Many countries, including the UK, are experiencing a resurgence of Covid-19 cases recently, although, thankfully, with a much lower death rate. I have run several iterations of my model in the meantime, introducing several lockdown adjustment points, since my last blog post, as the situation has developed. The key feature is the sharp rise cases, and to a lesser extent, deaths, around the time of the lockdown easing in the summer. I have applied a 10% increase in current intervention effectiveness on October 19th (although there are some differences in the half-term dates across the UK), followed by a partial relaxation after 2 weeks, -5%, reducing the circuit-breaker measure by half – so not back to the level we are at currently. The effect of that change is shown in the final chart in the blog post.
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.
I have now reforecast my model with a slightly lower intervention effectiveness (83% instead of 83.5%), and, while still slightly below reported numbers, it is nearly on track
A couple of interesting articles on the Coronavirus pandemic came to my attention this week; a recent on in National Geographic on June 26, highlighting a starting comparison of the USA’s cases history and recent spike in case numbers with European data.
This article referred to an older National Geographic piece, from March, by Cathleen O’Grady, referencing a specific chart from Katy Armstrong of the Imperial College Covid-19 Response team.
I noticed, and was interested in that reference following a recent interaction I had with that team, regarding their influential March 16th paper.
Meanwhile, my own forecasting model is still tracking published data quite well, although over the last couple of weeks I don’t think the published rate of deaths is falling as quickly as before.
A brief update post to confirm that my Coronavirus model is still tracking the daily reported UK data well, and doesn’t currently need any parameter changes. I go on to highlight some important aspects of emphasis in the Daily Downing St. Update on June 10th, as well as the response to Prof. Neil Ferguson’s comments to the Parliamentary Select Committee for Science and Technology about the impact of an earlier lockdown date, a scenario I have modelled and discussed before.
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.
Owing to the serendipity of a contemporary and friend of mine at King’s College London, Andrew Ennis, wishing one of HIS contemporaries in Physics, Michael Levitt, a happy birthday on 9th May, and mentioning me and my Coronavirus modelling attempts in passing, I am benefiting from another perspective on Coronavirus from Michael Levitt.
This is a brief update to my model predictions in the light of a week’s published data regarding Covid-19 cases and deaths in all settings – hospitals, care homes and the community.
The UK Government yesterday changed the reporting basis for Cononavirus numbers, retrospectively (since 6th March 2020) adding in deaths in the Care Home and and other settings, and also modifying the “Active Cases” to match, and so I have adjusted my model to match.
Even having explored Prof. Alex Visscher’s published MatLab code for a week or two now, with UK data, even I am surprised at how well the model is matching up to published UK data so far (on April 18th 2020). I have reported my previous work a couple of times, once relating to the modellingContinue reading “UK Coronavirus Modelling – match to data”