[Treefence]

Disclaimer I'm not a statistician, but I do love analyzing numbers.  As we are noting there are a few studies out that support the idea that the infection hit many more people than we thought, but at the same time thus the mortality rate is much lower than we thought.  This all may be true, but one country I'd look at as a counter would be San Marino.  The country has a population of roughly 34,000, 476 confirmed cases, 40 deaths, and almost 54,000 test performed.  

I realize that I'm picking one country here, so it could be an outlier, or there could be an underlying reason why their mortality rate would be higher, but so far just short of 0.12% of their population has died due to COVID-19. They don't have that many cases listed in critical condition at this point, 4 on the site I'm using. Based on the confirmed cases and death number, they have a mortality rate of 8.4%. 

Based on the previously mentioned studies, the antibody testing would imply that more likely than the 8.4% mortality rate, is that almost the entire population of San Marino is infected, and given the micro country is located in Northern Italy, this could be true, however they have performed 54,000 tests, that's more than 1 per person.  It's likely that more sever patients were tested multiple times, but given they only have 476 confirmed cases, and tons of testing done, it seems unlikely that the entire population contracted the virus right?  

All numbers are taken from this site https://www.worldometers.info/coronavirus/
If anyone sees any brobdingnagian flaws in my logic, I'm happy to hear it, I'm honestly just trying to learn the most I can about all this.

[Treefence]

Disclaimer I'm not a statistician, but I do love analyzing numbers.  As we are noting there are a few studies out that support the idea that the infection hit many more people than we thought, but at the same time thus the mortality rate is much lower than we thought.  This all may be true, but one country I'd look at as a counter would be San Marino.  The country has a population of roughly 34,000, 476 confirmed cases, 40 deaths, and almost 54,000 test performed.  

I realize that I'm picking one country here, so it could be an outlier, or there could be an underlying reason why their mortality rate would be higher, but so far just short of 0.12% of their population has died due to COVID-19. They don't have that many cases listed in critical condition at this point, 4 on the site I'm using. Based on the confirmed cases and death number, they have a mortality rate of 8.4%. 

Based on the previously mentioned studies, the antibody testing would imply that more likely than the 8.4% mortality rate, is that almost the entire population of San Marino is infected, and given the micro country is located in Northern Italy, this could be true, however they have performed 54,000 tests, that's more than 1 per person.  It's likely that more sever patients were tested multiple times, but given they only have 476 confirmed cases, and tons of testing done, it seems unlikely that the entire population contracted the virus right?  

All numbers are taken from this site https://www.worldometers.info/coronavirus/
If anyone sees any brobdingnagian flaws in my logic, I'm happy to hear it, I'm honestly just trying to learn the most I can about all this.

[BostonCard]

Given the range of possibilities we have evidence to show could be facing society, with some of them being really, really catastrophic, it’s foolish to be making decisions without more known about the disease itself, and its implications for humanity.

OF, the obvious problem with waiting until more is known to make a decision IS a decision. We made the decision to "shelter in place" on information that was not perfect. I am pretty sure most all of us think that was a reasonable action. However, it is I think pretty clear that we can't wait two years gathering information in this present state (although you may feel otherwise).
Society often has to make decisions in the presence of great uncertainty. Sometimes there are no risk-free alternatives available. OTOH, many of the decisions humanity has made in the past based on what at the time was regarded as adequate information have had serious unanticipated negative consequences. In the case of COVID-19, I am certain that our nation, and almost all other nations of the world, will be making decisions in the next few months based on much less certainty than they prefer. Deciding to wait in the status quo is such a decision.

I agree wholeheartedly.  This is a very high stakes decision, both in terms of the health consequences and the economic ones.

BC

[BostonCard]

Given the range of possibilities we have evidence to show could be facing society, with some of them being really, really catastrophic, it’s foolish to be making decisions without more known about the disease itself, and its implications for humanity.

