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Published May 1, 2001 | public
Journal Article Open

Highly optimized tolerance in epidemic models incorporating local optimization and regrowth

Abstract

In the context of a coupled map model of population dynamics, which includes the rapid spread of fatal epidemics, we investigate the consequences of two new features in highly optimized tolerance (HOT), a mechanism which describes how complexity arises in systems which are optimized for robust performance in the presence of a harsh external environment. Specifically, we (1) contrast global and local optimization criteria and (2) investigate the effects of time dependent regrowth. We find that both local and global optimization lead to HOT states, which may differ in their specific layouts, but share many qualitative features. Time dependent regrowth leads to HOT states which deviate from the optimal configurations in the corresponding static models in order to protect the system from slow (or impossible) regrowth which follows the largest losses and extinctions. While the associated map can exhibit complex, chaotic solutions, HOT states are confined to relatively simple dynamical regimes.

Additional Information

©2001 The American Physical Society Received 29 August 2000; published 25 April 2001 We wish to thank T. Zhou for numerous useful discussions. This work was supported by the David and Lucile Packard Foundation, and NSF Grant No. DMR-9813752, and EPRI/DoD through the Program on Interactive Complex Networks.

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