SARS-CoV-2 – Page 2 – A rambling mind

Age and vulnerability related Coronavirus modelling

Chart 209 showing modelled and reported cumulative cases and deaths to 800 days in the groups model

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.

NPIs, variants and vaccine models

Chart 17 model output for deaths, active cases and Seriously Sick to 800 days. 2nd virus variant from September 23rd, day 235. 3rd variant from January 1st 2021, Day 335. 250k vacs/day from January 1st (day 335) and 400k vacs/day from February 1st (day 366) and thereafter. 15% NPI reduction on March 7th, model Day 401.

This paper reports some parametric Coronavirus model runs I have made that compare, in particular, how the UK vaccine programme allows some NPI relaxation compared with a case with no vaccination. The outcome is that the vaccine programme in the UK has the potential to reduce the imposition of NPIs on March 7th by about 15%, without costing lives, this being the next time we in the UK are due for a major NPI review, potentially involving the return of schools at around March 7th.

Concurrent Coronavirus two variant modelling

New 12-compartment model flowchart with additional vaccination compartment V and repeated Incubation, Sick, Seriously Sick, and Better compartments, all infective, in addition to the Uninfected, Vaccinated, Recovered and Deceased compartments

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.

The end of the beginning*

Chart 13 model outputs to 450 days, April 27th, 2021, no vaccinations compared with a 3-phase vaccination programme, as at December 1st

Now that it seems clear that a vaccination programme in the UK might start as early as next week, I have re-run my Covid-19 vaccination model for the UK, updating the November 25th scenarios (which begin on January 1st 2021) to reflect some potential UK outcomes.

Modelling of vaccine strategies

Comparative vaccination charts for the UK to 800 days. Continuation of current NPIs on the left; and an graduated vaccine intervention on the right from January 1st 2021

In my most recent post on November 18th, about updating my Coronavirus model to handle the impact of vaccines, I gave some examples of how case numbers, and more specifically death rates might be improved for the UK through a vaccination programme. Now that there seem to be several vaccines imminent, with efficacies ranging from 70% (Astra-Zeneca/Oxford) through 90% (A-Z/O via a different inoculation regime, and Pfizer), to 95% (Moderna) and several others in the mix, I explore some sensitivities in more detail, and also apply the model to the USA.

Make America well again

Model charts for the USA. Continuation of current policy until a postulated Biden intervention on February 20th 2021, on the left; and an early November 8th intervention on the right

I look at the impact of a postulated change in the timing of further measures to control the Covid-19 epidemic in the USA, against a current background of rapidly increasing daily case numbers and deaths. I also show an updated projection for the UK, both compared with Worldometers forecasts

SARS-Cov-2 modelling situation report

Modelled Cases & Deaths development since Feb 1st - Uninfected, Cumulative Deaths, Uninfected & Seriously Sick

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 than before. I have integrated the real world reported data with my model data to assess what is happening.

Phenomenology & Coronavirus – modelling and curve-fitting

This chart was put up by Michael Levitt on July 8th to illustrate curve fitting methodology using the Gompertz function. See https://twitter.com/MLevitt_NP2013/status/1280926862299082754

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

Reported Deaths vs. Modelled deaths, both cumulative and daily,

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

Deaths graphs from EurMoMo allow the calculation of Excess deaths

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.