Coronavirus

[meiroy]

According to Worldometer, USA had 267 Covid deaths yesterday.  That's the lowest figure since March 23rd, yet for some odd reason I can't seem to find any headlines at any major media outlet talking about it.  Weird.

 

Lol...

 

Something else that’s “weird”—the mortality graph is shifted to the right when compared to the case graph...almost like mortality lags cases and cases can be seen as an early warning sign of where mortality might be headed...hmmm...

 

 

Yes, deaths lag cases but that doesn't seem to be the case. Which makes it even more impressive.

[ERICOPOLY]

After Flu vaccine is given, number of cases of flu go down, not up.

After lockdown did cases go down or up?

 

I find that surprising since the CDC recommends getting the flu vaccine by the end of October each year.  Then the number of flu cases rise afterwards.

 

Because we all know that summer time respiratory diseases go down and winter they go up. Thats why they give flu vaccine in October.

 

Nevertheless.  Cases rising X amount after locking people down does not show that it was ineffective.  For example, let's say one person in my household was just exposed on the morning the lockdown began.  That person doesn't test positive for 10 more days, and then 10 more days after that a couple more people in the household come down with it.  That's 20 days of lockdown and an explosion in cases within my household.

 

Did you just accidentally make a case against lockdowns?  ;)

 

Yup.  Eric just described how to get an explosion of cases.

 

The data from NYC itself is clear. More crowded, more cases.  People living in small houses, more cases.  People going out such as transit and police, less cases.

 

I take it you are being facetious.  Intra-household spread is going to occur regardless of policy.

 

No, I am not being facetious. See below.

 

https://www.cnbc.com/2020/05/06/ny-gov-cuomo-says-its-shocking-most-new-coronavirus-hospitalizations-are-people-staying-home.html

Cuomo says it’s ‘shocking’ most new coronavirus hospitalizations are people who had been staying home

 

https://www.forbes.com/sites/lisettevoytko/2020/05/18/cuomo-said-most-coronavirus-cases-are-from-people-staying-at-home-public-health-experts-have-a-few-ideas-why/#5389e322d20e

 

I have put bold emphasis on what I deem suspicious and particularly interesting (was this a political statement by Cuomo?).

 

 

Jha called for Cuomo to release the full survey results: “Without having a full splay of the data, it’s very hard to know what this analysis tells you.” Cuomo’s office did not respond to multiple requests for comment by Forbes.

 

 

Social media users questioned the survey’s results, saying that because patients were coming from their homes, it meant that stay-at-home orders were flawed or an outright failure. Jha disagreed, saying other studies have shown that reducing people’s mobility flattens the curve, and that’s what has taken place in New York’s outbreak. “I don’t have a question in my mind whether ‘stay at home’ worked,” Jha said.

 

Both Vasan and Jha said the type of lockdown seen in Wuhan, where COVID-19 was first detected, was much more stringent than what New York and other U.S. states have been under⁠—meaning the virus could be transmitting more easily here.

 

 

Dr. Ashish Jha, Director of Harvard Global Health Institute, was first surprised by the survey’s results, but realized that “older and sicker people are less likely to go out and travel, and much more likely to get infected and to need hospital care.”

 

Dr. Ashwin Vasan, Columbia University Medical Center professor and CEO of nonprofit Fountain House, wanted to know more about the patients: “Even though these people are older, do they live with essential workers? Did they live in multi-generational households?”

 

According to Vasan, who also once served as an executive director for the NYC Department of Health, older people either living with essential workers or in multi-generational households are more common in low income and African American communities.

 

What New York did not account for, Vasan said, was transmission inside apartment buildings⁠—”particularly in densely-populated communities, which seems to track with the [survey’s] results.”

 

 

 

[Dalal.Holdings]

 

Yes, deaths lag cases but that doesn't seem to be the case. Which makes it even more impressive.

 

Given our existing dataset, we should know within a week or so if deaths inflect upwards if we expect the same lag time as in late March to hold. Nationally, cases really started inflecting up about 1 week ago, so it may be too soon to celebrate falling mortality numbers....Precautionary principle tells me better to worry than to blow it off and start celebrating, but that’s just me.

