Author: Jonas Dehning; Johannes Zierenberg; Frank Paul Spitzner; Michael Wibral; Joao Pinheiro Neto; Michael Wilczek; Viola Priesemann
Title: Inferring COVID-19 spreading rates and potential change points for case number forecasts Document date: 2020_4_6
ID: c8zfz8qt_51
Snippet: Simple model: SIR model with stationary spreading rate We consider a time-discrete version of the standard SIR model. In short, we assume that the disease spreads at rate λ from the infected population stock (I) to the susceptible population stock (S), and that the infected stock recovers (R) at rate µ. This well-established model for disease spreading can be described by the following set of (deterministic) ordinary differential equations (see.....
Document: Simple model: SIR model with stationary spreading rate We consider a time-discrete version of the standard SIR model. In short, we assume that the disease spreads at rate λ from the infected population stock (I) to the susceptible population stock (S), and that the infected stock recovers (R) at rate µ. This well-established model for disease spreading can be described by the following set of (deterministic) ordinary differential equations (see, e.g., Refs [5, 6, 20] ). Within a population of size N ,
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