Previous Article |
Table of Contents
| Next Article 
APPLIED MATHEMATICS
Multiscale, resurgent epidemics in a hierarchical metapopulation model
, 
, 
*Department of Sociology, and Institute for Social and Economic Research and Policy, Columbia University, New York, NY 10027; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501; and ¶College of Physicians and Surgeons, Columbia University, New York, NY 10032
Edited by David O. Siegmund, Stanford University, Stanford, CA, and approved June 14, 2005 (received for review February 12, 2005)
Although population structure has long been recognized as relevant to the spread of infectious disease, traditional mathematical models have understated the role of nonhomogenous mixing in populations with geographical and social structure. Recently, a wide variety of spatial and network models have been proposed that incorporate various aspects of interaction structure among individuals. However, these more complex models necessarily suffer from limited tractability, rendering general conclusions difficult to draw. In seeking a compromise between parsimony and realism, we introduce a class of metapopulation models in which we assume homogeneous mixing holds within local contexts, and that these contexts are embedded in a nested hierarchy of successively larger domains. We model the movement of individuals between contexts via simple transport parameters and allow diseases to spread stochastically. Our model exhibits some important stylized features of real epidemics, including extreme size variation and temporal heterogeneity, that are difficult to characterize with traditional measures. In particular, our results suggest that when epidemics do occur the basic reproduction number R0 may bear little relation to their final size. Informed by our model's behavior, we suggest measures for characterizing epidemic thresholds and discuss implications for the control of epidemics.
math model | population structure
This paper was submitted directly (Track II) to the PNAS office.
Abbreviation: SARS, severe acute respiratory syndrome.
To whom correspondence should be addressed. E-mail: djw24{at}columbia.edu.
© 2005 by The National Academy of Sciences of the USA
CiteULike 
Complore 
Connotea 
Del.icio.us 
Digg What's this?
This article has been cited by other articles in HighWire Press-hosted journals:
|
|
 |
|
  R. C. Larson Simple Models of Influenza Progression Within a Heterogeneous Population Operations Research, May 1, 2007; 55(3): 399 - 412. [Abstract] [PDF]
|
|