OF, the obvious problem with waiting until more is known to make a decision IS a decision. We made the decision to "shelter in place" on information that was not perfect. I am pretty sure most all of us think that was a reasonable action. However, it is I think pretty clear that we can't wait two years gathering information in this present state (although you may feel otherwise).
Society often has to make decisions in the presence of great uncertainty. Sometimes there are no risk-free alternatives available. OTOH, many of the decisions humanity has made in the past based on what at the time was regarded as adequate information have had serious unanticipated negative consequences. In the case of COVID-19, I am certain that our nation, and almost all other nations of the world, will be making decisions in the next few months based on much less certainty than they prefer. Deciding to wait in the status quo is such a decision.

I agree wholeheartedly.  This is a very high stakes decision, both in terms of the health consequences and the economic ones.

BC

[martyup]

Disclaimer I'm not a statistician, but I do love analyzing numbers.  As we are noting there are a few studies out that support the idea that the infection hit many more people than we thought, but at the same time thus the mortality rate is much lower than we thought.  This all may be true, but one country I'd look at as a counter would be San Marino.  The country has a population of roughly 34,000, 476 confirmed cases, 40 deaths, and almost 54,000 test performed.  

I realize that I'm picking one country here, so it could be an outlier, or there could be an underlying reason why their mortality rate would be higher, but so far just short of 0.12% of their population has died due to COVID-19. They don't have that many cases listed in critical condition at this point, 4 on the site I'm using. Based on the confirmed cases and death number, they have a mortality rate of 8.4%. 

Based on the previously mentioned studies, the antibody testing would imply that more likely than the 8.4% mortality rate, is that almost the entire population of San Marino is infected, and given the micro country is located in Northern Italy, this could be true, however they have performed 54,000 tests, that's more than 1 per person.  It's likely that more sever patients were tested multiple times, but given they only have 476 confirmed cases, and tons of testing done, it seems unlikely that the entire population contracted the virus right?  

All numbers are taken from this site https://www.worldometers.info/coronavirus/
If anyone sees any of immense proportions flaws in my logic, I'm happy to hear it, I'm honestly just trying to learn the most I can about all this.

Would love to see antibody tests of this population.

[martyup]

Disclaimer I'm not a statistician, but I do love analyzing numbers.  As we are noting there are a few studies out that support the idea that the infection hit many more people than we thought, but at the same time thus the mortality rate is much lower than we thought.  This all may be true, but one country I'd look at as a counter would be San Marino.  The country has a population of roughly 34,000, 476 confirmed cases, 40 deaths, and almost 54,000 test performed.  

I realize that I'm picking one country here, so it could be an outlier, or there could be an underlying reason why their mortality rate would be higher, but so far just short of 0.12% of their population has died due to COVID-19. They don't have that many cases listed in critical condition at this point, 4 on the site I'm using. Based on the confirmed cases and death number, they have a mortality rate of 8.4%. 

Based on the previously mentioned studies, the antibody testing would imply that more likely than the 8.4% mortality rate, is that almost the entire population of San Marino is infected, and given the micro country is located in Northern Italy, this could be true, however they have performed 54,000 tests, that's more than 1 per person.  It's likely that more sever patients were tested multiple times, but given they only have 476 confirmed cases, and tons of testing done, it seems unlikely that the entire population contracted the virus right?  

All numbers are taken from this site https://www.worldometers.info/coronavirus/
If anyone sees any of immense proportions flaws in my logic, I'm happy to hear it, I'm honestly just trying to learn the most I can about all this.

Would love to see antibody tests of this population.

[OutsiderFan]

I'll go along with whatever the expert consensus is. I'm just raising concern we are increasing our risk of something worse than we think we have now, by not asking enough questions, not getting enough answers, and making too many assumptions.

[OutsiderFan]

I'll go along with whatever the expert consensus is. I'm just raising concern we are increasing our risk of something worse than we think we have now, by not asking enough questions, not getting enough answers, and making too many assumptions.

