The abundance threshold for plague as a critical percolation phenomenon
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DOI: 10.1038/nature07053
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Cited by:
- Alexander Veremyev & Oleg A. Prokopyev & Sergiy Butenko & Eduardo L. Pasiliao, 2016. "Exact MIP-based approaches for finding maximum quasi-cliques and dense subgraphs," Computational Optimization and Applications, Springer, vol. 64(1), pages 177-214, May.
- Laperrière, Vincent & Brugger, Katharina & Rubel, Franz, 2016. "Cross-scale modeling of a vector-borne disease, from the individual to the metapopulation: The seasonal dynamics of sylvatic plague in Kazakhstan," Ecological Modelling, Elsevier, vol. 342(C), pages 34-48.
- Patrick W. Schmidt, 2020. "Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany," Papers 2011.04002, arXiv.org.
- Sean M Moore & Andrew Monaghan & Kevin S Griffith & Titus Apangu & Paul S Mead & Rebecca J Eisen, 2012. "Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-11, September.
- Paolo Zeppini & Koen Frenken & Luis R. Izquierdo, 2013. "Innovation diffusion in networks: the microeconomics of percolation," Working Papers 13-02, Eindhoven Center for Innovation Studies, revised Feb 2013.
- Huang, Xudong & Yang, Dong & Kang, Zhiqin, 2021. "Impact of pore distribution characteristics on percolation threshold based on site percolation theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
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