In my most recent post on February 12th, I described modelling work I had done in support of Prof. Alex de Visscher’s paper, in conjunction with Dr. Tom Sutton, on “Second-wave Dynamics of COVID-19: Impact of Behavioral Changes, Immunity Loss, New Strains, and Vaccination” which has now been published for peer review as a pre-print on Springer’s site at https://www.researchsquare.com/article/rs-195879/v1. I have now added vaccination and multiple variants I had already added to our previous model into the new grouped population model, and this blog post reports on progress with that new model.
Since my most recent posts on December 23rd and January 5th I have adjusted my model algorithms to model more than two variants, so that once better data is available on new variant characteristics, I can respond more quickly. The scenarios I have modelled show that presented with the threat of new variants, early proactive, preventative and decisive action in necessary as soon as a variant is identified. If a new variant is allowed to multiply and grow before appropriate Non Pharmaceutical Interventions are introduced (just as in the first days of the UK pandemic in March 2020, and with our UK March 23rd response) control of the virus is quickly lost.
I present an analysis of the pandemic situation in the UK, with two Coronavirus variants present since December 16th, and sensitivities to different New Year 2021 Non Pharmaceutical Interventions (NPIs), but always with the background of vaccine dispensing, which started in the UK on December 8th.
I cautiously welcomed “the end of the beginning”, and events since then have borne out the need for caution, with the discovery of a mutant variant of the SARS-Cov-2 virus (denoted VUI-202012/01) which seems to have a much greater transmission rate, as much as 70% more than the strain of SARS-Cov-2 we have seen previously in the UK. I have developed a further version of my Coronavirus model which now includes not only intervention capability but also a vaccination module, as reported before, and now the ability to add further virus strains with different transmission characteristics.
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.