When individual behaviour matters: homogeneous and network models in epidemiology
Applied Mathematics (United States) · The University of Texas at Austin · +5 more institutions
Abstract
Heterogeneity in host contact patterns profoundly shapes population-level disease dynamics. Many epidemiological models make simplifying assumptions about the patterns of disease-causing interactions among hosts. In particular, homogeneous-mixing models assume that all hosts have identical rates of disease-causing contacts. In recent years, several network-based approaches have been developed to explicitly model heterogeneity in host contact patterns. Here, we use a network perspective to quantify the extent to which real populations depart from the homogeneous-mixing assumption, in terms of both the underlying network structure and the resulting epidemiological dynamics. We find that human contact patterns…
Citation impact
- FWCI
- 14.24
- Percentile
- 100%
- References
- 76
Authors
3- SBShweta BansalCorresponding
Applied Mathematics (United States), The University of Texas at Austin
- BTBryan T. Grenfell
National Institutes of Health, Pennsylvania State University, Center for Disease Dynamics, Economics & Policy, Fogarty International Center
- LALauren Ancel Meyers
Santa Fe Institute, The University of Texas at Austin
Topics & keywords
- Homogeneous
- Mixing (physics)
- Computer science
- Heterogeneous network
- Epidemic model
- Host (biology)
- Population
- Network model
- Good health and well-being