 

Additionally, anyone looking at the daily data should see an obvious 7 day periodicity to the bars—rising during weekdays and falling on weekends with lowest counts on Sundays. This probably relates to testing/labs/reporting/etc falling during weekend as the virus doesn’t take weekends off, but some staff do. I would not celebrate too soon by looking at Sunday’s numbers of mortality (which is a lagging indicator itself).

 

Saturday/Sunday’s case number continues to rise despite the weekend effect though which suggests even further rise in cases this week...

[alwaysdrawing]

 

Yes, deaths lag cases but that doesn't seem to be the case. Which makes it even more impressive.

 

Given the lag time, we should know within a week or so if deaths inflect upwards if we expect the same lag time as in late March to hold as nationally, cases really started inflecting up about 1 week ago...Precautionary principle tells me better to worry than to blow it off, but that’s me.

 

Anyone looking at the daily data should see an obvious 7 day periodicity to the bars—rising during weekdays and falling on weekends with lowest counts on Sundays. This probably relates to testing/labs/reporting/etc falling during weekend as the virus doesn’t take weekends off, but some staff do. I would not celebrate too soon by looking at Sunday’s numbers of mortality (which is a lagging indicator itself).

 

Saturday/Sunday’s case number continues to rise despite the weekend effect though which suggests even further rise in cases this week...

 

I don't generally read this thread much anymore, but I agree this looks like an inflection point in the US states that are newly spiking.  Texas, Florida, Arizona, and potentially California may all be looking at another lockdown within a couple weeks.  California at least has increased mandatory NPIs like mask wearing, however the others do not seem to be changing their NPI guidelines (yet). 

 

Maryland notably has been a more proactive state regarding NPIs--I wouldn't be surprised if GOP Governor Hogan becomes a new star after this, as he has drawn a clear contrast with other GOP governors.

 

Overall, the falling death rate seems likely due to increased testing, and to some extent better treatment protocols.  There is probably also a better mix of ages for lower mortality, as high risk groups have taken increasing precautions.  The increase in positivity rates as well as positive tests in the recently spiking states is worrying--especially with reduced NPIs and "return to normalcy", I worry we will be looking at a second large outbreak or several clusters.  The bigger these outbreaks get, the more painful reacting is, as it means either shutdowns or increased spread beyond the borders of the outbreak.

 

Globally things do not seem to be slowing either.  India, particularly New Delhi, is in a very bad and dangerous situation.  I am very concerned things spiral out of control in India.  Brazil is obviously another hugely problematic area.  Mexico's positivity rate over 50% is incredibly worrying to me.

 

Overall, global cases hit an all time high yesterday....a Sunday.  That likely means things are even somewhat worse than reported due to weekend reporting effects.  This coming week will be telling--Tuesday's statistics may be a wake up call, once the weekend effect has worn off.

 

I have added small positions in 1 month VIX $60 calls and 2 month 30% OOTM market puts as a hedge for what I think would be the likely market reaction if events unfold how I see the statistics trending (i.e. hospitalizations/deaths increasing as a mirror on a two week lag to infections, and infections continuing to increase as the incubation period matures).

[Dalal.Holdings]

I would not say the situation is same across the globe. EU countries, even Italy and Spain, have much fewer new cases by the day now and doing much better.

 

USA in similar basket as Brazil and India with persistent new case formation. Guess we are like an emerging country now... Are we Great Again yet?

 

 

 

 

[alwaysdrawing]

I would not say the situation is same across the globe. EU countries, even Italy and Spain, have much fewer new cases by the day now and doing much better.

 

USA in similar basket as Brazil and India with persistent new case formation. Guess we are like an emerging country now... Are we Great Again yet?

 

 

 

I agree totally.  The US has done terribly, and the politicization of NPIs like masks is the height of stupidity.

 

We are going to face the worst of it, public health wise and economically, until we start acting like a mature, responsible country.  That means, continued mask wearing, increased testing, increased manufacturing capacity for PPE, and eventually, when we are able to obtain a result like Italy or other European and Asian countries with better results, to introduce contact tracing. 

