In this essay Dr. Rind counsels us on when to moderate our skepticism and recognize that our understanding of an illness or therapy might need to change
Our pediatrician said she always waits 6 months to see how a new drug or vaccine works before she recommends it. This gives time to see actual results rather than just test results. I think this is a good way of being skeptical but willing to try new treatments.
I really appreciated this article, thank you. I think we often get really accustomed to tagging flaws in any trial we read, especially when teaching, and it becomes as second-nature as reeling off familiar crossword answers: "apse", "rara avis", "immortal time bias", etc. It's good to be reminded that scouring a study for soft spots is not the same as invalidating it.
A very good dose of serious advice from David Rind. However, I do think that we should object firmly to the first sentence of the second paragraph: Note his chosen verbiage, ". . . .flaws that lead to the wrong answer". In biostatistical matters we actually never "uncover the right answer" and this startling point was made in a leading textbook some years ago by (I seem to recall) David Sackett (?) --- viz. in all applications of modern epidemiology sleuthing, including uses of even the most scrupulous RCTs, investigators will *always* get approximations of the Truth underlying some matter at hand. I think that epidemiologists sense reality through layers of fog, sometimes with greater difficulty than at other times, but never with 100.00 percent clarity despite strong applications of the most intense and au courant computational Kung Fu. In sum, I wish simply that Dr. Rind had said, ". . .focus on flaws that will lead the unwary to form misleading conclusions".
It doesn't seem convincing to make an argument against someone by calling them a name (i.e. contrarian). Nor by simply saying "those are facts". Would the Prasad you reference disagree with your second to last statement? I doubt so.
You are really going to try to defend the actions of public health "experts" during the past 3 years by citing masking and the disastrous vaccines. They have earned every bit of the enmity they receive. It is these "experts" that made indefensible decisions based not on science but on politics and/or tunnel vision to stop the virus. They ignored natural immunity, dramatically different risk by age or health status and the very real harms that the recommended/mandated interventions caused never once considering whether the collateral damage would be far more detrimental to the totality of public health. To make matters worse these same "experts" had the arrogance to censor, slander and ridicule those who dared ask the very questions that they should have considered. What has been proven is that these people should have never been "put in a position of having to make off the cuff decisions for entire populations...". Maybe the answer is no one should be in this position.
Your response uses the typical appeal to consensus (science is not based on consensus) and unsupported anecdotal emotional appeals. You fail to understand that there can both be a virus which causes real harms to certain portions of the population and a public health policy which ignores the collateral damage of interventions and past experience and science concerning respiratory viruses resulting in worse outcomes for the totality of public health. That you feel that you and your fellow "experts" should be "...put in a position of having to make off the cuff decisions for entire populations" is frightening. You and your peers refuse to honestly examine and learn from your failure but stand ready to make the same catastrophic decisions the next time we face a pandemic.
Just so I am prepared, what interventions do you think were effective and warrant reuse: mass mandated vaccination with an EUA vaccine of questionable effectiveness and safety, lockdowns, masks, etc. Please provide support for how these interventions benefits outweigh their harms.
You have perfectly illustrated one of the many problems with how public health policies were formulated and applied. You cite a model as proof of effectiveness and feel that is sufficient to justify the coerced vaccination of millions. Unfortunately, we live in the real world and have to deal with real consequences. What you linked to is nothing but a blog post about a model. It should surprise no one that if you formulate a model with the assumptions that the vaccine is effective the output of the model will show that the vaccines are effective. This does not make this true.
Below are some of the observations from a study of actual people using real data not made up assumptions in a model.
"The association of increased risk of COVID-19 with higher numbers of prior vaccine doses was unexpected."
"This is not the only study to find a possible association with more prior vaccine doses and higher risk of COVID-19. During an Omicron wave in Iceland, individuals who had previously received 2 or more doses were found to have a higher odds of reinfection than those who had received fewer than 2 doses of vaccine, in an unadjusted analysis [21]. A large study found, in an adjusted analysis, that those who had an Omicron variant infection after previously receiving three doses of vaccine had a higher risk of reinfection than those who had an Omicron variant infection after previously receiving two doses of vaccine [22]"
"Another study found, in multivariable analysis, that receipt of two or three doses of a mRNA vaccine following prior COVID-19 was associated with a higher risk of reinfection than receipt of a single dose [7]. Immune imprinting from prior exposure to different antigens in a prior vaccine [22,23], and class switch towards non-inflammatory spike-specific IgG4 antibodies after repeated SARS-CoV-2 mRNA vaccination [24], have been suggested as possible mechanisms by why prior vaccine may provide less protection than expected. We still have a lot to learn about protection from COVID-19 vaccination, and in addition to a vaccine’s effectiveness, it is important to examine whether multiple vaccine doses given over time may not be having the beneficial effect that is generally assumed."
Reading comprehension is not one of your strong suits. All the quotes and links are from the same peer-reviewed and published study linked in the comment. I have included the conclusion below given you seem to have had difficulty finding it.
