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Vaccine Effectiveness in Ireland

  • 24-08-2021 2:09am
    #1
    Registered Users Posts: 95 ✭✭


    The actual HSE data on vaccine breakthough cases in Ireland indicates that the effectiveness of the vaccines is significantly lower than 93%


    On the 12th of August at a HSE briefing Paul Reid released the following figures on vaccine breakthrough cases (real-world indication of the effectiveness of the vaccines) in Ireland:



    • 49% Covid patients in hospital fully vaccinated
    • 24% Of those in ICU were full vaccinated
    • 18% of those in ICU were partially vaccinated


    On the same day professor Philip Nolan released the following tweets to give more context to the above figures where we had 70% of the adult population protected (2 weeks after completing their regimen) and how he and his team are modeling this data.


    This is very interesting as not only have we received official data on breakthrough cases in Ireland, for the first time, we also get insight into how professor Nolan and his team are modeling and interpreting this data.


    I have attached an Excel spreadsheet of Professor Nolans model so you can change the key assumption parameters such as % vaccinated, % vaccine effectivness in preventing symptomatic infection, % vaccine effectiveness in preventing sever desiease requiring hospitalisation.

    The following is a screenshot of the spreadsheet reflecting what professor Nolan described as the current situation here on August 12th with 70% of the adult population protected (2 weeks after completing their regimen)

    As you can see the figures in the spreadsheet match the figures in the visualisation in professor Nolans tweets.

    Interestingly the admissions prevented was calculated on just the risk of hospitalisations % (5%) weighting and did not include the vaccine hospitalisation reduction % (65%). Including the vaccine hospitalisation reduction % increases the admissions prevented to from 137.2 to 159.5 which is an even better outcome for the message he is trying to convey so I'm not sure why he didn't include it.


    The following screenshot of the spreadsheet shows the figures in professor Nolans 90% vaccinated example (tweet 5/6)

    Again you can see that the figures match the visualisation presented by professor Nolan exept for the admissisions prevented which once again didn't take into account the vaccine hospitalisation reduction %


    The core point professor Nolan is trying to convey is as follows:

    If vaccine coverage increases to 90%, the majority of cases, and close to half the hospital admissions will be in vaccinated people, but it is a smaller number of cases (two-thirds of that with 70% coverage) and hospitalisations (less than half that with 70% vaccination)

    You can see in the spreadsheet data and his own visualisation the close to half the hospital admissions will be in vaccinated people equates to 38.57% (39% rounded in visualisation)

    The main issue is on the day professor Nolan posted these tweets with his model of the current situation (August 12th) the actual figure was 49% Covid patients in hospital fully vaccinated not the 14% portrayed in his model

    To get professor Nolans model to reflect the real figure which was 49% Covid patients in hospital fully vaccinated both the % vaccine effectivness in preventing symptomatic infection and the % vaccine effectiveness in preventing sever desiease requiring hospitalisation have to be significantly reduced.

    As an example if we assume the % vaccine effectiveness in preventing sever desiease requiring hospitalisation is 0% and leave % vaccine effectivness in preventing symptomatic infection at 80% the we get the following:

    The admission % goes up to 31.82% but is still 17% off the real figure 49% so

    To get to the real figure of 49% we have to reduce the % vaccine effectivness in preventing symptomatic infection to 59% which is a 21% reduction in effectiveness as shown in the following screenshot of the model

    If the % vaccine effectivness in preventing symptomatic infection is set to 0% and % vaccine effectiveness in preventing sever desiease requiring hospitalisation is 93%

    The hospital admissions in the fully vaccinated group would be 14.04% which is a long way off the actual value of 49%.

    To get to the real value of 49% the % vaccine effectiveness in preventing sever desiease requiring hospitalisation needs to be set to 58% which is a 35% reduction in effectiveness


    The vaccine breakthrough data from the HSE briefing on the 19th of August was as follows:


    • 45% Covid patients in hospital fully vaccinated
    • 23% Of those in ICU were full vaccinated
    • 15% of those in ICU were partially vaccinated

    75% vacinnated

    Inputting this data into the model gives us 17.36% fully vaccinated admitted to hospital which is requires a 27.64% adustment between the % vaccine effectivness in preventing symptomatic infection and/or the % vaccine effectiveness in preventing sever desiease requiring hospitalisation.