[dabigv13]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

Unfortunately after what seemed like an initial dip, the patients in hospital, in ICUs, and on vents are all pretty stable over the past week, and perhaps ticking up over the last day. It may be that our current social distancing/lockdown may not have gotten R0 below 1 even if it was effective enough to prevent an NYC like surge.

[dabigv13]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

Unfortunately after what seemed like an initial dip, the patients in hospital, in ICUs, and on vents are all pretty stable over the past week, and perhaps ticking up over the last day. It may be that our current social distancing/lockdown may not have gotten R0 below 1 even if it was effective enough to prevent an NYC like surge.

[magnus]

Unfortunately after what seemed like an initial dip, the patients in hospital, in ICUs, and on vents are all pretty stable over the past week, and perhaps ticking up over the last day. It may be that our current social distancing/lockdown may not have gotten R0 below 1 even if it was effective enough to prevent an NYC like surge.

I saw a CNN headline that some NY state hospitals were getting the go ahead to start elective procedures again.  I have heard other hospitals around the country opening up their clinics.  How does it look in your area dabigv13?  Are things opening up again or are appointments still tightly controlled?  Hopefully these hospitals aren't cutting corners with PPE.

[magnus]

Unfortunately after what seemed like an initial dip, the patients in hospital, in ICUs, and on vents are all pretty stable over the past week, and perhaps ticking up over the last day. It may be that our current social distancing/lockdown may not have gotten R0 below 1 even if it was effective enough to prevent an NYC like surge.

I saw a CNN headline that some NY state hospitals were getting the go ahead to start elective procedures again.  I have heard other hospitals around the country opening up their clinics.  How does it look in your area dabigv13?  Are things opening up again or are appointments still tightly controlled?  Hopefully these hospitals aren't cutting corners with PPE.

[dabigv13]

We are starting to look at how we restart elective procedures, but for now they are still cancelled through mid-May. I don't anticipate that will be moved forward.

[dabigv13]

We are starting to look at how we restart elective procedures, but for now they are still cancelled through mid-May. I don't anticipate that will be moved forward.

[2006alum]

Excellent Merc article out today detailing the problems with the Stanford study, the faulty statistical inferences, the unreliability of the test assay, the prior stated agendas of the primary researchers, and the many, many experts who have identified the problems with it:
[tweet]https://twitter.com/thackerpd/status/1252549640714665984?s=20[/tweet]

Nothing this forum didn't already know from having thorough picked it apart. Shame that Stanford is associated with this exercise in academic bad faith.

[2006alum]

Excellent Merc article out today detailing the problems with the Stanford study, the faulty statistical inferences, the unreliability of the test assay, the prior stated agendas of the primary researchers, and the many, many experts who have identified the problems with it:
[tweet]https://twitter.com/thackerpd/status/1252549640714665984?s=20[/tweet]

Nothing this forum didn't already know from having thorough picked it apart. Shame that Stanford is associated with this exercise in academic bad faith.

[burger]

Excellent Merc article out today detailing the problems with the Stanford study, the faulty statistical inferences, the unreliability of the test assay, the prior stated agendas of the primary researchers, and the many, many experts who have identified the problems with it:

Nothing this forum didn't already know from having thorough picked it apart. Shame that Stanford is associated with this exercise in academic bad faith.

It's even worse than that article suggests.  Now right wingers (I'm not dignifying them with links) are using the study to argue that it's safe to open things up because the mortality rate is so low.  It's not a stretch to imagine people getting killed as a result of this study.

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

[burger]

Excellent Merc article out today detailing the problems with the Stanford study, the faulty statistical inferences, the unreliability of the test assay, the prior stated agendas of the primary researchers, and the many, many experts who have identified the problems with it:

Nothing this forum didn't already know from having thorough picked it apart. Shame that Stanford is associated with this exercise in academic bad faith.

It's even worse than that article suggests.  Now right wingers (I'm not dignifying them with links) are using the study to argue that it's safe to open things up because the mortality rate is so low.  It's not a stretch to imagine people getting killed as a result of this study.

