  We model further development of the COVID-19 epidemic in the UK given the
current data and assuming different scenarios of handling the epidemic. In this
research, we further extend the stochastic model suggested in \cite{us} and
incorporate in it all available to us knowledge about parameters characterising
the behaviour of the virus and the illness induced by it. The models we use are
flexible, comprehensive, fast to run and allow us to incorporate the following:
-time-dependent strategies of handling the epidemic; -spatial heterogeneity of
the population and heterogeneity of development of epidemic in different areas;
-special characteristics of particular groups of people, especially people with
specific medical pre-histories and elderly.
  Standard epidemiological models such as SIR and many of its modifications are
not flexible enough and hence are not precise enough in the studies that
requires the use of the features above. Decision-makers get serious benefits
from using better and more flexible models as they can avoid of nuanced
lock-downs, better plan the exit strategy based on local population data,
different stages of the epidemic in different areas, making specific
recommendations to specific groups of people; all this resulting in a lesser
impact on economy, improved forecasts of regional demand upon NHS allowing for
intelligent resource allocation.
