Author: Emma Southall; Michael J. Tildesley; Louise Dyson
Title: Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data Document date: 2020_4_2
ID: dp4qv77q_38
Snippet: As previously, we can derive statistics of ω from the solution of this SDE. In 260 particular, since the SDE is linear in ω then we can describe ω as a Gaussian variable 261 with mean zero and variance given by the solution to the following ODE, was reduced from β 0 = 1 to 0, slowly forcing R 0 = 5 to 0. In Model 2, the rate of 269 vaccination was increased from p 0 = 0 to 1, slowly forcing R 0 = 5 to 0. In Model 3, the 270 transmission param.....
Document: As previously, we can derive statistics of ω from the solution of this SDE. In 260 particular, since the SDE is linear in ω then we can describe ω as a Gaussian variable 261 with mean zero and variance given by the solution to the following ODE, was reduced from β 0 = 1 to 0, slowly forcing R 0 = 5 to 0. In Model 2, the rate of 269 vaccination was increased from p 0 = 0 to 1, slowly forcing R 0 = 5 to 0. In Model 3, the 270 transmission parameter β was increased from β 0 = 0.12 to 0.24 so that the basic 271 reproduction number increases from R 0 ≈ 0.6 to ≈ 1.2.
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