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

[oldalum]

The authors need to publicly and loudly retract the preprint and admit their errors.  

Not much chance of that happening. From the same article:

Addressing the critics, Stanford’s Ioannidis, professor of medicine and  biomedical data science at Stanford University, promised an expanded version of their study will be posted soon. “The results remain very robust,” he said.

[oldalum]

The authors need to publicly and loudly retract the preprint and admit their errors.  

Not much chance of that happening. From the same article:

Addressing the critics, Stanford’s Ioannidis, professor of medicine and  biomedical data science at Stanford University, promised an expanded version of their study will be posted soon. “The results remain very robust,” he said.

[M T]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

It isn't clear to me what "universally" meant there.  Are you talking of the one study in NYC that came out in preprint recently, or perhaps you're saying that such testing is currently the standard procedure in LA county, or maybe you're saying it is all across the US?

People should be wary of using such a number as indicating 1.5% infection rate.  You need to think about when the infection happened and what are the effects of false positive & false negative on these numbers.

This study looks at the probability of a positive vs a false-negative result of a PCR test, based on sets of repeated testing of individuals.   For instance, if 100% of the pregnant patients were infected 30 days before the test, the number of positive results would be somewhere around the number reported.  (I'm NOT saying that is what happened.  I'm just trying to show one needs to be careful not to interpret the results without stopping to think.)

They also provide graphs to indicate how false positive rates (which they didn't try to measure) also affect the interpretation of prevalence, and urge better understanding of those numbers.

our results suggest that there may be some benefit to testing indiscriminately;conducting a single test on someone who had symptoms 10 days ago will have a nearly 33% false negative rate (using a nasal swab; 52.89% for a throat swab). As a means of determining population level exposure to SARS-CoV-2, serological tests are far more likely to provide an accurate profile.

(but, as we've seen, serological tests have their own set of problems, so far).

This study presents a case of a patient with clinical signs but had 9 negative PCR tests before getting the first positive tests.

[M T]

Pregnant patients prior to delivery are being universally tested, with about 1.5% positive. This is by PCR testing. It would fit with the LA county antibody prevalence testing showing low single digit exposure.

It isn't clear to me what "universally" meant there.  Are you talking of the one study in NYC that came out in preprint recently, or perhaps you're saying that such testing is currently the standard procedure in LA county, or maybe you're saying it is all across the US?

People should be wary of using such a number as indicating 1.5% infection rate.  You need to think about when the infection happened and what are the effects of false positive & false negative on these numbers.

This study looks at the probability of a positive vs a false-negative result of a PCR test, based on sets of repeated testing of individuals.   For instance, if 100% of the pregnant patients were infected 30 days before the test, the number of positive results would be somewhere around the number reported.  (I'm NOT saying that is what happened.  I'm just trying to show one needs to be careful not to interpret the results without stopping to think.)

They also provide graphs to indicate how false positive rates (which they didn't try to measure) also affect the interpretation of prevalence, and urge better understanding of those numbers.

our results suggest that there may be some benefit to testing indiscriminately;conducting a single test on someone who had symptoms 10 days ago will have a nearly 33% false negative rate (using a nasal swab; 52.89% for a throat swab). As a means of determining population level exposure to SARS-CoV-2, serological tests are far more likely to provide an accurate profile.

(but, as we've seen, serological tests have their own set of problems, so far).

This study presents a case of a patient with clinical signs but had 9 negative PCR tests before getting the first positive tests.

[dabigv13]

This is nonpublished data from a Southern California health system from the past couple weeks.

[dabigv13]

This is nonpublished data from a Southern California health system from the past couple weeks.

[BostonCard]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

[BostonCard]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

[burger]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

I think you're wrong for a few reasons.

1) The flaws in this preprint are so egregious that it has no legs left to stand on.  All of the positives could be false positives, and the authors erroneously did not account for this.  This isn't one of those "opinions differ on how to do this analysis" sorts of criticisms.  It's a fundamental error that makes the conclusions invalid.  Someone once told me that the worst thing you can say about a scientific paper is that the conclusions are not supported by the data. That's what we have here.

