Journal
ELIFE
Volume 10, Issue -, Pages -Publisher
eLIFE SCIENCES PUBL LTD
DOI: 10.7554/eLife.68341
Keywords
epidemic dynamics; COVID-19; heterogeneity; endemic state; herd immunity; Viruses
Categories
Funding
- University of Illinois System Office
- Office of the Vice-Chancellor for Research and Innovation
- Grainger College of Engineering
- Department of Physics at the University of Illinois at Urbana-Champaign
- U.S. DOE Office of Science Facility, at Brookhaven National Laboratory [DE-SC0012704]
- NSF [2107344]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [2107344] Funding Source: National Science Foundation
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This article discusses the importance of dynamic heterogeneity in the spread of epidemics, and demonstrates the emergence of a new long timescale by integrating the stochastic dynamics of social activity into traditional epidemiological models.
It is well recognized that population heterogeneity plays an important role in the spread of epidemics. While individual variations in social activity are often assumed to be persistent, that is, constant in time, here we discuss the consequences of dynamic heterogeneity. By integrating the stochastic dynamics of social activity into traditional epidemiological models, we demonstrate the emergence of a new long timescale governing the epidemic, in broad agreement with empirical data. Our stochastic social activity model captures multiple features of real-life epidemics such as COVID-19, including prolonged plateaus and multiple waves, which are transiently suppressed due to the dynamic nature of social activity. The existence of a long timescale due to the interplay between epidemic and social dynamics provides a unifying picture of how a fast-paced epidemic typically will transition to an endemic state.
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