    Similar data out of Israel indicated the % vaccine effectiveness in preventing symptomatic infection and transmission is an average of 39% where the effectiveness seems to decrease from the time you are vaccinated down to 16% 6 months out. However, this data showed that there was still 91% protection against serious illness but the Irish data seems to indicate the decrease in effectiveness is following though to serious illness when we are seeing that 23% of the people currently in ICU in Ireland are fully vaccinated and a further 15% were partially vaccinated.

    How is there not more discussion on this!?



«13

Comments

  • Registered Users Posts: 31,008 ✭✭✭✭Lumen


    Your model does not account for age related hospitalisation risk and vaccine coverage.

    I say "your model" because it's your spreadsheet, not Nolan's.

    There may be issues with Nolan's model too, but I find your presentation a bit confusing in as far as it doesn't make a single mathematical point.

    I also bothered by the omission of the important "additional" qualifier in Nolan's tweets (and your spreadsheet), which is present in JBMs infographics.



  • Registered Users Posts: 6,702 ✭✭✭Pete_Cavan


    Does your figure of 49% Covid patients in hospital fully vaccinated come from the Paul Reid quote at the beginning of your post where he says 51% in hospital have not been vaccinated? If so, it is unlikely that all of the non non-vaccinated are fully protected (2 weeks after completing their regimen, as Prof. Nolan puts it). The 49% is probably made up of fully and partially vaccinated people, with fully vaccinated making up only a portion of that.

    Some of those in hospital with Covid on August 12th could have been infected more than two weeks earlier, when fully vaccinated % was less. I am note sure of the time between infection and hospitalisation for Delta, also have to account for them having been in hospital for a few days at that stage. Fully vaccinated % was probably below 70% when these people caught it.

    Hospital acquired infections could also skew the figures. If the in hospital Covid figure includes people who were in hospital for other reasons and tested positive while there, it would not be a reflection on vaccine effectiveness.

    I think Prof. Nolans figures are a theoretical example of the benefits of vaccinations. I doubt it was intended to fully reflect actual figures as there are variables in the real world which are incredibly difficult to account for in such figures.



  • Registered Users Posts: 95 ✭✭Mr.StRiPe


    The spreadsheed represents professor Nolans model if you have spotted any errors please let me know and I'll correct them. This is why I attached the spreadsheet so anybody who wants to can try it out and point out if there are any errors it.


    Your model does not account for age related hospitalisation risk and vaccine coverage.

    It is not my model it is the HSE model populated with HSE data.

    I can only go off the data and the model that was released by the HSE and can only assume they are taking everything into account when they choose release this data as a single headline figure at the briefings with no further refernce data to go off of.

    The model explicitly accounts for vaccine coverage @70% as follows:

    Estimated outcomes over a 7-day period where 70% of the population is fully vaccinated

    Professor Nolan even clarifies this further in his 2nd tweet (which is referenced in post above) where he says:

    We have 70% of the adult population protected (two weeks after completing their regimen)


    There may be issues with Nolan's model too, but I find your presentation a bit confusing in as far as it doesn't make a single mathematical point.

    The mathematical point I am making is when you add the real figures into the HSE model it is mathematically impossible to get to 49% people in hospital fully vaccinated with a % vaccine effectivness in preventing symptomatic infection at 80% and % vaccine effectiveness in preventing sever disease requiring hospitalisation at 93% when 70% of the Irish population is fully vaccinated

    Then I showed matheatically in the extreme examples where we reduce one of these vaccine effectiveness to 0% you have to also reduce the other effectiviness % to achieve 49%


    I also bothered by the omission of the important "additional" qualifier in Nolan's tweets (and your spreadsheet), which is present in JBMs infographics.

    My spreadsheet includes both of the JMBs infographics I assume you are referring to the following qualifier on the infographics?

    Assumptions: Background force of infection would cause 70 cases per day per 100,000 population in the unvaccinated population. Vaccine effectiviness in preventing symtomatic infection 80%, vaccine effectiveness in preventing sever disease requiring hospitalisation 93%, risk of hospitalisation in an unvaccinated case 5%

    If so, I reference the exact wording of Vaccine effectiviness in preventing symtomatic infection and vaccine effectiveness in preventing sever disease requiring hospitalisation and their assumed values when making the comparrisons against their values when the real data is entered into the model.



  • Registered Users Posts: 95 ✭✭Mr.StRiPe


    Does your figure of 49% Covid patients in hospital fully vaccinated come from the Paul Reid quote at the beginning of your post where he says 51% in hospital have not been vaccinated?

    Yes, as this is all I can go on as it is the only breakthrough data available and it is how the HSE have choosen to communicate it.

