong in 2003 and rapidly spread throughout the world. SARSCoV can infect and replicate in mice, ferrets, hamsters, cats, and several species of nonhuman primates (cynomolgus and rhesus macaques, African green monkeys, and marmosets). MHV that infects both mice and rats often has been studied as a suitable model of human coronavirus diseases (Watanabe et al. 2010).
Summary Data
DeDiego et al. (2008) challenged four groups of the tg mice intranasally with graded doses of rSARSCoV and the survival was monitored for 13 days.
De Albuquerque et al. (2006) inoculated A/J mice with MHV1 intranasally via intranasal route and monitored the survival for 21 days.

The data from experiments 1 and 2 were able to be statistically pooled.
^{*}Recommended Model
It is recommended that the pooled experiments 1 and 2 should be used as the best doseresponse model. Both strains are common in outbreaks. The pooling narrows the range of the confidence region of the parameter estimates and enhances the statistical precision.
Optimized Models and Fitting Analyses
Optimization Output for experiment 1



Optimization Output for experiment 2



Optimization Output for experiment 1 and 2



Summary
By increasing the number of data points, the pooling narrows the range of the confidence region of the parameter estimates and enhances the statistical precision.
References
De Albuquerque, N., Baig, E., Ma, X., Zhang, J., He, W., Rowe, A., Habal, M., Liu, M., Shalev, I., Downey, G.P., Gorczynski, R., Butany, J., Leibowitz, J., Weiss, S.R., McGilvray, I.D., Phillips, M.J., Fish, E.N. and Levy, G.A. (2006) Murine hepatitis virus strain 1 produces a clinically relevant model of severe acute respiratory syndrome in a/j mice Journal of Virology 80, 1038210394.
DeDiego, M.L., Pewe, L., Alvarez, E., Rejas, M.T., Perlman, S. and Enjuanes, L. (2008) Pathogenicity of severe acute respiratory coronavirus deletion mutants in hace2 transgenic mice. Virology 376, 379–389.
Watanabe, T., Bartrand, T.A., Weir, M.H., Omura, T. and Haas, C.N. (2010) Development of a doseresponse model for sars coronavirus. Risk Analysis 30, 11291138.