The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
The effects of local spatial structure on epidemiological invasions
Open accessAbstract
Predicting the likely success of invasions is vitally important in ecology and especially epidemiology. Whether an organism can successfully invade and persist in the short-term is highly dependent on the spatial correlations that develop in the early stages of invasion. By modelling the correlations between individuals, we are able to understand the role of spatial heterogeneity in invasion dynamics without the need for large-scale computer simulations. Here, a natural methodology is developed for modelling the behaviour of individuals in a fixed network. This formulation is applied to the spread of a disease through a structured network to determine invasion thresholds and some statistical properties of a single epidemic.
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“When a population is organised in this fashion the capacity of epidemics to spread is reduced (Keeling 1999; Salathe ´ & Jones 2010).”
From Parasite-stress promotes in-group assortative sociality: The cases of strong family ties and heightened religiosity (2012) · cites this paper as Keeling 1999
Citations
Cites
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Self-citation
Research works printed but not linked: 4
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The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471
Strogatz, S. H. (2001) · Nature · doi:10.1038/35065725 · Cited by 8,236
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
A simple model of global cascades on random networks
Watts, D. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082090499 · Cited by 2,673
Metadata
- Authors
- Keeling, M. J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Keeling, M. J.
- ORCID
- Keeling, M. J.
- Venue
- Proceedings of the Royal Society of London. Series B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 1999-04-22
- Volume
- 266
- Issue
- 1421
- Pages
- 859-867
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- PMC
- PMC1689913
- OpenAlex
- W2030540141
- Cited by
- 798
- References
- 28
- Citations by year
- 2026: 19 · 2025: 27 · 2024: 19 · 2023: 30 · 2022: 23 · 2021: 36 · 2020: 33 · 2019: 30 · 2018: 44 · 2017: 46 · 2016: 35 · 2015: 47 · 2014: 37 · 2013: 41 · 2012: 38
- FWCI
- 9.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the Royal Society B Biological Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust
- Topics
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- invasion threshold, spatial structure, spatial heterogeneity, epidemic spread, structured networks, disease transmission, agent-based modeling, spatial correlation, epidemic persistence
- MeSH terms
- Communicable Disease Control, Communicable Diseases, Disease Outbreaks, Ecology, Epidemiology, Humans, Models, Biological, Vaccination
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