    If so, it is unlikely that all of the non non-vaccinated are fully protected (2 weeks after completing their regimen, as Prof. Nolan puts it). The 49% is probably made up of fully and partially vaccinated people, with fully vaccinated making up only a portion of that.

    It is possible that the 49% includes partially vaccinated people however, when Paul Reid gives the ICU data for fully vaccinated people he gives this breakdown which I referenced in the post above:

    • 24% Of those in ICU were full vaccinated
    • 18% of those in ICU were partially vaccinated

    As he broke the ICU data in to these 2 groups its not clear why he wouldn't have done the same for the hospital admission data if he had it available so I can only go off what he said.

    The ICU data is much more alarming as its clear he is talking about fully vaccinated people here at 24%

    Some of those in hospital with Covid on August 12th could have been infected more than two weeks earlier, when fully vaccinated % was less. I am note sure of the time between infection and hospitalisation for Delta, also have to account for them having been in hospital for a few days at that stage. Fully vaccinated % was probably below 70% when these people caught it.

    This is true which means the HSE model assuming that 70% of the population is fully vaccinated over estimates the vaccine effecitveness, if anything, for instance if you put 65% into the spreadsheet the effectiveness drops as to drop further to get to 49%. This is the point professor Nolan is trying to convey as the % of the population fully vaccinated increases from 70% to 90% he is expecting the majority of the cases and close to half the hospital admissions will be in vaccinated people.

    The issue is the model shows at 70% fully vaccinated with the real data the assumed Vaccine effectiveness metrics

    Vaccine effectiviness in preventing symtomatic infection 80%, vaccine effectiveness in preventing sever disease requiring hospitalisation 93%

    Are mathematically impossible and the real admissions are currently 10% higher (49-39) at 70% than what they should be at the 90% fully vaccinated.

    Hospital acquired infections could also skew the figures. If the in hospital Covid figure includes people who were in hospital for other reasons and tested positive while there, it would not be a reflection on vaccine effectiveness.

    This is an interesting point as it doesn't skew the Vaccine effectiviness in preventing symtomatic infection % as a fully vaccinated person still got a breakthrough infection however, it could skew the vaccine effectiveness in preventing sever disease requiring hospitalisation depending on how or if they are factoring it in to the headline figure they released. We have to assume the HSE are competent enough to be factoring this in especially when they only give a headline figure but as they haven't released the raw data we can't be sure.



  • Posts: 0 [Deleted User]


    You have gone to an awful lot of trouble to completely misunderstand the data.

    The rate of hospitalisation in under 50’s was 1/10th of that in over 50’s pre vaccine. Half of current icu patients are under 50.

    The median age of unvaccinated in Ireland at the moment is probably somewhere in the teens or possibly younger.

    Public health england produces some good reports on this topic. Would expect broadly similar data here

    https://www.gov.uk/government/publications/covid-19-vaccine-surveillance-report



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  • Posts: 0 [Deleted User]


    Is this what you’re getting at, OP?

    That the vaccines are protective against infection but not against serious disease and death in those vaccinated who become infected?



  • Posts: 0 [Deleted User]


    Seriously, you read that and thought it was worthy of sharing without immediately thinking, the DrRollerGator, I presume they are qualified to talk about what they are saying. And once you get to the actual “stats” they present. 1000 monkeys with access to a stats package would produce something with more coherent analysis.



  • Posts: 0 [Deleted User]


    Thanks, raind.

    I’ve followed DrRollerGator a while, actually. Their writings and analyses are fairly interesting, and since I myself make a good living by writing under a pseudonym, it’s not a thing that puts me off in and of itself.

    Anyway, onto more substantial things: What are the errors you’re seeing in the stats presented?



  • Registered Users Posts: 95 ✭✭Mr.StRiPe



    You have gone to an awful lot of trouble to completely misunderstand the data.

    The only official data released by the HSE on vaccine breakthrough in Ireland is as follows:

    August 12th with 70% of the adult population protected (two weeks after completing their regimen)

    • 49% Covid patients in hospital fully vaccinated
    • 24% Of those in ICU were full vaccinated
    • 18% of those in ICU were partially vaccinated

    August 19th with 75% of the adult population protected (two weeks after completing their regimen)

    • 45% Covid patients in hospital fully vaccinated
    • 23% Of those in ICU were full vaccinated
    • 15% of those in ICU were partially vaccinated

    The HSE vaccine protection model assumptions are as follows:

    Background force of infection would cause 70 cases per day per 100,000 population in the unvaccinated population. Vaccine effectiviness in preventing symtomatic infection 80%, vaccine effectiveness in preventing sever disease requiring hospitalisation 93%, risk of hospitalisation in an unvaccinated case 5%


    In what part of my initial post do you feel I have misundersood any of this data?