 

I do not have confidence we are moving in that direction.  I actually think states/American people may refuse any second shutdowns, and the situation could quickly spin out of control with (relatively) unmitigated spread.

[Spekulatius]

 

Yes, deaths lag cases but that doesn't seem to be the case. Which makes it even more impressive.

 

Given our existing dataset, we should know within a week or so if deaths inflect upwards if we expect the same lag time as in late March to hold. Nationally, cases really started inflecting up about 1 week ago, so it may be too soon to celebrate falling mortality numbers....Precautionary principle tells me better to worry than to blow it off and start celebrating, but that’s just me.

 

Additionally, anyone looking at the daily data should see an obvious 7 day periodicity to the bars—rising during weekdays and falling on weekends with lowest counts on Sundays. This probably relates to testing/labs/reporting/etc falling during weekend as the virus doesn’t take weekends off, but some staff do. I would not celebrate too soon by looking at Sunday’s numbers of mortality (which is a lagging indicator itself).

 

Saturday/Sunday’s case number continues to rise despite the weekend effect though which suggests even further rise in cases this week...

 

Death have gone from ~1000/day a few weeks ago to ~300 day, despite a larger number of positive testS and in many states even a larger percentage of positive tests, indicating more Virus circulating around.

 

As mentioned in some news outlets, the likely cause is that one the infected skew you get, which has a large impact on IFR rates. It is also likely that better medical treatment had contributed some to the decline, but I think the biggest issue is age distribution of the infected.

[Gregmal]

My sense is that the market doesnt fear the virus...it fears the government responses. You can look at charts about death rates and total cases all you want, but I'm waiting for one charting the economic consequences of "shut everything down and lock people in their homes"...

 

It is also evident a lot of people do not fear the virus(for better or for worse) and have only been held back by government shutdowns. To the extent they focus on what should have been done from the get go, worry about older and at risk and tell the rest to be careful, I doubt things turn out as morbid as some are predicting. Which would be fine for stocks....if they were already obscenely expensive.

[Guest cherzeca]

Median Infection Fatality Rate Of COVID-19 For Those Under-70 Is Just 0.04%

 

https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v2.full.pdf

[ERICOPOLY]

Median Infection Fatality Rate Of COVID-19 For Those Under-70 Is Just 0.04%

 

https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v2.full.pdf

 

Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

 

https://www.medrxiv.org/

[alwaysdrawing]

Median Infection Fatality Rate Of COVID-19 For Those Under-70 Is Just 0.04%

 

https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v2.full.pdf

 

Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

 

https://www.medrxiv.org/

 

John Ioannidis is the author of the discredited Santa Clara serology study.  There were multiple issues with the study, including sampling bias, not adjusting for the sensitivity and specificity of the serology test, poststratification, and others.  This new study aggregates his original study with a bunch of other seroprevalence studies with similar flaws, and gets the same as his original results....but with the same limitations.

 

Perhaps the bottom line is best summed up by Nate Silver:

There are a lot of well-intended and well-written critiques of the Santa Clara Co. serology study but at some point it's not that complicated. A test that *could* have a false positive rate of up to ~2-3% isn't saying very much if it detects 2-3% positives in some population

 

When you look at locations with larger outbreaks, you see worse mortality rates.  Why?  Because if the false positive rate is 2%, then if the base rate of the population is 20% who have COVID, the error is only 10%, while if the base rate is 1%, it could be 200%.  Serology surveys are used to tell us approximately what proportion of the population has had a disease, not typically to estimate the Infection Fatality Rate (IFR).

 

There are numerous threads by good sources on Twitter from back in April on this by Trevor Bedford, Natalie Dean, PhD, and many others.

 

One such thread here walks through a number of the limitations:

 

A Columbia statistician named Andrew Gelman discusses the problems here:

https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/

 

Natalie Dean thread here:

 

 

If you want an estimate based on less noisy data, you can look at the NYC population level deaths and you can calculate some back of the envelope estimates.  Pretty clearly COVID hits older folks much harder, but I think the rates are higher than Ioannidis claims based on serology studies.

https://www1.nyc.gov/site/doh/covid/covid-19-data.page

 

Citywide, the death rate is .21% (that's of all people in NY, not just cases), with 75+ having a death rate of 1.57%, 65-74 0.63%, 45-64 0.19%, and 18-44 0.02%.  That's on a population level, in a city with an estimated 25% prevalence, these numbers would have to be multiplied by 4 if you want to estimate the IFR, giving you approx 0.84% overall IFR, with subgroups 75+ 6.28%, 65-74 2.52%, 45-64 0.76%, 18-44 0.08%.

