In this article, I present a few variations of the current model to illustrate some outcomes depending on different assumptions about the current dominant variant, Omicron BA.2; they are fairly consistent in their forecasts over the 1400 day period of the model, from the outset in February 2020 to December 2023, and show that as NPIs are removed, vaccination is what keeps us safe.
I haven’t needed to make significant updates to my Coronavirus model for a while, because it has been working well.
The original Omicron variant morphed into the new BA.2 variant, and although it seems no more dangerous than its predecessor, it is thought to be between 33%-50% more transmissible. I have assumed the lower value of 33% more transmissive for this post.
I have added Omicron BA.2 as fifth variant v5 to my model, with 8 times the transmissibility of Delta, compared with the original Omicron variant v4 in the model, at 6 times the Delta transmission rate.
While it is still very early days, both in the New Year of 2022 and also for the Omicron variant, this post adds to my recent 19th December update with a summary of further runs of my model for higher transmissions settings. Last time I ran options up to three times the transmission rate of the Delta variant, and I have now looked at transmission up to five times the Delta rate.
I have run updates to my model for lower and medium vaccine efficacy to Omicron, and lower, medium and higher virulence and mortality, and continue to compare with reported data. While evidence is still in short supply, nothing has firmly contradicted the impression that Omicron is highly transmissive, as well as being possibly less virulent.
The pandemic situation in continental Europe has been worsening rapidly, and I felt that it I should update some country comparisons in a dedicated post.It confirms that the sourcing of data for a Coronavirus model of any given country is a very specific task nowadays, given the considerable differences in the underlying demographics, cultures, Government actions (NPIs) and public responses in the various countries.
This blog post isn’t looking at the modelling per se, but concentrates on the very different outcomes we are seeing across Europe, and looking at some of the reasons why.
Vaccination has somewhat stabilised the SARS-Cov-2 pandemic in the UK. I summarise the capabilities that I have found necessary and useful in modelling the behaviour of the pandemic; successive variants, different population age-groups, the effect of Government NPIs, and vaccinations.
Having just had my 3rd Covid jab, the “booster” jab, it provoked a few thoughts about that, my Coronavirus model, and the wider scene. I had incorporated multiple jabs into my UK model some time ago, and multiple phases for inoculation volumes to cope with the first and second jabs. I am taking this opportunity to report briefly on model outcomes for waning immunity in the context of booster jabs.
The UK parliamentary Health and Social Care, and Science and Technology Committees have just jointly published their substantial report criticising the many errors made by UK Government in its handling of the Covid crisis. It praised, justifiably, the excellent strategy (early risk investment) and deployment of vaccines. But its own timing is as questionable as that of any it seeks to criticise.
In my April 8th 2020 post about the R0 reproduction number and the use of SIR models to model the pandemic, I developed a chart which predicted the proportion of the population uninfected by the end of an unconstrained pandemic.
That chart allowed for an R0 up to 3, but the Delta variant that arrived in the UK a year later, in April 2021, has an R0 far higher than the original, possible 2.5 times as high, as much as R0=7, perhaps.
I have added to the scope of that previous post to develop a chart allowing R0 up to 7..
There is no excerpt because this is a protected post.