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Colin Angus Profile picture
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5 Feb, 4 tweets, 2 min read
New data today from @NISRA shows all-cause deaths have fallen, but remain very slightly above the peak in 2010-19 for this time of year, and a fair way above the average.
The number of deaths from COVID-19 has fallen, but is still higher than at any point during 2020.
In the context of the rest of the UK though, Northern Ireland isn't doing too badly...
R code for these plots is here:
github.com/VictimOfMaths/…

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More from @VictimOfMaths

Colin Angus Profile picture
5 Feb
Forgot to update these plots when the latest ONS mortality data came out the other day.

There were ~ 250 COVID-19 deaths a day in English care homes in the week to 29th January. This is pretty grim, but the numbers have at least stopped rising.
Care home residents are still mostly dying in care homes, rather than in hospital.
There's a lot of variation in these figures across the country, but in Essex, Portsmouth, West Sussex and Wirral, over two thirds of care home deaths in the last week were from COVID.
Read 4 tweets
Colin Angus Profile picture
5 Feb
The latest NHS bed occupancy data for England shows that COVID-19 bed occupancy is falling, although there are still a *lot* of COVID patients in hospitals.
The fall is evident across all regions, although it's faster in those areas with the biggest peaks and rather slower in the North of England.
The picture is still pretty consistent when you drill down to NHS trust level.
Read 6 tweets
Colin Angus Profile picture
5 Feb
In light of the ONS data on alcohol-specific deaths for 2020, the other day I had a quick look at some similar figures for Scotland, and concluded that it didn't look as though Scotland had seen a rise in alcohol-related deaths in Q2 & Q3 in the same way that England & wales did.
Well, after I posted this, the ever helpful @juliemramsay from @NatRecordsScot pointed out that Scottish mortality data works differently from the English & Welsh figures. In E&W the ONS report the number of deaths *registered* in each quarter. Registration can be delayed...
...for some time (almost 1% take over a year) ons.gov.uk/peoplepopulati…) for various reasons, including where there is an inquest. So the Q2 2020 figures for E&W will be missing some deaths that occurred in that quarter, but will include some deaths from previous quarters.
Read 9 tweets
Colin Angus Profile picture
5 Feb
One last map before I go out for a walk.

This is a comparison of COVID-19 deaths in March-July and August-December 2020 at MSOA level.

More red, because there were more deaths in Mar-Jul, but not much dark red, or clear pockets of red, which would indicate herd immunity.
Even in London, which you would probably mark out as the most likely candidate, there are not many areas which were hit hard in the Spring, but not in the Autumn/Winter.
Again, this isn't a rigorous statistical analysis, and it doesn't include deaths in January (because the figures aren't available at MSOA level yet), but I think it's pretty interesting all the same.
Read 4 tweets
Colin Angus Profile picture
5 Feb
The more I think about this map, the more interesting I think it is.

So I thought I would do a little thread on it...
I'm interested in looking at geographical variation in COVID-19 deaths and trying to understand what patterns we might be able to see in them.

We can start by mapping overall COVID-19 death rates.

This fairly clearly shows higher rates in the North of England.
But hang on, London has seen a bigger increase in mortality during the pandemic than any other region in the UK, so why doesn't it show up in that map?
Read 17 tweets
Colin Angus Profile picture
4 Feb
This is a good explanation of the flimsiness of the conclusions of that study on international flights driving COVID deaths, but I think I have a more fundamental objection.

I think this kind of correlation analysis is close to useless for COVID, even if well conducted...
Countries' have been affected differently and at different times by COVID and to different extents for all sorts of different reasons, some of which are hard if not impossible to control for (including dumb luck).
For example, try controlling for the high prevalence of multigenerational households in deprived areas with high BAME populations who work in largely customer-facing jobs in parts of the country which happen to have had serious outbreaks in your national-level model.
Read 5 tweets

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