2) Getting an analysis wrong does not make us better understand the pandemic.  In fact, in the worst case scenario (already maybe happening), this faulty analysis may kill people by encouraging governors to open up their states to soon.

3) It's a preprint, and retracting now will actually be good for the entire research process going forward.  The media and public needs to realize that a certain proportion of all of these preprints floating around here are wrong to some degree, and some are very wrong.  It's not a bad thing for "science" to correct itself before publication.

4) I don't think you understand how peer review is supposed to work.  Articles that have fundamental mistakes should never be published, period.  Science is ultimately self-correcting, but there's a big difference between, say, a new theory that makes old studies invalid and publishing a paper full of mistakes.  Just because some papers get through with mistakes doesn't mean that that's a good thing.  Quite the opposite.  And during a pandemic, we don't have time to wait months for a better paper to come along and correct the erroneous one that decision-makers are already basing their actions on.

Edit: forgot to mention the non-random sampling issue which is as bad as the statistical issues, if not worse.

[burger]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

I think you're wrong for a few reasons.

1) The flaws in this preprint are so egregious that it has no legs left to stand on.  All of the positives could be false positives, and the authors erroneously did not account for this.  This isn't one of those "opinions differ on how to do this analysis" sorts of criticisms.  It's a fundamental error that makes the conclusions invalid.  Someone once told me that the worst thing you can say about a scientific paper is that the conclusions are not supported by the data. That's what we have here.

2) Getting an analysis wrong does not make us better understand the pandemic.  In fact, in the worst case scenario (already maybe happening), this faulty analysis may kill people by encouraging governors to open up their states to soon.

3) It's a preprint, and retracting now will actually be good for the entire research process going forward.  The media and public needs to realize that a certain proportion of all of these preprints floating around here are wrong to some degree, and some are very wrong.  It's not a bad thing for "science" to correct itself before publication.

4) I don't think you understand how peer review is supposed to work.  Articles that have fundamental mistakes should never be published, period.  Science is ultimately self-correcting, but there's a big difference between, say, a new theory that makes old studies invalid and publishing a paper full of mistakes.  Just because some papers get through with mistakes doesn't mean that that's a good thing.  Quite the opposite.  And during a pandemic, we don't have time to wait months for a better paper to come along and correct the erroneous one that decision-makers are already basing their actions on.

Edit: forgot to mention the non-random sampling issue which is as bad as the statistical issues, if not worse.

[Goose]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

I totally agree that this paper, warts and all, needs to be made public. There isn't tons of other data out there, so we need to take what there is, if for no other reason than to identify problems in this study. Maybe there is more to it than that and the "reviewers comments" can be addressed, at least to some degree. If not, at least in can serve as an example of how not to do it.

[Goose]

The authors need to publicly and loudly retract the preprint and admit their errors.  It's painful to see Stanford's name dragged through the mud, but it's not too late to avoid the worst damage.

No, I could not disagree more.  If every methodologically imperfect study was retracted, the medical literature would never advance.  In fact, there would be no medical literature.  Unless the authors are downright falsifying their data, they should not retract it.  Hopefully, they are addressing criticisms of their work and are working to address them and they are working to make the data and underlying methodology more transparent (and also, undergoing the peer review process).  But science only works if you accept that some "wrong" articles are published.  For one, sometimes the results of methodologically flawed papers are confirmed through more rigorous analysis.  Secondly, the scientific debate is healthy.  But it can only work if scientific papers are evaluated on their merit, and not because someone doesn't like their conclusions.  Does the paper have flaws?  Absolutely.  Have I seen papers with worse flaws get published in high impact journals?  Absolutely.  The paper helps us better understand the pandemic and as such it should absolutely be out there, even if the message challenges our understanding of the facts and there may be issues in how it was carried out.

