Moral Theology Texts

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JMJ

Caveat: This is a long and someone convoluted post.  It was originally my original 'part 3' but I realized that as I did the deep data dive, it became way too long and wrote the shorter part 3 that is currently posted.  I didn't want to lose all the work I did, so I've cleaned it up a bit and posted more as a draft copy for the record. 

Introduction

 This part of the series is by request of a reader who wanted to know more about how I assessed the safety and efficacy of the vaccines. Since it has been a number of months, I am going to walk through a redo assessment.

In our town's care home and assisted living facility all forty+ residents are immunized and there were no significant adverse reactions and no deaths that resulted.  However, a friend of ours witnessed some major adverse reactions and at least one that seems to result in death(btw: I found an adverse reaction that seem to match in Canada's databse). So while our experiences may differ, that just indicates that need to step back and look at the broader perspective. 

Can we trust the data?  

Before I get into the data, I have spoken with people who just don't trust the data or who trust YouTube personalities more than statisticians.  The reasons are varied, so I'm going to discuss the data I use, why and how far I will trust it.

Trial data is collected during is collected during the studies during which volunteers accept to be part of a test of a new vaccine.  These people are followed both during the study as well as afterwards.  There are criteria for the acceptance into the study and the study is designed to meet statistical significance while balancing the risk to the study participants.This data has to pass the scrutiny of experts both within the appropriate regulatory agency as well as the company experts.  If a significant adverse event occurs studies are halted to investigate the root cause prior to a decision being made to continue or terminate the study.

So based on my knowledge of the clinical trial process, the number of review stages and people involved, I am confident in the data provided from the trials.  

However, then there is the post-trial data that, by law, is collected after a pharmaceutical is approved for use in the general population.  For that reason as parents, we took a conservative approach and were somewhere between Early to Late Majority "adopters". For our eligible children and who had a need to be vaccinated we took a Late Majority approach.

In this manner any trends or risks not captured in the Phase 3 trials would surface during the surveillance phase. Thus enabling an informed decision on the risks vs benefits of being vaccinated.  This enabled us to assess the risks between the alternative vaccines.  Data on adverse events was particularly useful (link) in weighing the advantages / disadvantages for each vaccine type. Looking at this data, we decided that while the Moderna vaccine has a higher rate of adverse reactions, it has the lowest rate of serious adverse reactions.

Epidemiological Data about the progression of the disease through the population is collected by health care professionals (doctors) as they treat patients with a disease.

Testing results are likewise performed by trained personnel and public tests are usually performed by healthcare personnel.  I am aware that the test is susceptible to the garbage in / out. However, the test technology is very specific so false positives  negative are very rare. There is a possibility for false positives and I believe that is the reason for the multi-test protocol.

I trust the above data because it has the benefit of 'averaging' the outliers to provide a good representation of the situation for the majority of the sampled population.  As we try to examine smaller and smaller areas there will be a lot more variation. For example, some of our friends have had a greatly different experience with vaccinations and adverse events than we have.  Also a US friend of mine refers to the pandemic as a "nothing burger" because he has seen no significant impact amongst his friends and relations.  Whereas my family and relations have.  So at the provincial or national level, I am comfortable using the data and stats.  I am wary of using localized data where the sample size doesn't have the benefit of averaging the outliers.

I no longer trust the analysis of the various media outlets. I have found that all outlets in the spectrum (main stream, YouTubers, left / right) are presenting skewed perspectives of the data.  So if they cite a paper and I have time, I will read the paper.  Otherwise, I rely on the data that I can obtain from the sources noted above.

Lastly, no one has demonstrated systematic faults exist in the data provided by the Government of Canada.  Yep, I'm Canadian and not tracking US data that closely, but I suspect the same argument applies.   

There seems to be an infinite supply of FUD-Muckers (Muck Out Meaning link) who are simply saying they don't trust the Government (or pick your personality of choice) and try to instill Fear-Uncertainty-Doubt (link) in the data. In short they say: Don't trust them, trust ME! With 100% consistently, when I have fact-checked peer reviewed journal articles cited by the FUD-Muckers, I have found that they have either misquoted, misrepresented, or misunderstood the information. It can be very discouraging when I fact-check a person that I respect and find that they have made an error.

So, yes I do give credence to 'official' sources because of the reasons above. The question is what data do I use to assess safety and efficacy?

What data should we use?

It depends on the question we are trying to answer. To make a decision on safety we need mortality data and for efficacy we look for immune response data. A key component of this data is the context that allows you to understand how the data was collected, processed and the size of the population.

