Generic probabilistic modelling and non-homogeneity issues for the UK epidemic of COVID-19

Anatoly Zhigljavsky; Jack Noonan

We have run a large number of scenarios coded using a combination of R and Julia [15] ; the code is provided in Appendix. In Figures 6-11 , we illustrate a few of these scenarios. In all these scenarios, we have chosen R 0 = 2.5 and α = 0.2. The results are robust towards values of these parameters (subject to faster or slower rate of the epidemic in dependence on R 0 ). In Section 5 we use α = 0.132 to illustrate some specific results; α = 0.2 can be considered either as a generic value or, in the contents of Section 5, as the relative size of the group of vulnerable people which is larger than the group of people aged 70+.