Estimating Case Fatality Ratios from Infectious Disease Surveillance Data

• Activity Number: 592
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Nicholas G. Reich*+ and Justin Lessler and Ron Brookmeyer
• Companies: The Johns Hopkins University and The Johns Hopkins University and The Johns Hopkins University
• Keywords: case fatality ratio ; infectious disease ; incomplete data ; missing data ; influenza

Abstract

Knowing which groups are most at risk from an emerging infectious disease is crucial in deciding the optimal allocation of resources during an outbreak response. The case fatality ratio is the fraction of cases who die after contracting a disease. Incomplete reporting of the number of infected individuals, both recovered and dead, can lead to biased estimates of the case fatality ratio. We propose an estimator for the relative case fatality ratio that controls for reporting rates that may vary across time. We generalize our methods to account for elapsed time between infection and death. We conduct a simulation study to evaluate the performance of our methods in realistic outbreak scenarios. Our new methods could provide valuable information to identify vulnerable subpopulations early in an outbreak of an emerging pathogen such as pandemic H1N1 influenza.