For vaccine safety and efficacy, I am looking for specific data points to help understand how the vaccine affects people both in the phase 3 trial study group, as well as the general population when a vaccine has been approved for use in the general population.

I also try to understand the limitations of the way the data is presented. For example, the WHO  VigiBase / VigiAccess (link) adverse reaction database needs to be understood in the context of what reactions could occur

What is VigiBase? VigiBase is the unique WHO global database of reported potential side effects of medicinal products. It contains more than 26 million reports dating back to 1968. The data in VigiBase are provided by the more than 140 members of the WHO PIDM, who share their data to support global pharmacovigilance. All Programme members that share data have their own rules and guidelines for when and how to report information about side effects and what to share with the programme through VigiBase. For example, one member may require that there is at least a probable link between the product and the reaction to warrant reporting to VigiBase, while another may share all events that have been observed within a certain period after the product was administered, whether a link is suspected or not. Understanding the variety of reporting practices used throughout the programme is vital when interpreting the data in VigiBase.

The same can be for the Canadian equivalent the Canada vigilance adverse reaction online database (link A) / (Search Page link B). Now this database provides more information on what happened and the person in question.

Data Sources

• Vaccine Monograph: This provides the summary level data for the adverse reactions noted during the clinical trials, especially the phase three trial where they are assessing both safety and efficacy.
• https://covid-vaccine.canada.ca/
• https://covid-vaccine.canada.ca/info/pdf/covid-19-vaccine-moderna-pm-en.pdf
• https://covid-vaccine.canada.ca/info/pdf/pfizer-biontech-covid-19-vaccine-pm1-en.pdf
•  Averse reaction databases: This allows us to compare the limited trials (~30,000 to ~ 50,000 participants)  with a much larger population.  The longer the vaccines are used the more the population.
• https://www.canada.ca/en/public-health/services/diseases/coronavirus-disease-covid-19/vaccines/safety-side-effects.html
•  https://cvp-pcv.hc-sc.gc.ca/arq-rei/index-eng.jsp
• Epidemiological data that allows us to understand the risk posed by the disease to the population as a whole and to the different demographic groups. I am usually concerned about how the disease impacts different age groups.
• https://health-infobase.canada.ca/covid-19/visual-data-gallery/
• https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html
  

Method

• Number of fatalities during the trial and serious adverse reactions. This includes Anaphylactic reactions as this is an acute immune response to an allergen. I exclude normal reactions such as commonly found in other vaccines, such as fever, muscle aches, fatigue; as these are to be expected.  These are represented as percentages which is useful for comparison.
  
• I look for comparable adverse reactions in the published data and check to see if there is a gross inconsistency. This provides a comparison of the trial data of tens of thousands, compared with millions.
  
•  I focus on data that is relevant to the processes and competencies in my country and region (if comparable numbers to the trial are available).
  

• I may expand to the US VAERS system for a larger comparison if needed.
  

Thoughts

•  The risks and benefit ratio needs to be assessed on a personal level as well as societal level.  The society includes our near-contacts (family and friends) as well as society as a whole.  The reason for this is that low case fatality rates are directly related to the level of care that can be provided. If intensive care units are full, then it creates a cascade effect throughout the medical system.
• The key risk factors to consider are age, health and any factors that would influence the risk rating. For example, having asthma increases the risk of complications with COVID-19.
  

What's missing? Context!

In assessing the vaccines for COVID-19 we need to know a little more about the disease. This is an important bit of context to make the risk vs benefit decision. In other words, the risk of getting COVID-19 vs the risk of getting the vaccine.

Looking at the data on infobase (link) we find the following stats for today (Oct 2, 2021) for cases, hospitalizations, ICU admissions and death. NB. I took the data and put in an a spreadsheet that I can analyse on my own.

First the data table:

	Age group (years
Class	0-19	20-29	30-39	40-49	50-59	60-69	70-79	80+
1. Case	326,370	313,526	269,131	232,971	202,356	125,339	65,575	75,039
2. Hospitalized	1,707	3,641	6,134	7,860	12,329	14,739	15,817	21,055
3. ICU	196	469	1,038	1,705	3,220	4,185	3,560	1,615
4. Deceased	17	73	173	390	1,097	2,749	5,659	17,502
Grand Total	328,290	317,709	276,476	242,926	219,002	147,012	90,611	115,211
Risk	0-19	20-29	30-39	40-49	50-59	60-69	70-79	80+
Hospital	0.52%	1.12%	1.88%	2.41%	3.78%	4.52%	4.85%	6.45%
ICU	0.06%	0.14%	0.32%	0.52%	0.99%	1.28%	1.09%	0.49%
Deceased	0.01%	0.02%	0.05%	0.12%	0.34%	0.84%	1.73%	5.36%

I added some quick "bulk"  stats to compare the risk of hospitalization for each case. So this breaks down the bulk risks for the whole population down to the individual age groups.  Unfortunately, we don't have the number recovered for each to do a proper comparison.

