The Hot Spot

The UK's tedious Infinite Covid Apocalypse, reexamined.

Endless infections in the UK, and the possibility of “immune deficiency critical mass.”

Well, looks like it’s almost time to buy presents for the UK “summer wave”s first birthday.

Long-time Unglossed readers may remember that I “checked out” of the UK in October. The persistent high case rates, and the UKHSA’s weekly “negative efficacy” infection updates, were astonishing and startling - but they also weren’t supported by the experience of other heavily vaccinated regions. “Forever Spike,” as I had termed the phenomenon the month before, had by then already proved to be strictly a feature of the Isles. It didn’t seem appropriate to keep drawing conclusions regarding the Covid vaccines based on a geographic outlier that was in disagreement with Israel, New England, and the other high-uptake nations of Europe.

Now, at last, the rest of Western Europe appears to be picking up on the trend, though this may owe more to the accident of a more rapid exposure to BA.2.

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That aside, perhaps it is appropriate to again try to tease out just what the UK’s unholy 10 Month Wave means.

Diversion: OAS in Flames

Just before “checking out” in October, I made a bold call regarding the throwaway comment on post-breakthrough-infection Nucleocapsid (N) antibodies that had been dropped into the UKHSA’s blood donor graphs.

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Of the report’s comment that “recent observations” showed that the Covid vaccinated didn’t make N antibodies after breakthrough infection, I argued that this is likely not relevant to the observed low rate of N antibodies in blood donors:

The sentence concerns charts on prevalence for antibodies to the spike protein (the target of the pseudo-vaccines) and the nucleocapsid protein (“N,” which would only be derived from natural infection) in highly Covid-vaccinated blood donations. Despite the tsunami of cases in the UK’s “summerautumn wave,” levels of “N” protein in sampled blood donations don’t seem to be coming up very much. Is this because the infected (especially elderly infected), among other possible changes in behavior, are less likely to continue donating blood - or has something “broken” in the memory immune response of the Covid-vaccinated?

source: UK Health Security Agency (pdf) (annotated)

The sentence (emphasis added):

Seropositivity estimates for N antibody will underestimate the proportion of the population previously infected due to (i) blood donors are potentially less likely to be exposed to natural infection than age matched individuals in the general population (ii) waning of the N antibody response over time and (iii) recent observations from UK Health Security Agency (UKHSA) surveillance data that N antibody levels appear to be lower in individuals who acquire infection following 2 doses of vaccination.

“Recent observations” does not mean observations of recent outcomes. Plenty of “recently” published studies have been time capsules of post-Covid-vaccination infections from the spring. […]

Thus, in advance of knowing the actual source of the Security Agency “observations,” there is no reason to use them as a basis for concluding anything. Early “breakthrough” infections are less symptomatic, and more prone to false positives; post 4-month “breakthrough” infections are more likely to be the real deal.

The other portions of the statement, meanwhile, strongly argue against extrapolating from the blood donor seroprevalence charts to the rates that would be found in the general population. The sample, again, likely selects both for high rates of Covid-vaccinated and low rates of post-infection donors (with the latter bias increasing with age).

In other words, the flat-lined rate of N antibodies among donors wasn’t showing something “wrong” with the immune response of the Covid-vaccinated after infection - because it wasn’t showing blood from infected donors at all.

How did I arrive at this off-the-cuff conclusion? I applied a simple rubric:

• If a sample contains an obvious selection bias (as any survey/donor based sample does by default), assume that the selection bias is driving the results.

• If the authors presenting the results offer a non-selection-bias account for their results, ignore them. They are wrong.

• If other bloggers are uncritically reporting the authors’ wrong account as gospel, stake a claim on the opposite interpretation so that you can be proven right 6 months later.

This post was the first of my “OAS Is Not Real” series.

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And while the post goes on to discuss why failure to generate N antibodies wouldn’t really be “OAS” anyway, it’s still appropriate to start our reexamination of the UK situation here, especially since the spectre of the UKHSA’s comment has been raised again, in a recent and otherwise well-argued post by Igor Chudov.

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Is something wrong with the N antibody response after breakthrough infection, and does this have something to do with the UK’s high infection rates?

