Back in October, when the
critics rounded on the UKHSA for publishing vaccine data that didn't fit the narrative,
front and centre of their complaints was the claim that they were using poor estimates of the size of the unvaccinated population, and thus underestimating the infection rate in the unvaccinated. Cambridge's Professor David Speigelhalter didn't hold back,
writing on Twitter that it was "completely unacceptable" for the agency to "put out absurd statistics showing case-rates higher in vaxxed than non-vaxxed" when it is "just an artefact of using hopelessly biased NIMS population estimates".
To the UKHSA's credit, while it conceded other points, it never gave in on this one, sticking to its view that the National Immunisation Management System (NIMS) was the "
gold standard" for these estimates. It pointed out that ONS population estimates have problems of their own, not least that for some age groups the
ONS supposes there to be fewer people in the population than the Government counts as being vaccinated.How can we know which estimates are more accurate?
A group of experts has applied analytical techniques in order to estimate the size of the unvaccinated population
independently of ONS and NIMS figures. Using three different methods,
experts from HART found that estimates from all three methods were in broad agreement with the NIMS estimates, whereas the ONS estimate was a much lower outlier.The first method involves recognising that
people not within the NHS database system still catch Covid and still get tested. Assuming these people have the same infection rates per 100,000 people as the unvaccinated, you can calculate how many people there are outside of the database system and add these to the NIMS totals.
The second method involves
looking at the rate of growth of people with an NHS number, which has been remarkably steady at around 2.9% per year. If you assume that people who are not yet registered in the NHS will sometimes become sick enough to seek healthcare, and thus a record will be created for them,
applying this growth rate to the 2011 ONS population estimates give another figure for the total population.The third method involves assuming that,
in low-Covid weeks, deaths within an age bracket should occur at a similar rate in vaccinated and unvaccinated, allowing the size of the total population to be inferred from the percentage of deaths in the unvaccinated.
The results in terms of reported infection rates according to the five different estimates are depicted in the chart above. They show that the
ONS is a clear outlier, its estimates sitting far too low, and NIMS is likely to be much more accurate. The ONS puts the unvaccinated population at around 4.59 million whereas NIMS puts it at 9.92 million, a difference of 5.33 million. That's a lot of people not to be included in estimates, and suggests, among other things, that the ONS has
not adequately estimated the magnitude of illegal immigration into the country.As well as vindicating the UKHSA in its decision to stick with NIMS over ONS, HART's analysis also indicates that, contrary to the assertions of Prof Spiegelhalter,
the UKHSA data showing infection rates higher in the vaccinated compared to the unvaccinated is not a mere artefact of using the wrong population estimates. There may be other biases in it, but this is not one of them.
Here is the weekly update on unadjusted vaccine effectiveness based on the raw data in the UKHSA
Vaccine Surveillance report. The unadjusted vaccine effectiveness estimates against infection have
remained low in all adult age brackets this week, particularly in those aged 40-70, though there is little sign of further decline; in the older age groups (over 40), the recent vaccine effectiveness revival continues, possibly as a result of the third doses. There is also a sign of a rise in vaccine effectiveness against hospitalisation in the over-70s.
VE Age Table
In Nazi Germany, the public perception of the secret police was that it was terrifyingly all-seeing and all-knowing, where the reality was much later revealed to be that the offices of the Gestapo were a pathetic shambles of nearly useless record keeping, that most of their actionable intelligence simply came from neighbors ratting out neighbors and not any actual detective work or data collection and analysis.
But the false perception of omnipresent surveillance was such a driving force that other systems were largely unnecessary, except for show.
I don't know if that pattern maps onto the situation today, given that we now actually have the technology to track and process massive amounts of data, but it is still curious that nobody seems to have access to what one would think are very basic numbers wrt Covid vaccination coverage.
I find that cautiously encouraging.
Mind you.., it's a spotty history. There is also the story of IBM providing the computer technology necessary to accurately map Semitic bloodlines in the German population, a project pursued with grim determination and energy and, if the history is true, astonishing accuracy.
It may simply be a matter of compartmentalization, with many left hands not knowing what the many right hands are doing.
Another feature of Nazi Germany was that Hitler and his staff were extremely vague when it came to social dictates, leaving heads of all the various agencies acting on guesswork in an effort to interpret what the great dictator might want from them, resulting in a race of psychopaths trying to out-evil each other, and to climb professional ladders by accusing their competitor/peers of not being true enough to the Reich. -A system which organically developed new evil practices at a far speedier rate than if they were all actually following dictates from the top.