Friday, 3 December 2021

Possible systematic miscategorisation of vaccine status raises concerns about claims of Covid-19 vaccination effectiveness

24 Dec Update: The new ONS report has serious anomalies

5 Dec Update: Norman Fenton was interviewed about this work on the Maajid Nawaz show on LBC on 4 Dec: 

 

 

 

 

Our research team have now analysed the ONS England November mortality data. We conclude that, despite seeming evidence to support vaccine effectiveness, this conclusion is doubtful because of a range of serious inconsistencies and anomalies. Our detailed report is here.


The data appear to show lower non-Covid mortality for the vaccinated compared to the unvaccinated. Odd. Also unvaccinated mortality rates peak at the same time as the vaccine rollout peaks for the age group, then falls and closes in on the vaccinated. This is not natural

 

Consider what we are witnessing here. We have a vaccine whose recipients are suffering fewer non-covid deaths and hence are benefitting from improved mortality. And the mortality rates look to differ significantly from historical norms, as evidenced in mortality lifetables.

Correlating unvaccinated mortality with vaccine roll out we see curious patterns (dotted line the proportion of people getting first and second doses). Why are the unvaccinated dying after NOT getting the 1st dose? Why are the single dosed dying after NOT getting the 2nd dose?

 

 Plenty of evidence that the vaccinated who die within 14 days of vaccination may be categorized as unvaccinated. Then someone who dies within 14 days of first dose is miscategorised as unvaccinated and a similar thing could occur post second dose.

 

 

Miscategorization might explain odd phenomena in ONS mortality (as previously explained with this hypothetical example). To correct the error we can take the difference between the expected mortality for the unvaccinated and the data, and re-allocate this unexpected excess mortality to the vaccinated to get new ADJUSTED estimates.

 


The early spikes in mortality that appear to occur soon after vaccination may be caused by the infirm, moribund, and severely ill receiving vaccination in priority order and thus simply appearing to hasten deaths that might otherwise have occurred later in the year.

Turning to Covid mortality, at face value, there appears to be clear evidence of vaccine effectiveness.

 

But……..After vaccination people endure weakened immune response for a period of up to 28 days and may be in danger of infection from Covid or other infectious agent at any time in that period. It therefore makes sense to examine infection date rather than date of death registration.

We adjust for this using a  temporal offset and see a large spike in mortality for all age groups during the early weeks, when covid prevalence was high, and when the first dose vaccination rollout peaked.

 

After our offset adjustment we observe no significant benefit of the vaccines in the short term. They appear to expose people to an increased mortality, in line with what we know about immune exposure or pre-infection risks,

Whatever the explanations for the observed data, it is clear that the ONS data is both unreliable and misleading.

Absent any better explanation Occam’s razor would support our conclusions. The ONS data provide no reliable evidence that the vaccines reduce all-cause mortality.

Full reference:

Martin Neil, Norman Fenton, Joel Smalley, Clare Craig, Joshua Guetzkow, Scott McLachlan, Jonathan Engler and Jessica Rose, “Latest statistics on England mortality data suggest systematic miscategorisation of vaccine status and uncertain effectiveness of Covid-19 vaccination”, http://dx.doi.org/10.13140/RG.2.2.14176.20483

The paper has also benefited from the input of senior clinicians and other researchers who remain anonymous to protect their careers.

See also:

The impact of misclassifying deaths in evaluating vaccine safety: the same statistical illusion

This video provides some background:


 

 

29 comments:

  1. Best analysis yet. Well done!!

    ReplyDelete
  2. It was clear from the start that something like this was happening, but your analysis just crystalizes it nicely. I think it may be apt to introduce a data-science corollary to Occam's razor that would have avoided this error:

    -When comparing multiple phenomena, choose the comparator that introduces the fewest distinctions between the classes while differentiating between them as completely as possible.-

    If that approach had been taken, then the obvious comparison would have been been deaths after injection and deaths after infection. The whole idea of using a two-week lag after injection to count vaccine mortality is utterly absurd to me. It was obviously going to introduce a harvesting effect.

    ReplyDelete
  3. Great work! I suspected this all the time.

    ReplyDelete
  4. https://www.ons.gov.uk/aboutus/transparencyandgovernance/freedomofinformationfoi/definitionofanunvaccinatedindividual

    ReplyDelete
    Replies
    1. This comment has been removed by the author.

      Delete
    2. Thanks for the link, for the people reading this, here is the content of this page:

      "Definition of an unvaccinated individual
      Release date:
      11 October 2021
      FOI Reference: FOI/2021/2989

      You asked
      ​1. Please could you provide me with the official ONS definition of an 'unvaccinated individual' that you use when reporting figures of deaths involving Covid-19.

      2. Do you consider an individual 'unvaccinated' if they die within 7 or 14 days of their first dose?

      I am specifically referring to the recent report analysing deaths involving Covid-19 that occurred between 2 January and 2 July this year.

