Name
Abstract | ||
|---|---|---|
Over the last 10 years, the field of mathematical epidemiology has piqued the interest of complex-systems researchers, resulting in a tremendous volume of work exploring the effects of population structure on disease propagation. Much of this research focuses on computing epidemic threshold tests, and in practice several different tests are often used interchangeably. We summarize recent literature that attempts to clarify the relationships among different threshold criteria, systematize the incorporation of population structure into a general infection framework, and discuss conditions under which interaction topology and infection characteristics can be decoupled in the computation of the basic reproductive ratio, R0. We then present methods for making predictions about disease spread when only partial information about the routes of transmission is available. These methods include approximation techniques and bounds obtained via spectral graph theory, and are applied to several data sets. © 2008 Wiley Periodicals, Inc. Complexity, 2009 This article was submitted as an invited paper resulting from the “Understanding Complex Systems” conference held at the University of Illinois at Urbana-Champaign, May 2007. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1002/cplx.v14:4 | Complexity |
Keywords | Field | DocType |
basic reproductive ratio,network,spectral graph theory,asymptotic stability,spectral radius,complex system | Complex system,Spectral graph theory,Computer science,Artificial intelligence,Basic reproduction number,Population structure,Mathematical modelling of infectious disease,Machine learning | Journal |
Volume | Issue | ISSN |
14 | 4 | 1076-2787 |
Citations | PageRank | References |
2 | 0.43 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura A. Zager | 1 | 70 | 2.69 |
| George C. Verghese | 2 | 208 | 26.26 |