Instigator / Pro
21
1511
rating
25
debates
68.0%
won
Topic
#4378

We have learned that the COVID Vaccines do more harm then good.

Status
Finished

The debate is finished. The distribution of the voting points and the winner are presented below.

Winner & statistics
Better arguments
9
6
Better sources
6
8
Better legibility
3
5
Better conduct
3
3

After 5 votes and with 1 point ahead, the winner is...

Sir.Lancelot
Parameters
Publication date
Last updated date
Type
Rated
Number of rounds
5
Time for argument
One week
Max argument characters
30,000
Voting period
Two months
Point system
Multiple criterions
Voting system
Open
Minimal rating
None
Contender / Con
22
1587
rating
182
debates
55.77%
won
Description

COVID Vaccines, means Pfizer, Moderna, J&J, and AZ.
Harm refers to any negative impact that vaccinations have on individuals or the broader community.
Good refers to positive outcomes or benefits that can result from a particular action or behaviour.

More Harm than Good is admittedly subjective, so the BOP is on both parties to show through the balance of probabilities, their respective position.

Round 1
Pro
#1
PurposeThis is not a discussion of semantics, and any Kritiks of the resolution are welcomed without reservation, the essence of the debate is clear, and the BOP does not change.  Any reference to the word vaccines mean those as defined.

Harm versus Good, would also logically mean that the achieved outcome of good, outweighs the harm.  I used the term "learned" very specifically, as my position is that information has been obtained, post COVID vaccine programmes being initiated.    The question of what should have happened prior, is a subject for another debate, that I am sure will come up.

Whiteflame brought up a valid warning in the comments, about the risk of this being too long and erratic.  I accept that warning, and will limit my arguments in each rounds, if Con agrees to do the same.  If Con does not agree, that is fine as well, I will make up any lost arguments from Round 1 later on, because we have a big fat character limit :).  I assure that I will not bring up any new arguments in the final round.  I also have no problem jointly cutting this short.

The expression balance of probabilities is a 50%+ standard.  It is used in civil cases, versus a preponderance of the evidence which is criminal.  (Source) So both sides may make great arguments, but which one wins, even by the slightest degree,

Ok so lets get into it:

 Purpose:

I am confident that the we can agree that the purpose of the vaccination program was to reduce death, significant illness, and hospital admissions directly caused by the SARS-COVID-19 virus (inclusive of any variants).  Therein it would be fair to say that if the vaccine caused more hospitalizations than it prevented, the purpose was unsuccessful.

UK:

There are many regions to look at, and data is not tracked at a national level in a harmonious or contiguous way.  I have decided (in this round), to focus on UK data, and a couple key indicators there.  The ONS (Office of National Statistics) in the UK tracks, assembles, and publishes data related to many aspects of UK life. There are some other good UK data souces to use.

So my argument is that the total number of people you need to vaccinate in order to prevent a hospitalization ,or a serious hospitalization, is far lower than injuries attributed to the vaccine, and therefore the benefit is lost to the harm cause.  I am going to use UK data, and the trial data from Pfizer and Moderna, to demonstrate this.  We are not talking marginal numbers.   I reserve other discussion points for future rounds, should they be needed. With respect, I am taking a sniper approach here.  

Lets set a benchmark of what harm can be caused by the vaccines.   The Brighton Collaboration, has over 20 years of experience in researching vaccine safety. They set a benchmark for categorizing vaccine injuries for COVID vaccines.  This was assembled based manufacturers data, as well as other studies.  Most importantly is to look at the definition of a Serious Adverse Event (SAE).   As referenced here, both Pfizer and Moderna use the same definition.

