Copyright © 2004 by the Johns Hopkins Bloomberg School of Public Health
ORIGINAL CONTRIBUTIONS |
Invited Commentary: Real-Time Tracking of Control Measures for Emerging Infections
1 Department of Epidemiology, Harvard School of Public Health, Boston, MA.
2 Department of Biology, University of Washington, Seattle, WA.
Received for publication May 17, 2004; accepted for publication June 3, 2004.
| The first 150 words of the full text of this article appear below. |
Health officials faced a daunting task with the emergence of severe acute respiratory syndrome (SARS) last year: forecasting the trajectory of an emerging infectious disease and implementing effective control measures, even as the etiologic agent was still being identified. Investigators initially had little to go on beyond crude epidemiologic data such as the timing of new cases (the epidemic curve). With such limited data, it was difficult to disentangle two fundamental epidemiologic quantities: the time from one transmission of the infection to the next, known as the serial interval or generation time, and the average number of secondary cases resulting from each infection, known as the reproductive number.
A simple example illustrates the problem. Compare two idealized diseases, A and B. Disease A has a short generation time of 4 days but has relatively low transmissibility, such that each primary infection generates two secondary infections. Disease B has a longer
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  SARS: The Effect of Control Measures Journal Watch Infectious Diseases, November 5, 2004; 2004(1105): 8 - 8. [Full Text]
|
|
|
|
 |
|
 J. Wallinga and P. Teunis Wallinga and Teunis Respond to "Real-Time Tracking of Infection Control Measures" Am. J. Epidemiol., September 15, 2004; 160(6): 520 - 520. [Full Text] [PDF]
|
|