Real-time Estimates in Early Detection of SARS

Real-time Estimates in Early Detection of SARS

Pierre-Yves Boelle, Roy M. Anderson, Anthony J. Hedley, Christl A. Donnelly, Neil M. Ferguson, Gabriel M. Leung, Alain-Jacques Valleron, Simon Cauchemez, Guy Thomas

We propose a Bayesian statistical framework for estimating the reproduction number R early in an epidemic. This method allows for the yet-unrecorded secondary cases if the estimate is obtained before the epidemic has ended. We applied our approach to the severe acute respiratory syndrome (SARS) epidemic that started in February 2003 in Hong Kong. Temporal patterns of R estimated after 5, 10, and 20 days were similar. Ninety-five percent credible intervals narrowed when more data were available but stabilized after 10 days. Using simulation studies of SARS-like outbreaks, we have shown that the method may be used for early monitoring of the effect of control measures.

2006

Communicable diseases, Epidemiologic methods, Population surveillance, Disease Outbreaks, Emerging, severe acute respiratory syndrome

DOI: 10.3201/eid1201.050593

Emerging Infectious Diseases

Centers for Disease Control and Prevention

Infectious and parasitic diseases, Medicine