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American Journal of Epidemiology Advance Access originally published online on August 2, 2005
American Journal of Epidemiology 2005 162(5):479-486; doi:10.1093/aje/kwi230
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American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved

ORIGINAL CONTRIBUTIONS

Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease

A. C. Ghani1, C. A. Donnelly1, D. R. Cox2, J. T. Griffin1, C. Fraser1, T. H. Lam3, L. M. Ho3, W. S. Chan4, R. M. Anderson1, A. J. Hedley3 and G. M. Leung3

1 Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
2 Nuffield College, University of Oxford, Oxford, United Kingdom
3 Department of Community Medicine, University of Hong Kong, Hong Kong, People's Republic of China
4 Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong, People's Republic of China

Correspondence to Dr. Azra Ghani, Infectious Disease Epidemiology Unit, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom (e-mail: azra.ghani{at}lshtm.ac.uk).

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.

case-fatality ratio; Kaplan-Meier estimator; SARS virus; survival analysis

Abbreviations: SARS, severe acute respiratory syndrome


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