To really know the answer to this, we would need to see:

• An actual study measuring N seropositivity after breakthrough infections after the first few months after injection (most post-injection infections occur after infection efficacy drops,

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  and so the experience of the early-breakthrough-infected is not very interesting). Edit, May 2: It turns out this wish was granted back in October, at the same time the UKHSA comment was added! N-antibodies are nearly 100% for post-Delta infections among double or single-dosed Covid vaccinated in a Public Health England study. See footnotes.
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• Immune performance (reinfection or not) of the breakthrough-infected stratified by N seropositivity. If the Covid-vaccinated in the UK are not developing N antibodies after infection, it doesn’t mean anything unless they are also getting infected again.

In the meanwhile, all we have is the UKHSA’s throwaway comment. It hasn’t been substantiated by a link or citation of an actual study. It hasn’t removed the language (“shorter” infections) that imply that the “observations” were from early breakthrough infections (only early breakthrough infections are measurably shorter), though on the other hand the reference to “recent” observations was removed. It just keeps being pasted into new iterations of the report, over and over. Despite the fact that blood donor N antibodies have risen dramatically since October.

source: UK Health Security Agency (pdf) (annotated)

The overall rate obscures the even more dramatic rise in the 59 and younger donors, in whom an additional ~20% are now positive for N antibodies vs week 39:

source: UK Health Security Agency (pdf)

In so far as I placed a “bet,” back on week 39, that the previous results were an effect of timing or bias, I seem to have made the stronger bet - the results have changed (from little increase to high increase), suggesting the results were and are an accident of timing or bias. Alternately, human biology just changed on a dime and made me look correct by accident. (Sure.)

And so, why aren’t the 60-84 groups rising as much? Likely for the same reasons that they were lower to begin with:

• Infected elderly are less likely to donate blood, because infections are more likely to be severe or fatal.

• Infected elderly with milder illness may be less likely to develop antibodies against the N protein, due to immunosenescence - the lower immune response to novel antigens that occurs with aging. Importantly, the term for immunosenescence is not “OAS.” The term is “immunosenescence.”

• Edit, May 3: Or, a faster rate of N-antibody fadeout for the Covid-vaccinated, rather than a failure to generate N antibodies in the first place, as suggested by the analysis of Whitaker, et al. in footnote 6, which means that a “negative moderate breakthrough infection donor” bias only needs to be temporary to drive the UKHSA results. For various reasons (higher N-antibodies would likely become an effective marker for “temporary unlikeliness” in this model) I doubt this.

And what of the young - is it not still true that measured donor N seropositivity is lower than the real infection rate? Yes - but infected, Covid-vaccinated young are still also less likely to donate blood than the not-yet-infected, just not to the extent of older groups. All “Omicron” appears to have done is partially lower this selection bias among the young, either by removing the stigma around breakthrough infection, or by increasing the rate of asymptomatic infection (I would say likely the former).

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The Data Isn’t There

The context of Chudov’s re-invocation of the UKHSA comment is the question of whether the Covid vaccinated are experiencing rapid, repeat reinfections - this, again, is the more important question anyway.

Notably, the current case pattern almost, sort-of-kind-of fits the bill for a rapid-reinfection or chronic infection “afterimage” (wherein December positive-testers simply re-qualify as new “infections” en masse in March, 90 days after their previous positive, driving the appearance of a second Omicron wave

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).

But besides not quite lining up to 90 days, there are other problems with the theory that rapid reinfections are driving the second wave. First is that the UKHSA’s other publication, the “Variants of Concern” briefing, provides an apparently robust look into the question of post-BA.1 (“Omicron”) reinfection, with BA.2 or otherwise.

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Among “186,896 BA.1 confirmed cases with genome sequencing” from December 27 to January 16 (out of 496,228 PCR-positives during that time), only “Thirty-one of these cases had another subsequent sequenced sample with an interval of at least 20 days after a previous positive test, with a maximum follow-up period of 72 days.”

All but 1 of these 31 sequenced samples matched for BA.2. If the rate of sequencing per PCR-positive is comparable for putative reinfections, then only ~16 out of every 100,000 BA.1 infections (30/1.86896) was followed by a rapid reinfection with BA.2.

In the same report, “reinfections” defined by a 90 day window also do not appear rampant in the BA.2 era, compared to BA.1 or to the overall BA.2 spike (this may be an artifact of delayed reporting for reinfections; however, I believe that the reinfection plot is equally or even more current):

source: UK Health Security Agency (pdf)

Further, to conclude that the “BA.2 era reinfections” are in fact rapid reinfections, and are occurring among the Covid vaccinated specifically, we would need to know:

• The date of previous infection for March reinfections.

