A simple model for complex dynamical transitions in epidemics.
By D. Earn, P. Rohani, Benjamin M. Bolker, Bryan T. Grenfell. Science, 2000
731 citations recorded by the source corpus.
Subfields: Genetics, Modeling and Simulation, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/05ed376f273ecd7654ebbeaeedb08722163c5eb6
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Citations in the corpus
- Ecological forecasts: an emerging imperative. (2001, background): “Finkestadt and Grenfell 2000, Earn et al. 2000 ).”
- The Mathematics of Infectious Diseases (2000, background): “[71] proposed a simple, time-forced SEIR model with slow variation in the average rate of recruitment of new susceptibles.”
- Threshold Dynamics for Compartmental Epidemic Models in Periodic Environments (2008, background): “Vaccination program is also a source of periodicity [ 10 ].”
- Statistical physics of vaccination (2016, background): “For example metapopulation models can explain the observed de-correlation observed in the time-series of UK major cities after the introduction of measles vaccination [92, 141].”
- Seasonality and the dynamics of infectious diseases. (2006, background): “…childhood infections, measles and whooping cough, are modelled with essentially the same equations, and yet they show different dynamics in the presence of noise, with major impacts on how each pathogen has responded to vaccination in time and space (Rohani et al. 1999; Earn et al. 2000).”
- Invading with biological weapons: the importance of disease‐mediated invasions (2012, background): “Functional Ecology © 2012 British Ecological Society, Functional Ecology, 26, 1249–1261 important drivers of the population and epidemiological dynamics in single host–parasite systems (Altizer et al. 2006; Earn et al. 2000; Childs & Boots 2010; Keeling & Rohani 2008; Tompkins et al. 2011).”
- External forcing of ecological and epidemiological systems: a resonance approach (2004, methodology): “…3.3 we method by providing different diseases models other than the same resonance ) is plotted against one or example, took the bifurcation parameter to be the forcing amplitude ( δ ) and Earn et al. [9] the average contact and Piccardi [10], in their two-dimensional study, varied both and 0 .”
- Networks and epidemic models (2005, background): “I N Z b I N : ð1:3Þ This leads to a nonlinear term (bSI/N ) representing the transmission of infection, generating a variety of rich dynamical behaviours (Schwartz 1985; Olsen et al. 1986; Rand & Wilson 1991; Anderson & May 1992; Earn et al. 2000; Keeling et al. 2001).”
- Plug-and-play inference for disease dynamics: measles in large and small populations as a case study (2009, background): “This may be partly because of the additional difficulties of inference for such systems and partly because models based on homogeneous mixing do an impressive job of describing key dynamic features (Earn et al. 2000; Grenfell et al. 2002).”
- Improved inference of time-varying reproduction numbers during infectious disease outbreaks (2019, background): “For example, transmission of vector-borne pathogens varies due to factors including seasonal temperature variation (Lord, 2004; Obolski et al., 2019) , and outbreaks of childhood diseases such as measles are affected by school term dates (Earn et al., 2000) .”
- Threshold dynamics in a time-delayed periodic sis epidemic model (2009, background): “Periodic vaccination strategies are often used to control diseases [6].”