England Covid case data are grouped into about twenty 5-year age bands. For anyone who’s been paying attention it’ll come as no surprise that the first age group to have recorded more than 1 million cases (on Xmas Eve) is 10-14 year olds. Merry Christmas, kids. 🧵
The red line on the graph shows how you’d expect the (roughly) 10 million cases so far in England to be distributed based on population statistics (the size of each age group). As you can see, some groups are over-represented in the cases and others are under-represented.
It’s not surprising that adults of working age are over-represented in the cases, whereas older adults (for whom it is easier to limit contacts) are under-represented. But the over-representation is greatest of all for school-age children.
Indeed, just the “overshoot” in cases from what would be expected for 10-19 year olds is considerably greater than the *total* number of cases recorded in all 70+ year olds.
It's reasonable to attribute some of the overshoot in cases among school-age children to higher levels of testing. But one can't get away from the fact that we have failed to provide children with a Covid-safe environment.
One indicator of which aspect of childrens' environment isn't Covid-safe is the way in which we see cases go up and down at regular intervals that just happen to coincide with term dates. School-age children have the highest rate of Covid cases because schools are not Covid-safe.
Time and again the Dept for Education have failed to introduce mitigations (like ventilation and filtration) that would make schools safer. At the same time they've taken away mitigations like masks and bubbles that help to curb transmission.
And we're about to do it all again, but this time, apparently, without tests. This isn't safeguarding children's education -- it's the opposite. It's also endangering the health of children, their teachers and their families.
With new records for hospitalisation of children being broken every day, the government's pretense that schools are Covid-safe is looking more and more reckless.
If we look at the age breakdown we see a similar pattern to other places -- the big increase over the last week (red line vs. blue line) has been among young(ish) adults. I think this is largely due to greater socialising in these age groups.
Here, for example, is the plot for 25-29 year olds since October. The rate has approximately doubled in the last three days.
There's been no rise in the 55+ groups yet. That difference between younger and older adults could - in part - reflect a booster effect. But if so, why don't we see a similar increase in cases among unboosted (often unvaccinated) children? (That's why I think it's socialising).
I think the "Tory ministers vs scientists" framing is a distraction from the real clash, which isn't about science. More generally, people's beliefs about Covid are not just about evidence -- they also reflect people's motivations.
Here's my take 🧵
Only a tiny minority would (if they’re honest) claim that omicron poses no threat. The majority see that it poses a serious threat, though just how big a threat remains to be established. My focus here is on those who say, "Yes, it's cause for concern, but it'll probably be OK".
Ministers have the power to do something about this threat – but don’t want to. Rejecting the science is a more acceptable way of doing nothing than openly admitting you don’t care abt life-threatening disruptions to public services & the prospects of tens of thousands of deaths.
I'm continuing to see people talking about the rate at which sequenced Omicron cases are doubling as if it's a matter of interpretation, or something that different people could reasonably disagree on. It isn’t. It’s like 2+2.
Perhaps it would be useful for me to give a short tutorial on how to calculate doubling rates? It's actually very easy, when you know how. Is anyone interested in that?
OK, looks like there is some interest. So here's a short tutorial for people who never knew how to do this, or who are a bit rusty. I suspect there are a lot of people in this category, so I hope it’ll be useful to them. (I'll deal with qualifiers at the end of this thread).
I shouldn't take it personally, but I am starting to feel rather gaslit by people (including experts) talking about omicron cases doubling every 3 days (or 2.5 days). I've plotted the data against different doubling rates below -- how fast do *you* think cases are doubling?
The graph above said "log scale" (I forgot to change the label), but it is obviously a linear scale (thanks @UncleJo46902375 ). Here's the correctly labelled version.
If you'd like to check my working (please do!), here are the data (two parts):
date newCases total
2021-11-2722
2021-11-2813
2021-11-29811
2021-11-301122
2021-12-011032
2021-12-021042
2021-12-0392134
2021-12-0426160
2021-12-0586246
2021-12-0690336
Having another go at plotting UK omicron cases (previous attempt plotted total over time, which I decided wasn't very useful). Numbers are still sufficiently small to mean that noise in the data makes a big difference. But based on data so far, current doubling rate is 1-2 days.
This estimate could be too fast, if we've got better at detecting omicron over the last few days. Or it could be too conservative if it's getting harder for us to track omicron caes as numbers increase. Mix of imported and home-grown cases also unclear. So some caution required.
Updating this graph for 7th Dec. That line of best fit is still consistent with a doubling rate of 1-2 days (midpoint is 1.6 days). Things should get clearer in a couple more days. But we don't need to wait until then to introduce precautionary measures such as working from home.
I feel a sense of deja vu, looking at Charnwood once again. It's interesting because it's one of those places where schools go back earlier than other parts of England, so it's a kind of canary in the Covid mine. Rates have grown steeply there in the last week in 5-14 year olds.
Although school age children have by far the highest rates in Charnwood, there is one adult age group that is catching up: 40-44 year olds. This is a familiar pattern.
The short thread below was the last time I looked at Charnwood. Showing typical caution in causal attribution I noted that the increase *could* just reflect "back-to-school testing". What happened subsequently suggests it wasn't.