• The Covid-vaccination status of the reinfected.

If, instead, the reinfections in March are from individuals previously positive in 2020 or 2021, then BA.2 is merely carrying on the work of BA.1 in exploiting evasion from previously air-tight natural immunity - following the first sibling in the reinfection buffet line, rather than pilfering from said sibling’s plate.

Worry Window Dismissal

An alternate account for the endless wave in the UK might propose that the injections are directly increasing positive tests, rather than leading to downstream reinfections. However, like “OAS,” the “worry window” is a myth, or at least unlikely to drive large-scale infection trends. There is no strong evidence supporting the “worry window.” An upcoming post will revisit this topic; but for now we’ll just arbitrarily exclude the myth from our analysis and move on.

Innate Immune Deficiency and Critical Mass

So, we land back where we have been since autumn. A region-scale disruption of the virus’s “normal” (compared to most regions) pattern of invasion and retreat; a plethora of anecdotes alleging that the Covid-vaccinated, especially in the UK, are in a sort of “infection purgatory” - suffering constant colds or back-to-back positive tests for SARS-CoV-2, etc. - and a single plausible mechanism, one which suggests possible experimental validation: Innate immune suppression.

However, such experimental validation has yet to arrive.

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So I still feel hesitant to litigate the case in favor of innate immune suppression, even if the circumstantial evidence seems to be piling up higher and higher.

Instead, I will offer the reader my provisional speculation on how innate immune suppression could account for what is still the most striking feature of the UK’s endless wave: Why it isn’t repeated in Israel and New England. Funnily enough, it has to do with AIDS, and why the “HIV-AIDS theory” performs strongly for the first group of cases, among injection-sharing (or proximate), sexually promiscuous 80s-era artistes, and not for later cases among normies. The speculation is this:

Symptomatic immune-suppression is enhanced by Network Effect.

If you have impaired your innate immune system to some marginal degree, your likelihood of noticing the impairment is increased according to how much immune challenge is thrown at you. Likewise, your likelihood of throwing more immune challenge at someone else increases. Eventually (as the portion of innate-impaired in a population increases), even the non-impaired will be affected in some degree by the feedback loop of high background immune challenge.

One way to characterize this might be as the antithesis of Herd Immunity (however, “Herd Immunity” is also a myth

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). A simpler route, though it violates the official Unglossed style guide, is to use analogy:

• If you are lazy with cleaning up crumbs in your kitchen, you are still unlikely to get roaches in an apartment building without other dirty neighbors. You don’t have a “problem” with your kitchen habits.

• If a good handful of your neighbors are dirty, you will not get away with leaving out crumbs. Your kitchen habits are a “problem.”

• If half or almost all of your neighbors are dirty, you will have roaches in your kitchen no matter how strictly you clean it. Your residence in the apartment is the problem.

Thus, I submit this loose theory of Network Effect / critical mass as a tentative account for why the real-world anecdotes and circumstantial evidence for innate immune suppression from the Covid vaccines remains inconsistent, and (so far) centered on the UK.

• Innate immunity is lower in the UK at baseline, due to latitude, than in Israel and to a lesser extent New England.

• Covid vaccination rates are meanwhile higher in the UK than in regions with comparable density, directly feeding the innate suppression Network Effect. However, West Europe at large, as well as Israel, urban Australia and New Zealand, have caught up. Canada is not considered to be as dense for this loose analysis (and case reporting seems less transparent anyway). Covid-vaccination rates in urban New England are possibly over-estimated, and rural New England is not as dense.

• Thus, as with HIV-AIDS, the Covid-vaccine-“VAIDS” link may be valid for individuals who currently reside in high-Network-Effect regions but not for individuals elsewhere.

If you derived value from this post, please drop a few coins in your fact-barista’s tip jar.

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1. On the other hand, while less-Covid-vaccinated Eastern Europe participated in the “Omicron wave” at first, there hasn’t been a second peak as in the West; this provisionally suggests that the Covid vaccines may be having an influence on case patterns after all.

2. See “(Not) Coming Up.”

3. The centerpiece of this series is probably “Original Antigroundhogic Sin.” But see also:

“Even-Steven.” (OAS is “proven” via generation of a more balanced immune responseagainst Alpha or Delta after breakthrough infection.)