An SAE was defined as an adverse event that results in any of the following conditions: death; life-threatening at the time of the event; inpatient hospitalization or prolongation of existing hospitalization; persistent or significant disability/incapacity; a congenital anomaly/birth defect; medically important event, based on medical judgment.
That above study shoes that in the Moderna trial, the SAE rate was 15.1 per 10,000 participants, which is 1 in 662(over placebo baselines).  The same document shows that the Pfizer trial has an SAE rate as 1 in 990(over placebo baselines)Combined, the SAE rate is 1 in 800(over placebo baselines)

That equates to about 1,250 serious events for each million vaccine recipients. or 1 in 800 having a serious adverse event as defined.  For Con to prove their case, they need to demonstrate that the vaccine(s) provided better results, even if it by a fraction of a percent.  That being whilst  statistically 1 in 800 people who got the injections, may have an SAE, 1.001 in 800 did not suffer the same impact from COVID-19, specifically as defined by the SAE. 

UK DATA RESULTS

The UK Health Security Agency (UKHSA) presentation tothe Joint Committee on Vaccination and Immunisation (JCVI) on 25October 2022, published in January of this year, outlines the "...estimation of numberneeded to vaccinate to prevent aCOVID-19 hospitalisation..."

I shall summarize.   The calculation of numbers needed to vaccinate (NNV)Table 3: NNV for prevention of hospitalisation for different programmes:  The first number is how many get hospitalized, i.e. how many vaccines to prevent a hospitalisation.  The second number (in parenthesis, see what I did there :) ). Is the number required to be vaccinated for that age group to prevent a serious hospital admission, which includes the adminstration of oxygen.  Yes if you need oxygen, you are in the second number.  So here are the numbers.  Remember we are talking a baseline of 1 in 800 having an SAE to the vaccines, as established above.

  • 20 - 29 Years, No risk group,   1 in  169,200, or ( 1 in 706,500)
  • 20 - 29 Years, In a risk group, 1 in  7,500, or (1 in 59,500)
  • 50 - 59 Years, No risk group, 1 in 43,600, or  (1 in 256,400)
  • 50 - 59 Years, In a risk group, 1 in 3,100, or (1 in 18,600)
  • 60 – 69 years, 1 in 3,600, or (1 in 27,300)
  • 70 + 1 in 800, or  (1 in 7,500)
Conclusion, RD 1

I have demonstrated that the SAE for vaccines is 1 in 800.  I have also demonstrated that the number of people needed to be vaccinated to prevent a hospital stay that does require oxygen, is as low as 1 in 7500.    That is nearly a 10:1 difference.

There is a 10:1 higher change of you ending up in hospital with the COVID vaccine, then with COVID alone.  Therefore, we have learned that the vaccine does more harm than good.


Con
#2
Typo Correction: This is not a Kritik, but just to clarify to voters. The resolution is Covid Vaccines do more harm than good.

I am not deterred by the character limit. There is a week of response time, so if Pro wishes to flood the debate with 30,000 words, I am more than happy to read and respond. 

There is, however, one major flaw with Pro's case. There is no proof that the rate of hospitalizations is caused by the vaccinations, even despite the results that this study was examining. If the study cannot directly link the hospitalizations as being an effect from the vaccines, then this means Pro's claim remains unsubstantiated.
Assertions made without evidence can be dismissed without evidence.

My case demonstrates that Pro's case is false, either way. As in the gap between hospitalizations has decreased significantly with the vaccinated, compared to those who remain unvaccinated. Let's compare.:

Age group      Rate per 100,000 among unvaccinated individuals      Rate per 100,000 among those who received at least one booster dose.
12 - 34               11.3                                                                                                          1.7
35 - 64               31.8                                                                                                          4.3
65+                     220.2                                                                                                       78.2


With this data, it is important to keep three things in mind.:
  1. Hospitalizations decreased with vaccinations.
  2. Less deaths occurred amongst the vaccinated demographic.
  3. Less vaccinated people got sick or infected.
As the resolution states, "We have learned that the Covid Vaccine does more harm than good," it is unclear exactly what Pro means by 'we.'
But in either interpretation, the BOP seems to favor Con because the majority of medical professionals agree that the Covid vaccines are necessary and while many people are taking a strong stance against Covid vaccines, the majority of people still believe it is a good thing. Showing that the people have internalized its benefits, on balance, as doing more good than harm.
Most Americans continue to support vaccine mandates — and want more
Microplastic pollution lingers in rivers for years before entering oceans - Northwestern Now (Despite the misleading title, the website the link directs people to is about the support for the Covid vaccine.)
Vote Con.
Round 2
Pro
#3
The Basics:
I want to reiterate the principals of harm as it relates to this discussion:

Is the risk of harm higher to someone with a vaccination, then without one.  This is not about if the vaccines work against COVID.  This is not a comparison of hospitalization rates of vaccine versus unvaccinated for COVID related illness.  This is about the potential benefits that are provided by the vaccines are now known to be worse than the negative effects.

Con has not negated, refuted or countered my UK data source, which clearly outline the total number needed to vaccinate,  called NNV.    NNV is a known statistical measure for assessing vaccine efficacy.    The data is very clear.   The number of either hospital or serious hospital infections that could be mitigated through broad vaccination strategy is very very low.  Con would need to show the the NNV modeling is flawed, or not an effective mechanism for measuring vaccine efficacy.

Unless otherwise argued, the baselines on the NNV stats for the UK I presented in Round 1, are an effective tool for mitigating hospitalizations for COVID. What you will see is that no matter what type of statistical game, or poor datasource argument one makes, the numbers are so disproportionate, clearly demonstrating that the harm is worse than the good. 

Con's Study:
Con provided a document from the Washington State Department of Health.  The document purport to support that vaccines reduce hospitalizations, for COVID illnesses.   Lets be clear.  This document only talks about the benefits of the vaccines with respect to the viral disease.  It does not address the known harms, the things we have learned.   This report is telling because it says a few things.   While the report does states that "Interpreting the data is challenging", the report highlights another key element with COVID as a whole, and that being the overall age related death risk demographic of COVID 

Deaths are only shown for Washingtonians ages 35 years and older due to the relatively small number of deaths in other age groups and associated instability in rates when assessing by vaccination status.
Con's study, shows that in certain data acquisition models, that a correlation between reduced hospitalizations and vaccine uptake is supported. For argument sake, I will concede that in certain circumstances the vaccine can have a benefit.  I also understand that people support the vaccines.  Again non-of this is part of the debate.  The debate is that we have learned the vaccines do more harm than good.  It is irrelevent if they do good.  What is the measure is if the harm outweighs the benefit.

Just to counter it, here is the official UK data for all of 2022 HERE, and previous data.  Here is a graph a friend of mine put together from that raw data.  It shows a stunningly higher COVID death rate among the vaccinated versus the unvaccinated.   All UK Government Data.

What Con Has Not Addressed:
Con has not addressed the harms known to be caused by the vaccines at all.  My opening argument was showing the clear NNV rates to prevent a hospitalization or a serious hospitalization.  It also showed the injury rates that case a SAE (Serious Adverse Event).   The study I showed is from a world renowned vaccine safety monitoring group.  Con inferred that there is no hospitalization support for the statistic presented.   I clearly did not articulate the foundation for COVID related vaccine injury rates.    I shall break it down with further evidence of the harms. 

Stamp Out Covid:
Something that was theorized early on, and turned out to be true, was the principal of negative efficacy.  The more COVID shots you have, the higher your chance of contracting COVID.  

The Cleveland Study showed a clear pattern.  Your probability of contracting symptomatic COVID is higher based on the number of vaccine shots you receive.  Check out the Figure 1 and Figure 2 graphs.

This UK Government Report. Page 45 shows that the more shots you have, the higher you hospitalization rate for COVID is.    You cant make this stuff up.  

The vaccines do not, and never were designed to prevent transmission, and the more you get vaccinated, the more you can catch it, the more you catch it, the higher chance you have of being in the hospital, not withstanding your increasing chance at a serious adverse event from one of the injections. So we now know the concept of the vaccination program is ineffective.

Switzerland has stopped recommending the vaccine across all age and risk groups   
Western Australia. Locked their state down for nearly 700 days.  Most people got vaccinated before they got exposed to the virus in WA.  However it had no effect on COVID mortality,  or hospital pressure.  In fact they Australian date for adverse events, showed significant concern.