 

Based on the data I've seen, those numbers look more realistic than Ioannidis.

 

[jamesmadison]

Median Infection Fatality Rate Of COVID-19 For Those Under-70 Is Just 0.04%

 

https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v2.full.pdf

 

Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

 

https://www.medrxiv.org/

 

John Ioannidis is the author of the discredited Santa Clara serology study.  There were multiple issues with the study, including sampling bias, not adjusting for the sensitivity and specificity of the serology test, poststratification, and others.  This new study aggregates his original study with a bunch of other seroprevalence studies with similar flaws, and gets the same as his original results....but with the same limitations.

 

Perhaps the bottom line is best summed up by Nate Silver:

There are a lot of well-intended and well-written critiques of the Santa Clara Co. serology study but at some point it's not that complicated. A test that *could* have a false positive rate of up to ~2-3% isn't saying very much if it detects 2-3% positives in some population

 

When you look at locations with larger outbreaks, you see worse mortality rates.  Why?  Because if the false positive rate is 2%, then if the base rate of the population is 20% who have COVID, the error is only 10%, while if the base rate is 1%, it could be 200%.  Serology surveys are used to tell us approximately what proportion of the population has had a disease, not typically to estimate the Infection Fatality Rate (IFR).

 

There are numerous threads by good sources on Twitter from back in April on this by Trevor Bedford, Natalie Dean, PhD, and many others.

 

One such thread here walks through a number of the limitations:

 

A Columbia statistician named Andrew Gelman discusses the problems here:

https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/

 

Natalie Dean thread here:

 

 

If you want an estimate based on less noisy data, you can look at the NYC population level deaths and you can calculate some back of the envelope estimates.  Pretty clearly COVID hits older folks much harder, but I think the rates are higher than Ioannidis claims based on serology studies.

https://www1.nyc.gov/site/doh/covid/covid-19-data.page

 

Citywide, the death rate is .21% (that's of all people in NY, not just cases), with 75+ having a death rate of 1.57%, 65-74 0.63%, 45-64 0.19%, and 18-44 0.02%.  That's on a population level, in a city with an estimated 25% prevalence, these numbers would have to be multiplied by 4 if you want to estimate the IFR, giving you approx 0.84% overall IFR, with subgroups 75+ 6.28%, 65-74 2.52%, 45-64 0.76%, 18-44 0.08%.

 

Based on the data I've seen, those numbers look more realistic than Ioannidis.

 

Your critiques are totally reasonable about his work. With a 2-3% false positive rate and a 2-3% prevalence, who knows what's going on.  Are you sure, however, that all 23 studies are similarly flawed? 

 

However, I think it's a bit "strange" for you to use NYC - literally the hardest hit area in the entire country (maybe the world?) as a counter-point.  Do you really think NYC is a good proxy for the entire country?  That seems like quite a stretch.  Furthermore, if you are willing to use the estimated 25% prevalence rate in NYC to do your calculations, why are you resistant to using the others?

 

What's interesting is the lack of recent news about sero-prevalence studies.  There hasn't been much on that front in well over a month. 

[UK]

https://www.bloomberg.com/news/articles/2020-06-18/sweden-remains-far-from-herd-immunity-despite-softer-lockdown

https://www.reuters.com/article/us-health-coronavirus-antibody/antibody-levels-in-recovered-covid-19-patients-decline-quickly-research-idUSKBN23T1CJ

[alwaysdrawing]

Your critiques are totally reasonable about his work. With a 2-3% false positive rate and a 2-3% prevalence, who knows what's going on.  Are you sure, however, that all 23 studies are similarly flawed? 

