期刊
EPIDEMICS
卷 10, 期 -, 页码 54-57出版社
ELSEVIER
DOI: 10.1016/j.epidem.2014.05.002
关键词
Stochastic epidemics; Global transmission; Extinction; Genetic evolution; Endemicity
资金
- Swedish Research Council
- Engineering and Physical Sciences Research Council
- Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directory, Department of Homeland Security
- Fogarty International Center, National Institutes of Health
- National Institutes of Health [R01-AI091980]
- National Science Foundation [RTG/DMS-1246991]
- Wellcome Trust from Fogarty International Centre [093488/Z/10/Z, R01 TW008246-01]
- Medical Research Council (UK) [MR/J008761/1]
- RAPIDD program from Fogarty International Centre with the Science & Technology Directorate, Department of Homeland Security
- Vetenskapsradet (Swedish Research Council) [20105873]
- Wellcome Trust [093488/Z/10/Z] Funding Source: Wellcome Trust
- EPSRC [EP/J002437/2, EP/J002437/1] Funding Source: UKRI
- MRC [MR/J008761/1, MR/K010174/1] Funding Source: UKRI
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1246991] Funding Source: National Science Foundation
- Engineering and Physical Sciences Research Council [EP/J002437/2, EP/J002437/1] Funding Source: researchfish
- Medical Research Council [MR/K010174/1, MR/K010174/1B, MR/J008761/1] Funding Source: researchfish
- National Institute for Health Research [HPRU-2012-10080] Funding Source: researchfish
The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way? (C) 2014 The Authors. Published by Elsevier B.V.
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