Vaccine Injuries - Pfizer data:
I am going to start by looking at the Pfizer data, specifically the internal documents that were released subject to a Federal Law Suit.  This supports the position that the harm was learned after the fact, because Pfizer wanted to keep these records secret for 75 years.  I am going to be using this Pfizer report here

Table 1, on page 7 gives a fascinating view.  Relevant cases means patients, and adverse events, means symptoms related to an adverse event.  Each active case had on average 3 different adverse events.   This table shows there were 42,086 patients containing a whopping 158,893 adverse events.

23% or 9,400 cases list an Unknown outcome.  It gets worse: 46.5% or 19,582 cases Recovered/Recovering were mixed together.  The most revealing number of cases was The most revealing number of cases was 1,223 [2.91%], patients with ‘Fatal’ outcomes.  The poor tracking, categorization and deliberate failure to include a cardiac related category, made finding some of the now known side effects harder to find.

This is from Pfizers own study data.  So their data supports that there are i fact issues.  Page 8 of the report shows about 50k of those events are considered "Serious" per the definition I outlined above.  

394 total cardiac related cases from Pfizers own data that included the following.
Arrhythmia: 102 cases
Myocardial infarction: 89 cases
Acute myocardial infarction: 41 cases
Cardiac failure: 80 cases
Acute cardiac failure: 11 cases
Cariogenic shock: 7 cases
Orthostatic tachycardia syndrome:
7 Pericarditis: 32 cases

There are many other type os SAE that I may refer to later if required.

MYOCARDITIS
  • 5x Myocarditis in Nordic Countries - BMJ
  • Thailand prospective study saw abnormal cardiac finding rates of 1 - 29 for boys and 1 in 16 for girls
  • Seattle, 35 cases of Myocarditis following a vaccine in Children.   

Vaccine Injuries - VAERS, etc:
VAERS, is the Vaccine Adverse Events Reporting System, a US system to report vaccine adverse events.   While this can be done by anyone, it is incredibly complex, takes over 40 minutes, and requires substantial medical knowledge. Every  report is then vetted, and deleted if it is incomplete, or inaccurate. 

The Yellow Card Scheme is the UK version of VAERS, and has a simpler interface.  The Western Australian version is WAVSS

But just check out the graphs.  Clearly there is a problem, and it is similar for each three.

VAERSWestern Australia (check the graphs lower in the article.

Summary
  • I have established that the NNV rates show a very high number of people need to be vaccinated to prevent a single hospitalization from COVID-19
  • I have demonstrated that the more vaccinations you get, the higher your chance of getting COVID is.
  • I have demonstrated that hospitalizations for vaccinated with COVID exceed those unvaccinated, contrary to Con's
  • I have demonstrated that Pfizers own data, showed significant adverse events, and that is data we learned after the EUA was granted
  • I have demonstrated that there are numerous studies around the world that show marked adverse events, such as myocarditis. 
  • I have demonstrated the the overall SAE rate is about 1 in 800.  So for clarity, statistically speaking, if 800 people got a jab, one will have a serious adverse event requiring hospitalization.   
in the 50-59 year old, HIGH RISK group, the NNV is 1:3600.   So you have a 4.5x chance of ending up in the hospital after getting the jab then you do with getting COVID.  And remember more COVID vaccines, more COVID, more COVID, more chance of being hospitalized.

I have therefore shown that we have learned that the COVID vaccines do more harm than good. 


Con
#4
Forfeited
Round 3
Pro
#5
Whilst i have much more to say about this topic, I shall extend my previous arguments and give SL an opportunity to catch up.
Con
#6
Apologies for the forfeit. 

Pro’s own statistics seem to contradict each other. 

Extend.
Round 4
Pro
#7
It is easy to get lost in the weeds here, and I am not sure what the contradiction  Con has referred to, as it was not highlight.   I will nat add any new information here, just clarify what I have said, out of courtesy to Con.  I would ask that Con allow me to rebut any new information that is provided in their response, in the final round. 