      We said
      Thank you for your enquiry regarding the definition of "unvaccinated" in our recent publication Deaths involving COVID-19 by vaccination status, England: deaths occurring between 2 January and 2 July 2021.

      An unvaccinated individual is someone who has received no vaccinations.

      The risk of a new infection following vaccination is highest during the first 21 days after the first vaccination, as shown by analysis of the COVID-19 Infections Survey.

      So therefore our analysis is based on deaths within 21 days after first dose, 21 days or more after first dose, deaths within 21 days after second dose and finally 21 days after second dose as this is when vaccine is deemed most effective.

      If you have any further enquiries, please contact Health.Data@ons.gov.uk."

      In my opinion, the ONS is *refusing* to define whether they consider people as vaxxed in the first 2 weeks by circumventing the question. Also, they appear to admit the initial vulnerability of the vaccinee but by their definition that is 3 weeks rather than 4 as Fenton takes it.

      Delete
  5. FYI, some typos on your paper:
    "Non-Covid mortality rate in unvaccinated and unvaccinated versus % vaccinated in age group 70-79"
    Should say "vaccinated", not "unvaccinated". This error is propagated through several of your charts.

    ReplyDelete
    Replies
    1. Consider rephrasing this. Does not make sense, so I suspect a typo:
      "In all Figures 12 to 14 we see peaks in mortality risk for the unvaccinated across the three age groups that
      occur almost immediately as if they had received the first vaccine and peak at consecutively later times in
      line with when vaccine was administered for that age group. "

      Delete
    2. It makes perfect sense to me, although admittedly it is a bit too long and slightly convoluted. Which part do you find confusing?

      Perhaps, the last part of the sentence starting with "and peak at" should be a new sentence, e.g. "Furthermore, this mortality peak occurs at consecutively later times in line with vaccine administration timing for that age group. "

      Delete
  6. Thank you so much. Your research is very eye-opening and has kept me up all night more than once. Some suggestions, comments, and questions:

    1) The clinical trials similarly do not do analysis until some days after second dose. The analogous problem there I suppose is not “misclassification”, but censoring. Maybe someone should analyze how sensitive the results of those trials are to the censoring of those earlier times?

    2) Just as you have done a temporal offset for covid mortality, a similar offset would be sensible for all-cause mortality, right? Even if date of death is used, wouldn’t the delay between vaccination and “death due to vaccination” result in similar bias?

    3) It would be great if someone repeated similar analyses for the US data. Different results could give insight into what dataset has or doesn’t have what bias.

    4) Is it right to presume that this same type of misclassification will play out the same with hospitalization rates?

    5) Reference 19 in your paper leads to Livingston paper, which does not actually say anything about acute weakening of immune system. I’ve seen some charts floating around where people argue it is happening. You might be better served using those. Or else use your own final figures to raise the hypothesis.

    6) In non-pandemic times, avoidance of flu vaccine among the elderly has been shown to be a predictor of death. Though in pandemic times this has likely been reversed with perhaps the most frail being vaccinated first. However, in other age groups, you can’t assume this. Just look at WebMD reviews of the vaccines. Lots of people are clearly stopping after having a bad reaction to 1 dose. Self-selection (confounding by contraindication) is definitely a factor. In vaccine literature as a whole, the vaccinated do in fact tend to be healthier than the unvaccinated.

    7) Why are the “baseline” non-covid mortalities you computed from the ONS data lower than the lifetable mortalities? This is surprising given the immense harms of lockdown should definitely be expected to increase non-covid mortality above past years. My guess here is that this is a signal of misclassifying non-covid deaths as covid deaths. Or equivalently, it is a sign of the fallacy of counting deaths instead of counting years of life lost. This suggests that mislabeling cause of death is happening to such an extent that it completely offsets the expected increase in mortality from lockdown harms, and then some more. What is your interpretation?

    8) I think one more important confounder not addressed in this subject matter is the unvaccinated becoming increasingly naturally immune.

    9) A couple more typos:
    - Fig 25 lists the wrong age group on the label.
    - Fig 17 and Fig 18 misspells “non”

    ReplyDelete
    Replies
    1. Vaccination appears to be associated with increased cases in the first 2 weeks following vaccination. Relevant to your argument.
      https://www.researchgate.net/publication/351451876_USA_state-by_state_analysis_vaccinations_increase_COVID19_cases_3-6_days_later
      https://www.researchgate.net/publication/351136912_The_more_vaccinations_the_more_COVID19_cases_15_days_later_in_India_state-by_state_analysis

      Delete
  7. Another explanation for this apparent anomaly is that covid infections are being missed, therefore the surge in unvaccinated non-covid deaths is because some covid deaths are miscategorized as non-covid deaths.