    The rate of hospitalisation in under 50’s was 1/10th of that in over 50’s pre vaccine. Half of current icu patients are under 50.

    The median age of unvaccinated in Ireland at the moment is probably somewhere in the teens or possibly younger.

    Vaccine effectiveness is measured by the breakthrough cases which means it is only relevant to people who have been vaccinated so I don't follow why you are referring to data when the vaccines were not available and the unvaccinated when the vaccines are available? .

    Public health england produces some good reports on this topic. Would expect broadly similar data here

    https://www.gov.uk/government/publications/covid-19-vaccine-surveillance-report


    In the latest report week 33 in the Vaccine effectiveness against the Delta variant section it lists the

    Vaccine effectiviness in preventing symtomatic infection

    Vaccine effectiveness in preventing sever disease requiring hospitalisation

    This is inline with HSE vaccine protection model where they assume

    Vaccine effectiviness in preventing symtomatic infection at 80%

    and

    Vaccine effectiveness in preventing sever disease requiring hospitalisation at 93%

    So it appears as we would expect the HSE are doing their due dilligance and keeping up to speed with all the latest data when they created their model.

    What it doesn't change however, is when you put the real vaccine breakthrough figures, as reported by the HSE for Ireland, into their vaccine protection model it is mathematically impossible to have vaccine effectiveness @ 80% for preventing symtomatic infection and 93% for preventing sever disease requiring hospitalisation.

    As demonstrated in my first post the effectiveness % in both cases require a signifficant reductuion to reflect the real data Ireland has reported over the last 2 weeks.



  • Registered Users Posts: 95 ✭✭Mr.StRiPe


    No, what I'm getting at is if you enter the real vaccine breakthrough data reported by the HSE into the HSE vaccine protection model it is mathematically impossible to have vaccine effectiviness the model assumes which is Vaccine effectiviness in preventing symtomatic infection at 80% and vaccine effectiveness in preventing sever disease requiring hospitalisation at 93%

    That the vaccines are protective against infection but not against serious disease and death in those vaccinated who become infected?

    When the official HSE data for breakthrough cases in Ireland on August 12th are inputted into the HSE model (also released on August 12th) even if you reduce the Vaccine effectiviness in preventing symtomatic infection from 80% to 0% you also have to reduce the vaccine effectiveness in preventing sever disease requiring hospitalisation from 93% to 58% otherwise the model does not reflect the real breakthough numbers that were reported.



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  • Registered Users Posts: 13,980 ✭✭✭✭Cuddlesworth


    Seems like your getting your figure not from the number of people admitted to hospital and then the ICU, but off of figures of people currently in Hospital/ICU.



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    One thing to keep in mind is that numbers hospitalised for covid would be overstated in HSE reports - as virus becomes more prevalent population wide, there will inevitably be more people admitted to hospital for non-covid reasons, who happen to test positive for covid.

    The other is that age & comorbidities are the 2 biggest factors for risk of covid - and these people would have been prioritised for vaccination. So the vaccine group have a higher risk from covid to begin with.

    The crux of the problem is that no proper long term studies of vaccine vs no vaccine have been done. Those initially done by Pfizer et al actually ended up informing the control groups (placebo injection) that they were unvaccinated - 90% of them promptly got vaccinated for real.

    We desperately could do with a control group of different ages, comorbidities, etc to get a true measure of vaccine effectiveness - but we wont. We have long since decided to vaccinate everyone regardless of how effective it really is - the lack of control groups means we dont really know how well its working.



  • Registered Users Posts: 13,980 ✭✭✭✭Cuddlesworth


    That makes no sense, you don't need a control group past the initial trials, of which there were multiple done for numerous vaccines.

    Also you have a "control group" in the population anyway, it's the unvaccinated people. And everything I can see says they are worse off then unvaccinated.



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    The unvaccinated people are overwhelmingly younger - so you cant get an accurate measure of effectiveness because vaccinated people are majority older - and therefore, higher risk.

    The purpose of a control group is that they should mirror the test group in composition, with the only significant difference being the vaccine they get. That is not true with the current vax/unvax split.

