Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease
Identifieur interne : 004E80 ( Main/Merge ); précédent : 004E79; suivant : 004E81Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease
Auteurs : A. C. Ghani [Royaume-Uni] ; C. A. Donnelly [Royaume-Uni] ; D. R. Cox [Royaume-Uni] ; J. T. Griffin [Royaume-Uni] ; C. Fraser [Royaume-Uni] ; T. H. Lam [République populaire de Chine] ; L. M. Ho [République populaire de Chine] ; W. S. Chan [République populaire de Chine] ; R. M. Anderson [Royaume-Uni] ; A. J. Hedley [République populaire de Chine] ; G. M. Leung [République populaire de Chine]Source :
- American Journal of Epidemiology [ 0002-9262 ] ; 2005.
Abstract
During the course of an epidemic of a potentially fatal disease, it is important that the case fatality ratio be well estimated. The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital.
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DOI: 10.1093/aje/kwi230
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The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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