Delta variant impact on June 21st easing – delay or reduce?

Having explored what pandemic advisers might be seeing and highlighting to decision-makers in Government, I run scenarios with different settings for the planned June 21st relaxation of lockdown, the last in the series of relaxations over the first half of 2021, following the January 3rd lockdown. These model scenarios show examples of what the relative consequences of the June 21st relaxation as planned, versus four other options:- cancellation of the June 21st step altogether, two different delays, of 28 and 56 days, and lastly a 50% reduction in the scope of the June 21st relaxation.

Exploring new variants, vaccines and NPIs

There has been increasing concern recently about SARS-Cov-2 variants that might escape vaccines to some extent, as well as having different transmission rates (as the Kent variant does), and causing different severity of illness with higher mortality. I have added a vaccination efficacy modifier, var_eff, by variant, as a multiplier to the standard vaccination efficacy, vac_eff, to help model such potential variants that have a partial or total capability to escape vaccines, and this post shows examples of how that works, using a third variant introduced to the model on January 1st 2021. In addition, I have completed adding fSS (the fraction of people becoming seriously sick from each variant) and fmort (fatality of the variant) by Covid variant.

Introduce Yourself (Example Post)

This is an example post, originally published as part of Blogging University. Enroll in one of our ten programs, and start your blog right. You’re going to publish a post today. Don’t worry about how your blog looks. Don’t worry if you haven’t given it a name yet, or you’re feeling overwhelmed. Just click theContinue reading “Introduce Yourself (Example Post)”

Introduce Yourself (Example Post)

This is an example post, originally published as part of Blogging University. Enroll in one of our ten programs, and start your blog right. You’re going to publish a post today. Don’t worry about how your blog looks. Don’t worry if you haven’t given it a name yet, or you’re feeling overwhelmed. Just click theContinue reading “Introduce Yourself (Example Post)”

Introduce Yourself (Example Post)

This is an example post, originally published as part of Blogging University. Enroll in one of our ten programs, and start your blog right. You’re going to publish a post today. Don’t worry about how your blog looks. Don’t worry if you haven’t given it a name yet, or you’re feeling overwhelmed. Just click theContinue reading “Introduce Yourself (Example Post)”

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.

Coronavirus modelling work reported by the BBC

This article by the BBC’s Rachel Schraer explores the modelling for the progression of the Coronavirus Covid-19. In the article we see some graphs showing epidemic growth rates, and in particular this one showing infection rate dependency on how many one individual infects in a given period. https://www.bbc.co.uk/news/health-52056111 This chart led me to look intoContinue reading “Coronavirus modelling work reported by the BBC”

Coronavirus – possible trajectories

I guess the UK line in the Johns Hopkins chart, reported earlier, might well flatten at some point soon, as some other countries’ lines have. But if we continue at 3 days for doubling of cases, according to my spreadsheet experiment, we will see over 1m cases after 40 days. See:https://docs.google.com/spreadsheets/d/1kE_pNRlVaFBeY5DxknPgeK5wmXNeBuyslizpvJmoQDY/edit?usp=sharingand the example outputs attachedContinue reading “Coronavirus – possible trajectories”

Coronavirus – forecasting numbers

A few people might have see the Johns Hopkins University Medical School chart on Covid-19 infection rates in different countries. This particular chart (they have produced many different outputs, some of them interactive world incidence models – see https://coronavirus.jhu.edu/map.html for more) usefully compares some various national growth rates with straight lines representing different periods overContinue reading “Coronavirus – forecasting numbers”

Coronavirus modelling – GLEAMviz15

Here’s the kind of stuff that the Covid-19 modellers will be doing. https://www.nature.com/articles/srep46076.pdf I have downloaded GleamViz, http://www.gleamviz.org/simulator/client/, and it is quite complicated to set up (I used to have a little Windows app called Wildfire that just needed a few numbers to get a pictorial progression of life/recovery/death from the disease, depending on infectivity,Continue reading “Coronavirus modelling – GLEAMviz15”