"In conclusion, this study found an overall modest protective effect [29% BA.4/5, 20% BQ, and no effectiveness XBB] of the bivalent vaccine against COVID-19 while the circulating strains were represented in the vaccine and lower protection when the circulating strains were no longer represented. A significant protective effect was not found when the XBB lineages were dominant. The unexpected finding of increasing risk with increasing number of prior COVID-19 vaccine doses needs further study."
The author also addresses your excuses for the inconvenient data showing more vaccinations results in more incidents of Covid.
"A simplistic explanation might be that those who received more doses were more likely to be individuals at higher risk of COVID-19. A small proportion of individuals may have fit this description. However, the majority of subjects in this study were generally young individuals and all were eligible to have received at least 3 doses of vaccine by the study start date, and which they had every opportunity to do. Therefore, those who received fewer than 3 doses (46% of individuals in the study) were not those ineligible to receive the vaccine, but those who chose not to follow the CDC’s recommendations on remaining updated with COVID-19 vaccination, and one could reasonably expect these individuals to have been more likely to have exhibited higher risk-taking behavior. Despite this, their risk of acquiring COVID-19 was lower than those who received a larger number of prior vaccine doses. "
You then cite a completely unsupported anecdote about the level of vaccinated vs unvaccinated in the hospital and dying. The US data on this is problematic as it is collected inconsistently by many independent organizations using different standards.
The UK hospital system is government controlled therefore their data is consistently collected using the same standard. They collected and published good raw data biweekly through April or May of last year which shows in nearly all age groups the % of those hospitalized or dying of Covid who were unvaccinated does not exceed the % of the population that is unvaccinated at that time for any significant period of time. If what you assert were true, that the unvaccinated were hospitalized and dying at far greater rates, the % of those hospitalized or dying of Covid that were unvaccinated would exceed the % of the population that is unvaccinated by a material amount and this does not show up in the data. Do you believe that Covid would affect the English differently than those in the US?
You exposed yourself as a political ideologue and not a individual sincerely looking for truth when you decided to bring politicians into a discussion in which they have no relevance. Thanks for exposing yourself and saving me from wasting any more time with your nonsense.
Our pediatrician said she always waits 6 months to see how a new drug or vaccine works before she recommends it. This gives time to see actual results rather than just test results. I think this is a good way of being skeptical but willing to try new treatments.
It's good to know that people are willing to talk about skepticism. This is something we haven't had enough of in the last several years.
I really appreciated this article, thank you. I think we often get really accustomed to tagging flaws in any trial we read, especially when teaching, and it becomes as second-nature as reeling off familiar crossword answers: "apse", "rara avis", "immortal time bias", etc. It's good to be reminded that scouring a study for soft spots is not the same as invalidating it.
Having the self awareness to recognize one’s own biases is something every consumer of EBM should strive for.
This sentence really hit me: "We all have some degree of intellectual conflicts of interest – we all like to be right". I can certainly relate.
Probably one of the best ways to balance our own conflicts of interest is to ask others who disagree to engage with us.
A very good dose of serious advice from David Rind. However, I do think that we should object firmly to the first sentence of the second paragraph: Note his chosen verbiage, ". . . .flaws that lead to the wrong answer". In biostatistical matters we actually never "uncover the right answer" and this startling point was made in a leading textbook some years ago by (I seem to recall) David Sackett (?) --- viz. in all applications of modern epidemiology sleuthing, including uses of even the most scrupulous RCTs, investigators will *always* get approximations of the Truth underlying some matter at hand. I think that epidemiologists sense reality through layers of fog, sometimes with greater difficulty than at other times, but never with 100.00 percent clarity despite strong applications of the most intense and au courant computational Kung Fu. In sum, I wish simply that Dr. Rind had said, ". . .focus on flaws that will lead the unwary to form misleading conclusions".
It doesn't seem convincing to make an argument against someone by calling them a name (i.e. contrarian). Nor by simply saying "those are facts". Would the Prasad you reference disagree with your second to last statement? I doubt so.
You are really going to try to defend the actions of public health "experts" during the past 3 years by citing masking and the disastrous vaccines. They have earned every bit of the enmity they receive. It is these "experts" that made indefensible decisions based not on science but on politics and/or tunnel vision to stop the virus. They ignored natural immunity, dramatically different risk by age or health status and the very real harms that the recommended/mandated interventions caused never once considering whether the collateral damage would be far more detrimental to the totality of public health. To make matters worse these same "experts" had the arrogance to censor, slander and ridicule those who dared ask the very questions that they should have considered. What has been proven is that these people should have never been "put in a position of having to make off the cuff decisions for entire populations...". Maybe the answer is no one should be in this position.
Your response uses the typical appeal to consensus (science is not based on consensus) and unsupported anecdotal emotional appeals. You fail to understand that there can both be a virus which causes real harms to certain portions of the population and a public health policy which ignores the collateral damage of interventions and past experience and science concerning respiratory viruses resulting in worse outcomes for the totality of public health. That you feel that you and your fellow "experts" should be "...put in a position of having to make off the cuff decisions for entire populations" is frightening. You and your peers refuse to honestly examine and learn from your failure but stand ready to make the same catastrophic decisions the next time we face a pandemic.