    And yes you do need control groups past the initial trials - you cannot count the prevalence of side effects or vaccine effectiveness without a control group to benchmark against. IF you vaccinate your entire control group - how can you calculate efficacy if you dont know risk of unvaccinated control group?



  • Registered Users Posts: 1,379 ✭✭✭schmoo2k


    What you say is true if you want accurate numbers - but for now the real world tends are clearly showing that the higher the vaccinated % is, the safer it is to lift restrictions.



  • Registered Users Posts: 13,980 ✭✭✭✭Cuddlesworth


    So in your mind when do you no longer have a trial and control group. Whats the point where you yourself declare that the data is good and go forward with a vaccine rollout in the middle of a global pandemic? Whats the number of trials, the locations, the group size, the timeframe in which its run? Do you start again with each new variant, do you segregate by region and restrict access to the vaccines so that you can retain a good sample size for future never ending trials? Do you pick out the populations with higher median ages over populations with lower median ages?

    Why do you believe your viewpoint of more trials, control groups, higher death rates and long term covid effects on the populace which are known and documented, is at odds with multiple independent groups of public heath experts spread across the world?



  • Registered Users Posts: 16,456 ✭✭✭✭astrofool


    I'd love to be the politician announcing that the vaccines continue to remain effective because we're seeing more people in the population control group dying.

    For a variety of reasons, this isn't what happens in the real world (where there is also unvaccinated countries to compare against).



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    In emergency conditions you can use emergency protocols. They got emergency use approval (or equivalent thereof) in many jurisdictions, and went vaccinating before phase 3 trials had finished, nevermind phase 4. And rightly so - however you cannot stand by the efficacy numbers and say they are "true" when the process of measuring them is inherently flawed. Ideally, the trials that Pfizer initially had would have been kept going and not been ruined by vaccinating the control groups. But then you get into ethics issues I suppose - either way there are ethical issues really - to keep a small group of people unvaccinated to get a true measure of efficacy and baseline rate of possible side effects would be more valuable to society as a whole.

    Every viewpoint is at odds with multiple groups of experts and scientists. There is very rarely (if ever) widespread consensus on any of this stuff. For every "expert" you find who supports your position, I can find same who supports the opposite. Consensus does not create truth - facts and data do. And my point here, is that the numbers on efficacy are not calculated with best practice and are inherently flawed. They may be more efficient than we are led to believe, or less, or vary largely with age and other factors. The truth is that we do not know.



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    Its a bit grim but this is the normal approach. When you enroll in a clinical trial you accept all these risks - thats just how it is.

    All other vaccines before this were approved/denied based on a difference in outcomes between test and control groups. Even the emergency use for pfizer/moderna etc were all based on a reduction in death compared to a control group. Its not anything new.

    And sure with the way society is partitioning into us vs them on vaccines vs unvaccinated, people would cheer politicians announcing such things.



  • Registered Users Posts: 3,817 ✭✭✭Darc19


    Did people waste time and actually read the OP's post?

    All I saw was some random person online that seems to have no expertise whatsoever and less grasp of how figures work trying to show that he/she is an" expert" (YET ANOTHER EFFIN ONLINE EXPERT)

    OP - i reckon you spent a couple of hour constructing that - what a waste of a couple of hours


    For me, a quick glace showed that you really have not got a clue



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  • Registered Users Posts: 16,456 ✭✭✭✭astrofool


    Once the phase 3 trials are finished, then a control group isn't necessary, there are other ways of gathering the needed data, it's not quite as accurate, but it doesn't need to be at that stage (and yes, they continue to monitor the vaccinated group even after the phase 3 trial is finished, but the control group is free to do whatever they want at that stage).

    Medicine effectiveness is calculated with a confidence interval that is published with the date, the confidence interval grow larger when a control group isn't involved but there are other techniques used to keep it statistically significant.



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    Yes I agree - but the phase 3 trials have not finished. And they wont finish - since the control groups used in those trials have since been vaccinated.

    It's a total breach in protocol for conducting such studies - and casts doubt over the long term efficacy of these vaccines. They may be over or under estimated.



  • Registered Users Posts: 216 ✭✭ohnohedidnt


    The Israeli government are saying protection against infection is as low as 16% for people who received a 2nd dose in January, the methodology for collecting that data isn't clear, but I'm not sure why they would lie.

