SARS-Cov-2 modelling situation report

As we start September, the UK situation regarding Covid-19 cases and deaths has changed somewhat.

Since the UK Government re-assessed the way deaths data is collected and reported, the reported daily deaths resulting from Covid-19 infections have (thankfully) reduced to a very low level.

Cases, however, have started to rise again, although for a number of reasons the impact on deaths has been less then before. I have integrated the real world reported data with my model data to assess what is happening.

Phenomenology & Coronavirus – modelling and curve-fitting

There is a range of modelling methods, successively requiring more detailed data, from phenomenological (statistical and curve-fitting) methods, to those which seek increasingly to represent the mechanisms (hence “mechanistic” modelling) by which the virus might spread.

We see the difference between curve-fitting and the successively more complex models that build a model from assumed underlying interactions, and causations of infection spread, between parts of the population.

Current Coronavirus model forecast, and next steps

My model is currently fitting deaths data for the UK, on the originally modelled basis of Government published “all settings” deaths. I plan to compare results by looking at the Gompertz function and Sigmoid charts that Michael Levitt uses.

Michael Levitt’s analysis of European Covid-19 data

I promised in an earlier blog post to present Prof. Michael Levitt’s analysis of Covid-19 data published on the EuroMoMo site for European health data over the last few years. His finding is that COVID19 is similar to flu only in total and in age range excess mortality. Flu is a different virus, has a safe vaccine & is much less a threat to heroic medical professionals.