BC

I totally agree that this paper, warts and all, needs to be made public. There isn't tons of other data out there, so we need to take what there is, if for no other reason than to identify problems in this study. Maybe there is more to it than that and the "reviewers comments" can be addressed, at least to some degree. If not, at least in can serve as an example of how not to do it.

[2006alum]

I totally agree that this paper, warts and all, needs to be made public. There isn't tons of other data out there, so we need to take what there is, if for no other reason than to identify problems in this study. Maybe there is more to it than that and the "reviewers comments" can be addressed, at least to some degree. If not, at least in can serve as an example of how not to do it.

IMHO, there is a brobdingnagian delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

[2006alum]

I totally agree that this paper, warts and all, needs to be made public. There isn't tons of other data out there, so we need to take what there is, if for no other reason than to identify problems in this study. Maybe there is more to it than that and the "reviewers comments" can be addressed, at least to some degree. If not, at least in can serve as an example of how not to do it.

IMHO, there is a brobdingnagian delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

[Goose]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

[Goose]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

[OutsiderFan]

I just heard someone say the study has been retracted. Can’t find confirmation.

[OutsiderFan]

I just heard someone say the study has been retracted. Can’t find confirmation.

[dabigv13]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

Good scientists don't go to the media with unbacked predictions, and then publish a study with fundamental errors that gives support to their prior untested theories.

That's not ad hominem to observe. This is far from normal operating procedure and I'll be surprised if this paper is published in a reputable journal after peer review without extensive revisions.

[dabigv13]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

Good scientists don't go to the media with unbacked predictions, and then publish a study with fundamental errors that gives support to their prior untested theories.

That's not ad hominem to observe. This is far from normal operating procedure and I'll be surprised if this paper is published in a reputable journal after peer review without extensive revisions.

[2006alum]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

Because three of the co-authors were on record in mid-March saying this was no worse than the flu and social distancing was an overreaction. They do a study that has serious methodology flaws they do not even attempt to address in their estimates, and those estimates are used to extrapolate a finding (an IFR of .12%) that seems to contradict real world lived experience in places like NYC, Italy, and Spain, while failing to disclose that an equally possible finding within their own confidence intervals is a dataset of exclusively false positives.

No one seems to have explained to me why they made no effort to adjust for the self-selection in sample, nor why didn't have a topline result noting that they could not at the 95% confidence level exclude a null hypothesis that there was effectively no non-documented community spread.

The only answer I can reach is that they are acting in bad faith. I'm still waiting for evidence to the contrary.

[2006alum]

IMHO, there is a of immense proportions delta between "making data public" and needlessly extrapolating a non-credible IFR estimate and seeking widespread media coverage by giving interviews, press releases, etc., all broadcasting that this is not much worse than the flu, as several of the co-authors of this paper have been doing since at least mid March. IMHO, it's VERY hard to rebut an accusation of bad faith given how flawed this paper is.

You underestimate the power of hubris and stupidity :-). Seriously, just because you (and others) believe the conclusions are flawed why do you ipso facto believe those that disagree with you are operating in "bad faith"?   Granted, it may be the authors are "bad" people, I really don't know. But until I have concrete evidence otherwise, I am willing to accept the idea they are honest in intent but wrong in some conclusions. To do otherwise is ad hominem, IMHO.

Because three of the co-authors were on record in mid-March saying this was no worse than the flu and social distancing was an overreaction. They do a study that has serious methodology flaws they do not even attempt to address in their estimates, and those estimates are used to extrapolate a finding (an IFR of .12%) that seems to contradict real world lived experience in places like NYC, Italy, and Spain, while failing to disclose that an equally possible finding within their own confidence intervals is a dataset of exclusively false positives.

No one seems to have explained to me why they made no effort to adjust for the self-selection in sample, nor why didn't have a topline result noting that they could not at the 95% confidence level exclude a null hypothesis that there was effectively no non-documented community spread.

The only answer I can reach is that they are acting in bad faith. I'm still waiting for evidence to the contrary.