    ReplyDelete
    Replies
    1. 1. Then why should only Covid deaths amongst the UNvaccinated be systematically miscategorized as non-Covid? That does not make any sense.

      2. That's not practically believable given what we know for a fact - non-Covid deaths are systematically treated as Covid deaths.

      Delete
  8. I appreciate learning that when I don't like how the data looks I can just hypothesize an explanation for why it is wrong and then "correct the error" to get new ADJUSTED estimates. Life will be so much easier moving forward!

    ReplyDelete
    Replies
    1. If you have a hypothesis for why Person A taking the vaccine would cause Person B to spontaneously drop dead, I welcome it.

      Delete
    2. Why hypothesize about something silly when we can say with certainty that the unvaccinated population includes people too ill to get jabbed. If you look at the ONS data underlying figure 9 above you will see that the unvaccinated population in the 70-79 age group dropped from 4.1 million to 397,000 from weeks 1 to 7. The share of that population that is too ill to get vaccinated is surely higher in week 7 than in week 1.
      Another thing to point out is that the ONS mortality rates are statistical estimates with confidence intervals, some of which are quite large. From week 6 onward the all cause mortality rate confidence interval is +/- 10-15 points. How many of the differences pondered here are even statistically significant?

      Delete
    3. There is nothing silly about his hypotheses. On the other hand, your speculation that the very frail were not vaxxed is just that - a speculation with no evidence to support that. We don't know why the unvaxxed chose to stay so and the frail were certainly not discriminated against or advised against the jab by the NHS. Onthe contrary, all we heard was that the vulnerable are prioritised. Therefore, there is no reason to believe that the unvaxxed are particularly frail and certainly there is no evidence.

      Delete
  9. The mortality spikes post vaccination ( or post not considered vaccinated) do look similar to the Adverse event reporting curves.

    ReplyDelete
  10. The LBC interview is now unavailable on YouTube, but can be found here: https://www.bitchute.com/search/?query=norman%20fenton%20interviewed%20by%20majid%20nawaz,%20lbc%20radio%204%20dec%202021&kind=video

    ReplyDelete
  11. I wonder if reported AE's could be analyzed like this: Instead of looking at vaccines, look at all other drugs. Look only at deaths that were NOT associated with vaccination. Then see if deaths, stratified by age, have any spike that coincides with vaccine rollouts. The point of this would be that it negates the concerns that vaccine-associated deaths are just getting reported out of an abundance of caution (i.e. correlation is not causation). If vaccines are not listed on an AE report, then the clinician, etc., is very unlikely to have ever had vaccines cross their mind as a possible cause of death, thus eliminating the reporting bias.

    ReplyDelete
    Replies
    1. What do you mean by "all other drugs"?
      Fenton already looks at both all-cause and non-covid death as per your suggestion (or similar). Also, officially there are no vaccine related deaths so in essence all his analysis is looking at "death not related to vaccines", as per your suggestion.

      Delete
    2. I mean use an adverse event reporting database as the data source.

      Delete
  12. I wonder whether you found also this detail: "120,000+ people aged 70 to 79 did not move into the ‘Within 21 days of the first dose’ group after getting their first dose."


    https://idee.frank-siebert.de/2021/12/18/taking-englands-all-cause-mortality-data-literally/

    Let me know your thoughts about this.

    ReplyDelete
  13. Ufabet, just like other casinos on the internet, provides its players an online environment for betting. You can play poker or other games live on various sports. Your banking account will be secure. Ufabet requires that you have an active Line application. It is required to be able to contact the staff and operator in case of issues. Register today if you have never used ufabet before and start winning! ufabet

    ReplyDelete
  14. “CDC overcounts millions of vaccinations”. So here we have yet a second type of misclassification that points in the same direction:
    https://www.axios.com/cdc-revises-data-overcounting-number-vaccinations-29816191-c921-4942-bdd4-879b24f172f6.html
    https://www.usnews.com/news/health-news/articles/2021-12-21/uneven-reporting-raises-doubts-about-cdc-vaccination-numbers

    ReplyDelete
  15. After spending too many hours searching for criticism of this study on Twitter, I can mention (apart from the torrent of straw men, ad hominems, and undeserved self-congratulations) that there does seem to be at least one more possible explanation of these unvaccinated mortality spikes. Namely, people who are too sick to get it at the moment (or in general) may become concentrated in the ever-shrinking unvaccinated group. These are not people necessarily averse to vaccination. They may then die in a cluster. On the other hand, such an effect would be opposed by confounding by indication, where many of the very sickest may be absent from the dwindling unvaccinated group precisely because they made sure to get vaccinated.

    So in short, the misclassification hypothesis definitely still stands.

    ReplyDelete
  16. https://covid19.ca.gov/state-dashboard/#postvax-status
    Here is a dataset from a dashboard in California, USA where I live. At least as of today, it looks like it may fit the same pattern of spikes around third vaccine rollout.

    ReplyDelete