 

However, I think it's a bit "strange" for you to use NYC - literally the hardest hit area in the entire country (maybe the world?) as a counter-point.  Do you really think NYC is a good proxy for the entire country?  That seems like quite a stretch.  Furthermore, if you are willing to use the estimated 25% prevalence rate in NYC to do your calculations, why are you resistant to using the others?

 

What's interesting is the lack of recent news about sero-prevalence studies.  There hasn't been much on that front in well over a month.

 

Many seroprevalence studies have the same faults as the Santa Clara study. I've read a number of the studies he's included, and the bottom line is, seroprevalence studies are just not a great way of estimating IFR when the false positive rate of the serology tests is so high. 

 

NY just has some of the better statistics I've seen available--I just included as a proxy for general IFR estimating.  I wouldn't hang my hat on those estimates, but even the population level death statistics show that it's higher than he's estimating.

[orthopa]

After Flu vaccine is given, number of cases of flu go down, not up.

After lockdown did cases go down or up?

 

I find that surprising since the CDC recommends getting the flu vaccine by the end of October each year.  Then the number of flu cases rise afterwards.

 

Because we all know that summer time respiratory diseases go down and winter they go up. Thats why they give flu vaccine in October.

 

Nevertheless.  Cases rising X amount after locking people down does not show that it was ineffective.  For example, let's say one person in my household was just exposed on the morning the lockdown began.  That person doesn't test positive for 10 more days, and then 10 more days after that a couple more people in the household come down with it.  That's 20 days of lockdown and an explosion in cases within my household.

 

Did you just accidentally make a case against lockdowns?  ;)

 

Yup.  Eric just described how to get an explosion of cases.

 

The data from NYC itself is clear. More crowded, more cases.  People living in small houses, more cases.  People going out such as transit and police, less cases.

 

I take it you are being facetious.  Intra-household spread is going to occur regardless of policy.

 

No, I am not being facetious. See below.

 

https://www.cnbc.com/2020/05/06/ny-gov-cuomo-says-its-shocking-most-new-coronavirus-hospitalizations-are-people-staying-home.html

Cuomo says it’s ‘shocking’ most new coronavirus hospitalizations are people who had been staying home

 

https://www.forbes.com/sites/lisettevoytko/2020/05/18/cuomo-said-most-coronavirus-cases-are-from-people-staying-at-home-public-health-experts-have-a-few-ideas-why/#5389e322d20e

 

I have put bold emphasis on what I deem suspicious and particularly interesting (was this a political statement by Cuomo?).

 

 

Jha called for Cuomo to release the full survey results: “Without having a full splay of the data, it’s very hard to know what this analysis tells you.” Cuomo’s office did not respond to multiple requests for comment by Forbes.

 

 

Social media users questioned the survey’s results, saying that because patients were coming from their homes, it meant that stay-at-home orders were flawed or an outright failure. Jha disagreed, saying other studies have shown that reducing people’s mobility flattens the curve, and that’s what has taken place in New York’s outbreak. “I don’t have a question in my mind whether ‘stay at home’ worked,” Jha said.

 

Both Vasan and Jha said the type of lockdown seen in Wuhan, where COVID-19 was first detected, was much more stringent than what New York and other U.S. states have been under⁠—meaning the virus could be transmitting more easily here.

 

 

Dr. Ashish Jha, Director of Harvard Global Health Institute, was first surprised by the survey’s results, but realized that “older and sicker people are less likely to go out and travel, and much more likely to get infected and to need hospital care.”

 

Dr. Ashwin Vasan, Columbia University Medical Center professor and CEO of nonprofit Fountain House, wanted to know more about the patients: “Even though these people are older, do they live with essential workers? Did they live in multi-generational households?”

 

According to Vasan, who also once served as an executive director for the NYC Department of Health, older people either living with essential workers or in multi-generational households are more common in low income and African American communities.

 

What New York did not account for, Vasan said, was transmission inside apartment buildings⁠—”particularly in densely-populated communities, which seems to track with the [survey’s] results.”