“Macaque Me an Offer I Can’t Refuse.” (OAS is “proven” via animal models where mRNA-vaccinated hamsters and macaques do better than unvaccinated controls vs Omicron.)

“Funeral for a Fact,” footnote 3. (OAS is “proven” because the boosters restore infection efficacy vs. Delta during the Omicron wave.)

“Darmok and the Spike Protein at Tanagra.” (OAS is “proven” when high pre-existing antibodies against coronaviruses… don’t correlate to severe outcomes in infection with SARS-CoV-2 in any way.)

4. See Chudov, Igor. “Australia: Deadly Hong Kong Covid Variant Taking Over.” (2022, April 3.) Igor’s Newsletter.

5. See “Darmok and the Spike Protein at Tanagra,” Footnote 8.

6. Edit, May 2:

Somehow, the UKHSA’s comment about “recent observations” was added to the report at the same time as Public Health England posted to pre-print a paper detailing observations of breakthrough-infection N-seroprevalence, apparently solving the mystery of the source of the “recent observations,” and yet the UKHSA has (apparently) never cited the PHE paper in all the subsequent references to their alleged “observations.”

See Whitaker, H. et al. “Nucleocapsid antibody positivity as a marker of past SARS-CoV-2 infection in population serosurveillance studies: impact of variant, vaccination, and choice of assay cut-off.”

Here, blood samples are randomly requested 4 - 6 weeks after PCR-confirmed infection with SARS-CoV-2, with the variant determined either by S-gene failure or by date of the PCR.

Thus, with sufficient time for seroconversion for both variants, the “probably early, Alpha breakthrough” and “not-so-probably early, Delta breakthrough” can be compared, with greater stakes for “proving Brian right” riding on the latter result. N-seroconversion rates are below-normal, but high in the Alpha breakthrough set and near-universal (62 of 64) in the Delta breakthrough set.

Whitaker, et al. Table 1.

Note that Covid-vaccinees, despite being largely N-positive, do have lower concentrations of N-antibody, but they all meet a lower cutoff and mostly all meet a higher cutoff for the assay (see Table 3). This could mean that the UKHSA’s comment is “right for the wrong reasons,” in that N-seropositivity may not show up for samples taken as long after “breakthrough” infection compared to for natural infection, which would make random sampling less accurate. A further bias in a sample for “longer time from infection,” including in older age groups, could further exaggerate this effect.

Also:

For comments on Follmann, et al., which looked (duh!) exclusively at early “breakthrough” infections, see “The Moderna N-Antibodies Paper.” Note that the findings by Whitaker, et al. suggest that early sample timing may have largely driven the results in the Moderna paper.

Meanwhile, another “not on my wish-list” study was recently released on the propagandistic CDC MMWR platform. See Clarke, K. et al. “Seroprevalence of Infection-Induced SARS-CoV-2 Antibodies — United States, September 2021–February 2022.”

Predictably, this MMWR release provides almost no raw data to help explore the meanings of the results. Rates of Covid-vaccination in each age group could be approximated by S-antibody positivity; it isn’t reported. Still, the results for the 0-11 vs 12-17 group provide a robust test of the impact of Covid-vaccination on N-antibody generation. A test which is failed (Covid-vaccination does not lessen N-antibody rates in teens):

Additionally, the differences in how many are still unvaccinated does not seem able to account for the (larger) difference in how many are N-positive (so that even if all unvaccinated have been infected, they, alone, cannot drive the differences between age groups). The difference between age groups is thus likely a reflection of other factors.

Anyway, kudos to this bad CDC study for finally alerting me to the pretty good PHE study.

7. (link anchor)

8. This pattern may also appear in “reinfections” amongst (formally) immunocompromised populations, whenever reinfections are defined as positive tests after a 90 day window from the previous positive. See “Oh Nomicron!” Footnote 19.

9. See https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1063424/Tech-Briefing-39-25March2022_FINAL.pdf

10. The mechanism and the weakness of experimental evidence confirming it are both discussed in “Neg.”

11. See “Die Herd.”

12. (Housekeeping notice for longer-term subscribers: Going forward, I am replacing the monthly “drive” model with per-post donation solicitation. However, I will continue to try to create value for long-term readers via monthly “magazine-worthy” articles!)