The Case Fatality Ration (CFR) is:

CFR = 27,660 /(27,660 + 1,556,530 ) *100 = 1.75%

This means that if you get a reportable case of  COVID-19, the bulk estimated fatality rate is 1.75%  Depending on your age, it would breakdown roughly as above. 

I pulled the data into a google sheets and created this combo chart to give us some perspective. The left access provides the number of cases and the right the number of people hospitalized, in ICU and deceased. 

The trend the pops out is the increased severity and impact for the older cohorts. With all of these metrics increasing with age (likelihood of hospitalization, being admitted into an ICU and finally, dying).

I know that the focus has been on dying, but being hospitalized tells us two things. First, that the case is bad enough that they have to have special care or risk downgrading to class #4 (death). Second, that about 5% need to be hospitalized.  Of these, from the people that I know, they have experienced some lingering effects due to damage to their lungs.  Time will tell if they develop chronic conditions. 

Then there are the limited ICU and hospital capacity.  One reason for our low fatality rate is the level of care that we can provide.  If the healthcare facility is overwhelmed, then the CFR will increase notably for the young and healthy.

Another factor to consider is the impact on those people around us.  If we have regular contact with people in the older cohorts, if we carry the disease to them, the effects would probably be worse that what you would experience. 

A final facet to consider is just how many people, based on these stats, would get sick? At the beginning of the pandemic it was estimated that about only 20% of cases manifested as needing hospitalization. Globally, the infection fatality ratio (IFR) has been estimated as between 0.5% and 1%.  This sounds like a small number without the population context.  In Canada the population is 38M.  That means that if everyone caught COVID-19 without the vaccine, you could expect between 190,000 to 380,000 people to die.  This  assumes that the healthcare system continues to function.

 

So that is the problem context.

So ... are the vaccines safe?

I provided my thoughts in part 3 of this series (link to come).

Efficacy

I have seen a big deal made of breakthrough infections, but when I looked at the stats showing the percentage of breakthroughs - there were well lower than the 5% expected efficacy as noted in the studies.  

There's also been some noise made about boosters - the article I read noted the decrease in immune response for those with compromised immune systems. This makes sense and is therefore a 'nothing burger'. 

One thing that Tradiate observed is that the vaccines doesn't create a force field. It preps your immune system to handle the virus without serious disease.  So yes, it is possible to spread it.  This isn't new to science even if it is new to the public.

Conclusion

The moral issue was my primary concern about the vaccines as I understand the process for developing the vaccines and trusted the system.  I am also pleased that we are able to choose which vaccine to receive and can therefore favour those that are both moral (mRNA) and safe.

Others will be coming out in the next 12 months that will offer similar benefits but based on different technology platforms.  

I hope that soon a completely untainted vaccine will be available.

P^3

Reference: Making Moral Vaccine Decisions Series

Tradicat Series: Making Moral Vaccine Decisions

 New Article Series: Making Moral Vaccine Decisions 

Making Moral Vaccine Decisions - Part A: Guiding Principles  

Making Moral Vaccine Decisions - Part B: Situation 

Making Moral Vaccine Decisions - Part C: Moral Issues 

Making Moral Vaccine Decisions - Part D: Vaccine Safety and Efficacy 

Making Moral Vaccine Decisions - Part E: Vaccines In Canada 

Making Moral Vaccine Decisions - Part F: Our Obligations 

Making Moral Vaccine Decisions - Part G: Conclusion and Resources 

Making Moral Vaccine Decisions - Part H: Responses to Comments by L Fischer --- Update A 

Making Moral Vaccine Decisions - Part i: Canadian Conference of Catholic Bishops 

Making Moral Vaccine Decisions - Part J: How to Vaccinate Like a Catholic

Moral Theology Texts

 

 Quick Note: I have found reports that pre-clinical (animal) trials were performed on non-human primates (monkeys) before the human trials were started (link). This is for the Pfizer vaccine and I am assuming that the others would have had some pre-clnical trial.  That the vaccine testing process was accelerated is a largely a parallelization of the clinical trial process. Instead of doing the trial, then sending the data to the regulators, the data was sent to the regs throughout the trial.  This alone cut off a large amount of time.