Just so I am prepared, what interventions do you think were effective and warrant reuse: mass mandated vaccination with an EUA vaccine of questionable effectiveness and safety, lockdowns, masks, etc. Please provide support for how these interventions benefits outweigh their harms.
You have perfectly illustrated one of the many problems with how public health policies were formulated and applied. You cite a model as proof of effectiveness and feel that is sufficient to justify the coerced vaccination of millions. Unfortunately, we live in the real world and have to deal with real consequences. What you linked to is nothing but a blog post about a model. It should surprise no one that if you formulate a model with the assumptions that the vaccine is effective the output of the model will show that the vaccines are effective. This does not make this true.
Below are some of the observations from a study of actual people using real data not made up assumptions in a model.
"The association of increased risk of COVID-19 with higher numbers of prior vaccine doses was unexpected."
"This is not the only study to find a possible association with more prior vaccine doses and higher risk of COVID-19. During an Omicron wave in Iceland, individuals who had previously received 2 or more doses were found to have a higher odds of reinfection than those who had received fewer than 2 doses of vaccine, in an unadjusted analysis [21]. A large study found, in an adjusted analysis, that those who had an Omicron variant infection after previously receiving three doses of vaccine had a higher risk of reinfection than those who had an Omicron variant infection after previously receiving two doses of vaccine [22]"
"Another study found, in multivariable analysis, that receipt of two or three doses of a mRNA vaccine following prior COVID-19 was associated with a higher risk of reinfection than receipt of a single dose [7]. Immune imprinting from prior exposure to different antigens in a prior vaccine [22,23], and class switch towards non-inflammatory spike-specific IgG4 antibodies after repeated SARS-CoV-2 mRNA vaccination [24], have been suggested as possible mechanisms by why prior vaccine may provide less protection than expected. We still have a lot to learn about protection from COVID-19 vaccination, and in addition to a vaccine’s effectiveness, it is important to examine whether multiple vaccine doses given over time may not be having the beneficial effect that is generally assumed."
This chart shows the more doses of vaccine the greater the incidence of Covid-19. - https://www.medrxiv.org/content/medrxiv/early/2023/03/22/2022.12.17.22283625/F2.large.jpg?width=800&height=600&carousel=1
Full Study - https://www.medrxiv.org/content/10.1101/2022.12.17.22283625v5.full
Reading comprehension is not one of your strong suits. All the quotes and links are from the same peer-reviewed and published study linked in the comment. I have included the conclusion below given you seem to have had difficulty finding it.
"In conclusion, this study found an overall modest protective effect [29% BA.4/5, 20% BQ, and no effectiveness XBB] of the bivalent vaccine against COVID-19 while the circulating strains were represented in the vaccine and lower protection when the circulating strains were no longer represented. A significant protective effect was not found when the XBB lineages were dominant. The unexpected finding of increasing risk with increasing number of prior COVID-19 vaccine doses needs further study."
The author also addresses your excuses for the inconvenient data showing more vaccinations results in more incidents of Covid.
"A simplistic explanation might be that those who received more doses were more likely to be individuals at higher risk of COVID-19. A small proportion of individuals may have fit this description. However, the majority of subjects in this study were generally young individuals and all were eligible to have received at least 3 doses of vaccine by the study start date, and which they had every opportunity to do. Therefore, those who received fewer than 3 doses (46% of individuals in the study) were not those ineligible to receive the vaccine, but those who chose not to follow the CDC’s recommendations on remaining updated with COVID-19 vaccination, and one could reasonably expect these individuals to have been more likely to have exhibited higher risk-taking behavior. Despite this, their risk of acquiring COVID-19 was lower than those who received a larger number of prior vaccine doses. "
You then cite a completely unsupported anecdote about the level of vaccinated vs unvaccinated in the hospital and dying. The US data on this is problematic as it is collected inconsistently by many independent organizations using different standards.
The UK hospital system is government controlled therefore their data is consistently collected using the same standard. They collected and published good raw data biweekly through April or May of last year which shows in nearly all age groups the % of those hospitalized or dying of Covid who were unvaccinated does not exceed the % of the population that is unvaccinated at that time for any significant period of time. If what you assert were true, that the unvaccinated were hospitalized and dying at far greater rates, the % of those hospitalized or dying of Covid that were unvaccinated would exceed the % of the population that is unvaccinated by a material amount and this does not show up in the data. Do you believe that Covid would affect the English differently than those in the US?
You exposed yourself as a political ideologue and not a individual sincerely looking for truth when you decided to bring politicians into a discussion in which they have no relevance. Thanks for exposing yourself and saving me from wasting any more time with your nonsense.
Appreciate the space to broadly reflect on my own biases. Thank you.
Hear here!