Public Health Lessons Learned From Biases in Coronavirus Mortality Estimation.

I found this interesting piece in the Cambridge University Press. It is from August 2020.

www.cambridge.org... rus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9#

try this link

In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.

They make the comparison between confusion surrounding the difference between CFR and IFR to the failed NASA Mars Climate rover, which i am sure most on this site know was lost because sometimes even experts make mistakes. Here are a couple more quotes...

Also in early May, 2020, a New York State survey of 1269 COVID-19 patients recently admitted to 113 hospitals found that most of the patients had been following shelter-in-place orders for 6 wk, which raised state officials’ suspicions about social distancing effectiveness. Still, polls showed the public credited social distancing and other mitigation measures for reducing predicted COVID-19 deaths, and for keeping people safe from the coronavirus.

So basically people were scared from the insane mortality estimates and once they did not pan out, attributed it to masks and social distancing instead of just...experts being mistaken which is clearly what happened.

CFRs and IFRs represent different segments of a targeted population and contain widely different proportions of nonfatal infections; therefore, misapplying findings or generalizing inferences between these 2 groups can cause a type of selection bias known as sampling bias or ascertainment bias. In this type of bias, people do not represent segments of the population to whom findings apply. Furthermore, “…comparisons of the CFR of 1 disease with the IFR of another are mostly useless,”  and sampling bias can lead to serious inaccuracies, as when Congress was informed that the coronavirus is 10-times more lethal than seasonal influenza.

A comparison of coronavirus and seasonal influenza CFRs may have been intended during Congressional testimony, but due to misclassifying an IFR as a CFR, the comparison turned out to be between an adjusted coronavirus CFR of 1% and an influenza IFR of 0.1%. Had the adjusted coronavirus mortality rate not been lowered from 3% to 1%, fatality comparisons of the coronavirus to the IFR of seasonal influenza would have increased from 10-times higher to 20- to 30-times higher. By then, epidemiologists might have been alerted to the possibility of a miscalculation in such an alarming estimation.

Just some food for thought.

a reply to: Chalcedony

I don't know how to make the link short enough to work. The title of this article is the same as the title of my post.

a reply to: Chalcedony

Wow. A nonsensical post about forced vasectomies has 20+ pages of comments but not one comment on this piece of actual information. Maybe ATS isn't the right place for me. Gosh I was hoping for some conversation about this. I find it really interesting.

originally posted by: Chalcedony
a reply to: Chalcedony

Wow girl. A nonsensical post about forced vasectomies has 20+ pages of comments but not one comment on this piece of actual information. Maybe ATS isn't the right place for me. Gosh I was hoping for some conversation about this. I find it really interesting.

Oh, I'm sure it's been read plenty of times by now. This is my second read-thru of your OP, but since this is backing up common sense observations, I figured it was more worthwhile to let the examination of the testimony to congress stand on it's own.


And the fact that zero resident fear-mongerers came in in ALL these hours to dispute this, is far more telling than a lack of posts from us like-minded. 5 hours and no attempts, it must be akin to deer-in-headlights

originally posted by: Chalcedony
I found this interesting piece in the Cambridge University Press. It is from August 2020.

www.cambridge.org... rus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9#

try this link

In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.

They make the comparison between confusion surrounding the difference between CFR and IFR to the failed NASA Mars Climate rover, which i am sure most on this site know was lost because sometimes even experts make mistakes. Here are a couple more quotes...

Also in early May, 2020, a New York State survey of 1269 COVID-19 patients recently admitted to 113 hospitals found that most of the patients had been following shelter-in-place orders for 6 wk, which raised state officials’ suspicions about social distancing effectiveness. Still, polls showed the public credited social distancing and other mitigation measures for reducing predicted COVID-19 deaths, and for keeping people safe from the coronavirus.

So basically people were scared from the insane mortality estimates and once they did not pan out, attributed it to masks and social distancing instead of just...experts being mistaken which is clearly what happened.

CFRs and IFRs represent different segments of a targeted population and contain widely different proportions of nonfatal infections; therefore, misapplying findings or generalizing inferences between these 2 groups can cause a type of selection bias known as sampling bias or ascertainment bias. In this type of bias, people do not represent segments of the population to whom findings apply. Furthermore, “…comparisons of the CFR of 1 disease with the IFR of another are mostly useless,”  and sampling bias can lead to serious inaccuracies, as when Congress was informed that the coronavirus is 10-times more lethal than seasonal influenza.

A comparison of coronavirus and seasonal influenza CFRs may have been intended during Congressional testimony, but due to misclassifying an IFR as a CFR, the comparison turned out to be between an adjusted coronavirus CFR of 1% and an influenza IFR of 0.1%. Had the adjusted coronavirus mortality rate not been lowered from 3% to 1%, fatality comparisons of the coronavirus to the IFR of seasonal influenza would have increased from 10-times higher to 20- to 30-times higher. By then, epidemiologists might have been alerted to the possibility of a miscalculation in such an alarming estimation.

Just some food for thought.

I often look first at simple impcompetence before I assume the conspiracy theory for something is correct. Now I will include bias confirmation errors before nefarious agendas also.

Thanks for the thought!

a reply to: Chalcedony

In the USA, half a million are dead of COVID-19, in the first year.

Similar rates of death have been seen around the world.

Can you argue that the numbers of dead are the result of bias on part of those who count the dead?

Of course, similar arguments have been used to assert that the holocaust was an exaggeration, and it was all just political bias and propaganda.

The fact is, that large numbers of people have been working to collate the data and present a true picture of what is happening. Those people aren't working for big pharma, or other vested interest, they are clerical workers, and would gain no advantage from lying.