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

Anatoly Zhigljavsky; Jack Noonan

Considerably important, in view of the discussions of the next section, is Figure 6 . In this figure, for the initial data of Figure 1 , we strongly separate group G at the time when 10% of the population is infected. We make no call to the general public for social distancing. In this scenario, the intervention does not considerably change the proportion of infected in the total population but it significantly 'flattens the curve' for the group G: compare the purple and green lines. The maximum of I G (t)/n is 0.086 which is 2.5 times lower than 0.216, the maximum of I(t)/N . Note also the fact that the curve I G (t)/n is rather flat for long time, during the main stage of development of the epidemic. Just after the peak of The scenario which led to Figure 6 is important and hence it has been re-run for a few variations of the model. Figure 7 shows the results of the simulations where we have removed the incubation period. The maximum of I G (t)/n is now 0.075 which is more than twice lower than 1.63, the maximum of I(t)/N . Note that in the scenario with no incubation period the whole epidemic is milder as the virus lives longer.