I have demonstrated:

1. More COVID vaccines, equals a higher chance of catching COVID. (Cleveland Study as one example)
2. More hospitalizations occur from the COVID vaccine than the COVID virus

Reminders:
  • SAE = Serious Adverse Event.    This means a response to a vaccine that results in death; life-threatening at the time of the event; inpatient hospitalization or prolongation of existing hospitalization; persistent or significant disability/incapacity; a congenital anomaly/birth defect; medically important event, based on medical judgment.  
  • NNV = Number Needed To Vaccinate.   This is a well established epidemiological statistic that explains how many people need to be vaccinated to prevent a pathogen response.  In this case we are looking at a hospitalization visits, AND hospitalization visits requiring oxygen.
  • VAERS, is the Vaccine Adverse Events Reporting System, a US system to report vaccine adverse events.
I have given many stats, that all show a much higher hospitalization rates for vaccine recipients versus COVID infections.

Based on the efficacy of the vaccines, particular Pfizer as I reference their data, the statistics show that in order to prevent ONE Healthy 50-59 Year old from just going to the hospital because of COVID, you need to vaccinate  43,600 people in that age group.  If you want to prevent that same person from needing oxygen in that hospital stay, you would need to vaccinate 256,400 people.   A quarter of a million healthy 50-59/yo to prevent ONE from needing oxygen.

Out of the 256,400 who prevented ONE serious hospital stay for COVID,   320 would end up with a Serious Adverse Event.   That is based on the 1:800 serious adverse event statistics from Pfizers own data.

So you prevent 1 hospitalization by causing 320

If you look at the VAERS data, and the Western Australian Data, you will see significant similarities.  Massive spikes in claims.  

Con cannot dispute Pfizers own data.  Con cannot dispute the authority of the UK, Swiss, and Australian public data.  Con can argue that the VAERS data may not be perfectly reliable, but cannot claim it is useless, as I pointed out above the difficulty in submitting, and the qualifying the FDA does on the submitted reports.

On the hole, I have shown the vaccines do more aggregate harm than good.
Con
#8
Firstly, Vaccine Efficacy.:

If we look at the four COVID-19 vaccines approved in Canada, their efficacy was shown to be much higher than anticipated. For Pfizer-BioNTech’s mRNA-based vaccine, its efficacy clocked in at 95%. This does not mean that 95% of people are protected from disease with the vaccine, which would imply that 5% are not and will go on to contract COVID-19. Rather, it means that in the trial there was a 95% reduction from the number of COVID-19 cases you would expect if they had not been vaccinated. So in a group of unvaccinated people in which 100 get COVID-19, 95 of these infections would have been prevented had the group been vaccinated. That’s what efficacy means.
Moderna’s mRNA vaccine performed similarly well, withan efficacy of 94.1%. AstraZeneca/COVISHIELD’s vaccine, which uses a harmless virus to deliver the DNA to make the coronavirus’ spike protein, was said to have an efficacy of 76% at reducing the risk of symptomatic COVID-19. 
Extend #’s and statistics of net positive amount succeeding the total harm. 


Round 5
Pro
#9
I have shown that the chances of being hospitalized with the vaccine is higher than without.  Those stats are clearly shown.  Those stats have not been refuted by Con.   

Con tries to argue that effectiveness means safe.  Cutting off your foot is a very effectiveness to treat a blisters on your heal.  However it causes more harm than good.  In reality, the same data that Con is referencing, shows that there is a 1 in 800 risk of a Serious Adverse Event when you receive that vaccine.  

  • Con would have needed to show that the vaccine prevents more hospital illness or death, and have not done so.
  • Con have not refuted the statistic I have shown from the UK, Australia and from Pfizers own data.
  • Con did not demonstrate any sort of factual, or interpretive problem with the data presented.

I have shown, without refutation, that we have learned the Covid vaccines do more harm than good.

Vote Pro.
Con
#10
Forfeited