    The oxford study which nobody has really managed to find a fault with, says about 50% effective after 4 months, starting from 92% and extrapolating out from Jan to August, makes the Israeli estimates seem reasonable to me

    www.ft.com/content/23cdbf8c-b5ef-4596-bb46-f510606ab556



  • Registered Users Posts: 5,376 ✭✭✭brickster69


    The thing is with Israel is that now they have given 3 rd shots to those who got jabbed first so no more data will be coming from them now. UK wont have much more data for a while either because they gave second doses 3 months later, so that is no use to most countries to see what is going on in real time.

    All roads lead to Rome.



  • Registered Users Posts: 435 ✭✭godzilla1989


    Israel data is as legit as it comes.

    Pfizer and Israel are in partnership, 10 million people injected, electronic medical records.

    The CEO of Pfizer had an interview yesterday talking about Israel and the relationshop with them, 6mins in on this video.

    CEO says they are developing a Delta specific vaccine which they hope won't be needed, but boosters of the same vaccine will be needed.

    He seems confused, as in the interview video below he thinks there will be no need for a delta vaccine, but then says in another interview a vaccine resistant strain is very likely

    https://www.insider.com/pfizer-ceo-vaccine-resistant-coronavius-variant-likely-2021-8

    A pre print paper released few days ago suggests we are 4 mutations away from a vaccine resistant strain eg Delta 4+

    https://www.biorxiv.org/content/10.1101/2021.08.22.457114v1

    "Surprisingly, most BNT162b2-immune sera enhanced infectivity of the Delta 4+ pseudovirus in a dose-dependent manner at relatively low concentrations of BNT162b2-immune sera, but showed weak neutralization only at the highest concentration of the sera."

    9 of the 12 antibodies they tested didn't really seem to bind at all and two of the other 3 were at like 40% of Delta binding (figure 6a). In the neutralization assay, only one antibody had any neutralization at dilutions less than 1:10, compared to all 20 tested against Delta (figure 6d and 2a).

    Another recent paper where the authors serially passaged the virus through diluted convalescent plasma shows that only three mutations were enough to abrogate neutralization by about 70% (E484K + a NTD deletion + a NTD insertion)

    So it seems to me anyway that vaccine resitant strains, boosters, new variant vaccine's will be big news this winter





  • Registered Users Posts: 5,376 ✭✭✭brickster69


    The main concern will be that Israel are wrong with waning in severe illness among those who got jabbed early. All over the UK media today, amazing how slow they are when all of this was made public 6 weeks ago.



    All roads lead to Rome.



  • Registered Users Posts: 13,980 ✭✭✭✭Cuddlesworth


    Yeah I read it. Its convoluted enough some people would be convinced his assumptions are correct. And I've already pointed out where his assumption and the example given differ. Now he can go off to find something else to prove his own confirmation bias correct.



  • Registered Users Posts: 16,456 ✭✭✭✭astrofool


    The phase 3 trials are finished, the ongoing monitoring of the vaccinated group does not need a control group, sorry to bang on, but it's an anti-vax "talking point" to say that the "phase 3 trials aren't even finished yet" and is completely not true, once the results are in and once approval has been granted, phase 3 essentially becomes ongoing monitoring without control and is common with all medicines.

    Monitoring future efficacy does not require a control group.



  • Registered Users Posts: 6,796 ✭✭✭timmyntc


    The Phase 3 clinical trial of BNT162b2 began on July 27 and has enrolled 43,661 participants to date, 41,135 of whom have received a second dose of the vaccine candidate as of November 13, 2020. Approximately 42% of global participants and 30% of U.S. participants have racially and ethnically diverse backgrounds, and 41% of global and 45% of U.S. participants are 56-85 years of age. A breakdown of the diversity of clinical trial participants can be found here from approximately 150 clinical trials sites in United States, Germany, Turkey, South Africa, Brazil and Argentina. The trial will continue to collect efficacy and safety data in participants for an additional two years.

    Within 6 months of the phase 3 trials beginning, the majority of participants ended up double doses - including people in the control group.

    Phase 3 trials typically last between 1 and 4 years - Pfizer indicate in the above press release (Nov 2020) that they intend to continue the trial for a further 2 years. But yet theyve already vaccinated the majority of their control group!



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  • Registered Users Posts: 16,456 ✭✭✭✭astrofool


    I've explained why that is multiple times, but sure, continue to ignore.

    "The trial will continue to collect efficacy and safety data in participants for an additional two years"

    I hate to break it to you, but in 2 years time, they'll commission a further extension and further study (if COVID is still a thing to be worried about).

    I started in a trial 11 years ago that still sends updates, the conclusion was reached and published long ago, yet I still receive follow ups asking for information, no control group was kept after the initial trial period.



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