 

 

 

https://www.latimes.com/california/story/2020-04-21/autopsies-reveal-first-confirmed-u-s-coronavirus-deaths-occurred-in-bay-area-in-early-february?mod=article_inline

 

If COVID was in California earlier then expected it was in NYC earlier then expected. Both get tons of international flights. That being said community spread was happening undetected. Was it the stay at home order that poured gas on the fire in NYC?

 

Initial business closure was on March 16th, schools closed on March 18th, Shelter in place March 22nd. Peak hospital usage April 8-10th so 21-23 days after kids forced to stay home. Are there a lot of multi generational homes in NYC? Was the gas on the fire bringing everyone together and locking them up in close contact for days on end? People of color would seem to be more likely to live in a multi generational situations. Is this why they are more hard hit in addition to comorbidities?

 

Italy had some of the strictest stay at home orders started on March 9th and 30% of Italians live in multi generational homes

 

https://www.wsj.com/articles/family-is-italys-great-strength-coronavirus-made-it-deadly-11585058566

 

Italy has a ton of multi generational homes

 

Wouldn't that be a pisser if the stay at home orders had just the opposite effects in NYC, Italy and Spain?

 

I had the same questions as these guys back in April.

[KCLarkin]

It is also important to remember that these serology tests do not require FDA approved. So the quality of the tests vary widely.

 

Under the FDA’s March 16 policy for serological tests, the FDA provided regulatory flexibility for developers offering such tests without FDA review and without an EUA where they have notified FDA that they have validated their tests and provide disclaimers about the limitations of the tests with any results generated by their tests, as outlined in the policy.  The FDA does not review the validation, or accuracy, data for these tests unless an EUA is submitted.

 

So a meta-analysis without evaluating which tests were used seems reckless.

 

--

Antibody tests for COVID-19 wrong up to half the time, CDC says

https://www.ctvnews.ca/health/coronavirus/antibody-tests-for-covid-19-wrong-up-to-half-the-time-cdc-says-1.4956506

[orthopa]

Your critiques are totally reasonable about his work. With a 2-3% false positive rate and a 2-3% prevalence, who knows what's going on.  Are you sure, however, that all 23 studies are similarly flawed? 

 

However, I think it's a bit "strange" for you to use NYC - literally the hardest hit area in the entire country (maybe the world?) as a counter-point.  Do you really think NYC is a good proxy for the entire country?  That seems like quite a stretch.  Furthermore, if you are willing to use the estimated 25% prevalence rate in NYC to do your calculations, why are you resistant to using the others?

 

What's interesting is the lack of recent news about sero-prevalence studies.  There hasn't been much on that front in well over a month.

 

Many seroprevalence studies have the same faults as the Santa Clara study. I've read a number of the studies he's included, and the bottom line is, seroprevalence studies are just not a great way of estimating IFR when the false positive rate of the serology tests is so high. 

 

NY just has some of the better statistics I've seen available--I just included as a proxy for general IFR estimating.  I wouldn't hang my hat on those estimates, but even the population level death statistics show that it's higher than he's estimating.

 

New tests are much more accurate. More serology large scale tests should be done.

 

https://diagnostics.roche.com/us/en/news-listing/2020/roche-highly-accurate-antibody-test-for-covid-19-goes-live-at-more-than-20-initial-lab-sites-in-the-us.html

 

It provides 99.8 percent specificity,

[KCLarkin]

Wouldn't that be a pisser if the stay at home orders had just the opposite effects in NYC, Italy and Spain?

 

Experts: test-trace-ISOLATE.

 

[Guest cherzeca]

The pair also suggests that the mandatory stay-at-home orders issued in hopes of stopping the spread of coronavirus may have been more harmful than good.

 

https://nypost.com/2020/06/23/new-study-says-summer-sun-can-kill-coronavirus-in-34-minutes/

[KCLarkin]

Your critiques are totally reasonable about his work. With a 2-3% false positive rate and a 2-3% prevalence, who knows what's going on.  Are you sure, however, that all 23 studies are similarly flawed? 

 

However, I think it's a bit "strange" for you to use NYC - literally the hardest hit area in the entire country (maybe the world?) as a counter-point.  Do you really think NYC is a good proxy for the entire country?  That seems like quite a stretch.  Furthermore, if you are willing to use the estimated 25% prevalence rate in NYC to do your calculations, why are you resistant to using the others?

