vaccines and boosters associated with faster case growth in UK

especially among the oldest and highest risk. this is a worrying trend.

it has long been known that the UK data was showing a strong signal of the vaccinated getting more per capita covid cases. certain internet felines have had quite a lot to say about this in the past.

but what has now become abundantly clear is that not only are cases per 100k higher in the vaccinated in the UK, but that the growth rate of cases in the vaccinated is much higher and worst of all, the variance in the growth rate is most extreme among the oldest cohorts. this same issue holds for boosters. this raises some severe concerns.

let’s look:

i used the data from the UK weekly vaccine reports HERE. as these reports are presented in overlapping 4 week tranches, i used the most recent report (13 jan) and compared it to 16 dec to get adjacent but non-overlapping date periods. this leaves us comparing week 46-49 in 2021 to week 50 2021 through week 01 2022.

this also has the advantage of letting us start to see what a shift to omicron looks like.

vaccination rates in the UK have been extremely high. full vaxx looks like this:

and booster like this:

they report case counts by age cohorted by 10 year tranche. this is extremely useful to keep us away from simpson’s paradoxes based on age, but still carries risk of other forms of cohort bias because there is self selection going into the decision to vaccinate and also adverse selection for those who fail to reach dose 2 or dose 3 due to adverse events from the vaccines. this can play all sorts of games with the data and i see no way to really control for it, so, we will do the best we can with what we have:

i also urge caution with the under 18 grouping as the data there is riddled with testing bias from schools and does have a possible age driven vaxx rate bias as well.

the first obvious point is that cases per 100k went up. a lot.

the second is that cases are far worse in the vaccinated in nearly every age category.

to make this easier to see, i generated a risk ratio by dividing cases per 100k among the vaxxed by cases per 100k of the unvaxxed. thus, any number over 1 shows vaccine group with higher risk. 1.5 = 50% higher cases, etc.

as can be seen, risk ratio was >1 in vaxxed for all groups except for <18 and > 80 for weeks 46-9.

it got markedly worse in every group by weeks 50-01 and exceeded 1 in all age classes.

they huge changes were in 70+. file that away. more soon.

this is a vaccine falling apart and is consistent with omicron being not only a vaccine escape variant, but one that infects the vaccinated preferentially. i’ve written quite a lot on this in the past.

where we start to get real visibility on something a bit novel is here:

i plotted the growth rate in cases per 100k from wks 46-9 to 50-01. (i would ignore the <18’s. i think that’s a testing artifact from holiday break getting them out of relentless school testing programs)

what’s striking here is this: growth in the unvaxxed was quite uniform. it was near identical for 30+.

but look at vaxxed. it was higher in all groups, but look how it starts to dramatically diverge in the older (and most vaccinated) groups. this is EXACTLY what you do not want.

to make this easier to see, i plotted the growth rate ratio of vaxxed/unvaxxed. (i excluded <18 because the ratio was 26.16 which seems both implausible and makes the graph hard to read. it is excluded from all scatters as well.)

now it really pops. those over 70 are seeing something altogether different. the ratio suddenly doubles.

you can see this same distinctive saddle shape here if we plot these points vs vaxx rates.

and booster rates:

these are quite high R2’s for such a noisy system, but in playing with best fits, i found something really striking. look what happens if you use a polynomial fit:

sure, correlation is not causality, and this might look like stats hacking, but this is not the kind of r2 you want to go around dismissing out of hand either. it is a weird shape though and this sort of horseshoe relationship would seem to require explanation if we are to base any kind of claims on it.

you really do not want to trust correlations that lack any a priori reason to suspect causal relationship.

but i think we may have one here:

my working hypothesis (and i want to stress the term “working hypothesis”) is that this is OAS/antigenic imprinting expressing differently in different age groups.

consider:

if you are younger and have a stronger immune system, you may get caught in the narrow imprinting trap of mRNA/adenovirus vaccines and generate S antibodies that do not really work well and fewer N antibodies as well but you still have other robust lines of defense in t-cells, etc. so, while you may underperform your unvaccinated peers vs this OAS variant, you still do OK.

but, if you are older and the rest of your immune system is not robust, you are wide open. you generate S antibodies that mostly or fully miss the mark and your other systems cannot take up the slack. so, bingo, you get covid and that rate explodes as omi gains prominence because omi is the OAS variant that leaky vaccines selected for.

this seems like the most complete and parsimonious explanation i can find so far. it explains a great many things:

• it explains risk ratio for vaxxed exceeding unvaxxed and getting worse as omi spread

• it explains higher growth in cases among the vaxxed as omi spread

• but most of all, it explains the jarring fact that case rates in 70+ rose by about the same as 30-69 in the unvaxxed, but at 2-3X that rate in the vaccinated

• it also explains the saddle shape we’re seeing and why you can get such a good polynomial fit. we’re probably plotting the rate of immune system decline

older people tend to rely more on antibodies and less on strong t cells. this is why flu is so dangerous to old people. they respond to the flus of their youth and new ones evade them. their antibodies miss the target, and the rest of their immune system cannot keep up. this is, in fact, the primary issue around which OAS has been studied.

if this is indeed the case, and please do not skip over that word if, then these vaccine programs are going to be a disaster in terms of covid spread in vulnerable populations. this may well make them worse off EVEN if the vaccines show efficacy.

if you get a 50% reduction in case hospitalization rate but a 300% rise in case rates, you are at 4X prevalence X 50% risk = twice the hospital counts as before.

more on this math HERE.

how this plays out on overall risk rates is still a bit early to call but warrants watching. 95% of vermonters over 65 are double vaxxed. yet that group and the 60-69 year olds as well hit new highs on hospitalization.

so we’re seeing some worrying signs. (many other northeastern states look the same)

this sheds some real doubt on the idea that covid vaccines are serving to help the high risk upon whom they are being relentlessly pushed.

this same looks increasingly so for boosters and approving them based on antibody counts when the antibodies don’t seem to work is beyond pointless, it’s pernicious. and some are starting to cotton on.

the sunk cost fallacy is in full effect and careers and credibility is on the line, but facts are stubborn things, and the fact is that these vaccines are accelerating spread.

they do not protect us as was promised. (and promises were definitely made)

at best, these are a personal choice to mitigate risk.

probably, doing so creates a net risk for others because you are more likely to get covid and spread covid.

the vaccinated are not a dead end for virus, they are crop-dusters for it and spreading it more widely.

omi may be more contagious, but i suspect that A LOT of the surges we’re seeing are so steep because of vaccine driven spread amplification.

the moralizing about “needing to be protected from the unvaxxed” is hallucinatory projection. it’s the opposite that is true. the vaxxed are the primary carrier on a per capita basis.

there has been enough lying and misrepresentation and vilification and othering. that just piles societal poison on top of gross epidemiological malpractice.

and we’ve had quite enough of these “expert” claims…