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Methods for estimating the case fatality ratio for a novel, emerging infectious disease
A C Ghani1, C A Donnelly, D R Cox
1Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. azra.ghani@lshtm.ac.uk
American Journal of Epidemiology
|August 4, 2005
Summary
Estimating disease fatality is crucial during epidemics. A new Kaplan-Meier survival method, considering death and recovery, provides a more accurate case fatality ratio, especially when analyzing patient subgroups by age.
Area of Science:
- Epidemiology
- Biostatistics
- Public Health
Background:
- Accurate estimation of the case fatality ratio (CFR) is vital for managing fatal disease epidemics.
- Traditional CFR estimation methods can be imprecise, particularly during the evolving stages of an outbreak.
Purpose of the Study:
- To introduce and evaluate a novel method for estimating the case fatality ratio (CFR) during epidemics.
- To compare the proposed method's performance against existing estimation techniques using real-world epidemic data.
Main Methods:
- The study utilizes the Kaplan-Meier survival procedure, incorporating both death and recovery outcomes.
- Performance evaluation is conducted using data from the 2003 severe acute respiratory syndrome (SARS) epidemic in Hong Kong.
- Subgroup analysis based on patient age at hospital admission is performed to assess the impact of characteristics on outcomes.
Main Results:
- The novel Kaplan-Meier-based method provides more accurate CFR estimates compared to naive methods at various epidemic points.
- The proposed method's estimates closely align with the eventually observed CFR.
- Patient characteristics, such as age, significantly influence outcomes, highlighting the importance of subgroup analysis.
Conclusions:
- The proposed Kaplan-Meier-based approach offers a robust and accurate method for estimating case fatality ratios during epidemics.
- Considering both death and recovery outcomes simultaneously improves estimation accuracy.
- Age-specific analysis is crucial for understanding disease impact and informing public health interventions.
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