 

What's interesting is the lack of recent news about sero-prevalence studies.  There hasn't been much on that front in well over a month.

 

Many seroprevalence studies have the same faults as the Santa Clara study. I've read a number of the studies he's included, and the bottom line is, seroprevalence studies are just not a great way of estimating IFR when the false positive rate of the serology tests is so high. 

 

NY just has some of the better statistics I've seen available--I just included as a proxy for general IFR estimating.  I wouldn't hang my hat on those estimates, but even the population level death statistics show that it's higher than he's estimating.

 

New tests are much more accurate. More serology large scale tests should be done.

 

https://diagnostics.roche.com/us/en/news-listing/2020/roche-highly-accurate-antibody-test-for-covid-19-goes-live-at-more-than-20-initial-lab-sites-in-the-us.html

 

It provides 99.8 percent specificity,

 

Yes, that's my point. We should be looking at serology studies that used high quality tests. Not a meta-analysis of all serology studies (with varying quality in study design and test used). I'd rather read one good study than find the "median" of crappy studies.

[jamesmadison]

Your critiques are totally reasonable about his work. With a 2-3% false positive rate and a 2-3% prevalence, who knows what's going on.  Are you sure, however, that all 23 studies are similarly flawed? 

 

However, I think it's a bit "strange" for you to use NYC - literally the hardest hit area in the entire country (maybe the world?) as a counter-point.  Do you really think NYC is a good proxy for the entire country?  That seems like quite a stretch.  Furthermore, if you are willing to use the estimated 25% prevalence rate in NYC to do your calculations, why are you resistant to using the others?

 

What's interesting is the lack of recent news about sero-prevalence studies.  There hasn't been much on that front in well over a month.

 

Many seroprevalence studies have the same faults as the Santa Clara study. I've read a number of the studies he's included, and the bottom line is, seroprevalence studies are just not a great way of estimating IFR when the false positive rate of the serology tests is so high. 

 

NY just has some of the better statistics I've seen available--I just included as a proxy for general IFR estimating.  I wouldn't hang my hat on those estimates, but even the population level death statistics show that it's higher than he's estimating.

 

New tests are much more accurate. More serology large scale tests should be done.

 

https://diagnostics.roche.com/us/en/news-listing/2020/roche-highly-accurate-antibody-test-for-covid-19-goes-live-at-more-than-20-initial-lab-sites-in-the-us.html

 

It provides 99.8 percent specificity,

 

Yes, that's my point. We should be looking at serology studies that used high quality tests. Not a meta-analysis of all serology studies (with varying quality in study design and test used). I'd rather read one good study than find the "median" of crappy studies.

 

Agreed.  As opposed to what that charlatan, Neil Ferguson, did with his POS useless model in which he used the median of all the crappy outputs to help justify the lockdowns.  ;)

[vinod1]

Neil Ferguson is a charlatan. Injecting bleach is genius! Trump supporters at their best.

 

I can see why college educated women would not date Trump supporters!

[clutch]

I can't help but think that we are going to have very similar discussions regarding climate change in the near future.

 

We will rely on prediction models that have no proof for causations (only correlations), no scientific validation (only based on incomplete data) and a ridiculously huge range of outcomes to make draconian decisions like a lockdown -- in this case, a "lockdown" of activities to prevent CO2 emissions.

 

People will say: "we have to do this for the worst-case scenario". Well, if that's your reasoning then you are not making a scientific decision. Just another version of Pascal's wager.

 

Just like people have abused religions and socialism to suppress freedom in the past, they will again do the same this time with science.

 

Note that I'm not discrediting science here -- but it's when people misuse/abuse the tool, the great danger arises.

[clutch]

Neil Ferguson is a charlatan.

 

Maybe not a charlatan, but he is a hypocrite. He broke the lockdown rules himself to be with his lover. A definition of a limousine liberal?

[jamesmadison]

Neil Ferguson is a charlatan. Injecting bleach is genius! Trump supporters at their best.

 

I can see why college educated women would not date Trump supporters!

 

You stay classy, vinod