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

Anatoly Zhigljavsky; Jack Noonan

From the value I(t), we can estimate the distribution of the number of deaths, at time t, as follows: first, since on average an infected person is considered as infected for 21 days, we compute I(t)/21. At each particular day, any person can die with the probability which is typical for the chosen population or sub-population. If we consider the whole population, then we apply the mortality rate for the population. However, if I(t) refers to a particular group only, then we should apply the corresponding coefficient for the group. In any case, the distribution for the number of deaths at time t can be roughly considered as binomial with parameters I(t) and the probability of 'success' rσ, where r is the mortality rate. Different authors disagree on the values of mortality r for the COVID-19; see, for example, [10]. UK's experts Figure 1 : An uninterrupted run of a COVID-19 epidemic in homogeneous conditions believe r 0.009 [3] , WHO sets the world-wide mortality rate at 0.034, the authors of [11] believe r is very small and could be close to 0.001, an Israeli expert D. Yamin sets r = 0.003, see [12] .