Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Published Online May 23, 2003
Science DOI: 10.1126/science.1086925

Perspectives

Submitted on May 16, 2003
Accepted on May 22, 2003

Modeling the SARS Epidemic

Chris Dye 1* Nigel Gay 2

1 Communicable Diseases, World Health Organization, 1211 Geneva 27, Switzerland.
2 Communicable Diseases, World Health Organization, 1211 Geneva 27, Switzerland; Health Protection Agency, Communicable Disease Surveillance Centre, London NW9 5EQ, UK.

* To whom correspondence should be addressed. E-mail: dyec{at}who.int.

Epidemiologists are still trying to understand how and why the SARS coronavirus has spread so readily throughout Asia and certain other regions of the world. In a Perspective, Dye and Gay discuss two new reports that use available data about the course of SARS infection to model the SARS epidemic (Lipsitch et al., Riley et al.).


THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Optimal control of epidemics in metapopulations.
R. E. Rowthorn, R. Laxminarayan, and C. A. Gilligan (2009)
J R Soc Interface 6, 1135-1144
   Abstract »    Full Text »    PDF »
Modelling control of epidemics spreading by long-range interactions.
B. Dybiec, A. Kleczkowski, and C. A. Gilligan (2009)
J R Soc Interface 6, 941-950
   Abstract »    Full Text »    PDF »
Contact heterogeneity in deer mice: implications for Sin Nombre virus transmission.
C. A Clay, E. M Lehmer, A. Previtali, S. St. Jeor, and M. D. Dearing (2009)
Proc R Soc B 276, 1305-1312
   Abstract »    Full Text »    PDF »
Data-driven exploration of 'spatial pattern-time process-driving forces' associations of SARS epidemic in Beijing, China.
J.-F. Wang, G. Christakos, W.-G. Han, and B. Meng (2008)
J. Public Health Med. 30, 234-244
   Abstract »    Full Text »    PDF »
Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models.
H. Rahmandad and J. Sterman (2008)
Management Science 54, 998-1014
   Abstract »    PDF »
Detecting Robust Patterns in the Spread of Epidemics: A Case Study of Influenza in the United States and France.
P. Crepey and M. Barthelemy (2007)
Am. J. Epidemiol. 166, 1244-1251
   Abstract »    Full Text »    PDF »
Host heterogeneity dominates West Nile virus transmission.
A Marm Kilpatrick, P. Daszak, M. J Jones, P. P Marra, and L. D Kramer (2006)
Proc R Soc B 273, 2327-2333
   Abstract »    Full Text »    PDF »
Multiscale, resurgent epidemics in a hierarchical metapopulation model.
D. J. Watts, R. Muhamad, D. C. Medina, and P. S. Dodds (2005)
PNAS 102, 11157-11162
   Abstract »    Full Text »    PDF »
SARS Revisited: The Challenge of Controlling Emerging Infectious Diseases at the Local, Regional, Federal, and Global Levels.
D. G. Maki (2004)
Mayo Clin. Proc. 79, 1359-1366
   PDF »
Severe acute respiratory syndrome: review and lessons of the 2003 outbreak.
U. D Parashar and L. J Anderson (2004)
Int. J. Epidemiol. 33, 628-634
   Full Text »    PDF »
Using conservation of pattern to estimate spatial parameters from a single snapshot.
M. J. Keeling, S. P. Brooks, and C. A. Gilligan (2004)
PNAS 101, 9155-9160
   Abstract »    Full Text »    PDF »
Modelling potential responses to severe acute respiratory syndrome in Japan: the role of initial attack size, precaution, and quarantine.
H Nishiura, K Patanarapelert, M Sriprom, W Sarakorn, S Sriyab, and I Ming Tang (2004)
J Epidemiol Community Health 58, 186-191
   Abstract »    Full Text »    PDF »
The Severe Acute Respiratory Syndrome.
J. S.M. Peiris, K. Y. Yuen, A. D.M.E. Osterhaus, and K. Stohr (2003)
N. Engl. J. Med. 349, 2431-2441
   Full Text »    PDF »


To Advertise     Find Products

Science. ISSN 0036-8075 (print), 1095-9203 (online)