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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).”
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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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