[dabigv13]

Yup, were going to feel a pinch from our private payers. But government pays most of our bills, and they just scrapped together 2 trillion. They can find some more too I bet. 

Comically myopic is thinking there is some sort of market approach to this pandemic. Maybe you belong on that blue ribbon commission with Jared and the guy who cant stay awake in his meetings.

[dabigv13]

Yup, were going to feel a pinch from our private payers. But government pays most of our bills, and they just scrapped together 2 trillion. They can find some more too I bet. 

Comically myopic is thinking there is some sort of market approach to this pandemic. Maybe you belong on that blue ribbon commission with Jared and the guy who cant stay awake in his meetings.

[teejers1]

Do you want your cancer operated on? Or your heart attack treated?

There is no functional economy or society without functioning hospitals, just not realisetic.

That's almost comically myopic. Don't you realize that the converse is equally true? That there are no functional hospitals without a functioning economy?

I wonder what definition of "functioning hospital" is.  I mean, aren't a ton of non-critical medical appointments/procedures - you know, the ones that keep hospitals afloat financially - being canceled now?  I'm not in medical profession and don't pretend to know anything.  But that's also why I am limited to layman terms/common sense, like linking "re-opening" to capacity to address those needing hospitalization for COVID virus.

And btw, tying these points together, it wouldn't shock me if hospitals put all COVID patients in some non-hospital site (though one fully equipped to handle treatment) so that hospitals can, in fact, go back to more regular operations.  [Maybe this is going on already, IDK].   This, of course, is also dependent on capacity (doctors and staff availability being the most important aspect of that, which will also be tied to how much of those resources need to be devoted to COVID patients).

[teejers1]

Do you want your cancer operated on? Or your heart attack treated?

There is no functional economy or society without functioning hospitals, just not realisetic.

That's almost comically myopic. Don't you realize that the converse is equally true? That there are no functional hospitals without a functioning economy?

I wonder what definition of "functioning hospital" is.  I mean, aren't a ton of non-critical medical appointments/procedures - you know, the ones that keep hospitals afloat financially - being canceled now?  I'm not in medical profession and don't pretend to know anything.  But that's also why I am limited to layman terms/common sense, like linking "re-opening" to capacity to address those needing hospitalization for COVID virus.

And btw, tying these points together, it wouldn't shock me if hospitals put all COVID patients in some non-hospital site (though one fully equipped to handle treatment) so that hospitals can, in fact, go back to more regular operations.  [Maybe this is going on already, IDK].   This, of course, is also dependent on capacity (doctors and staff availability being the most important aspect of that, which will also be tied to how much of those resources need to be devoted to COVID patients).

[Genuine Realist]

Yup, were going to feel a pinch from our private payers. But government pays most of our bills, and they just scrapped together 2 trillion. They can find some more too I bet. 

Comically myopic is thinking there is some sort of market approach to this pandemic. Maybe you belong on that blue ribbon commission with Jared and the guy who cant stay awake in his meetings.

Myopia, comic or not, is believing every other social value should be subordinated to the battle against C-19. I'm sure you know that suicide and divorce rates are directly correlated with unemployment percentages? And I don't think anyone has ever traced the degree to which mental illness and related ills are exacerbated by extensive social distancing. It's never been done before.

Plus those funds that the government 'scrapes up' are actually generated by commercial transactions on large scale, which commerce is at a standstill. 

So there IS a trade off, even if you restrict the metric to o health alone (ignoring quality of life issues, which is actually absurd).

It's a pretty prosaic point, so I am surprised at the resistance.

[Genuine Realist]

Yup, were going to feel a pinch from our private payers. But government pays most of our bills, and they just scrapped together 2 trillion. They can find some more too I bet. 

Comically myopic is thinking there is some sort of market approach to this pandemic. Maybe you belong on that blue ribbon commission with Jared and the guy who cant stay awake in his meetings.

Myopia, comic or not, is believing every other social value should be subordinated to the battle against C-19. I'm sure you know that suicide and divorce rates are directly correlated with unemployment percentages? And I don't think anyone has ever traced the degree to which mental illness and related ills are exacerbated by extensive social distancing. It's never been done before.

Plus those funds that the government 'scrapes up' are actually generated by commercial transactions on large scale, which commerce is at a standstill. 

So there IS a trade off, even if you restrict the metric to o health alone (ignoring quality of life issues, which is actually absurd).

It's a pretty prosaic point, so I am surprised at the resistance.

[TreesAndBirds]

The "Stanford antibody test" is the Premier Biotech test (per the Stanford Daily)

Not the best written article but this article says Stanford developed its own test, and compared the results to the results of the Premier Biotech test that it was previously using. 

https://news.google.com/articles/CAIiEGm...id=US%3Aen

[TreesAndBirds]

The "Stanford antibody test" is the Premier Biotech test (per the Stanford Daily)

Not the best written article but this article says Stanford developed its own test, and compared the results to the results of the Premier Biotech test that it was previously using. 

https://news.google.com/articles/CAIiEGm...id=US%3Aen

[BostonCard]

What would be an acceptable rate of false positives? 1%? Do we just need to wait until there's a sufficient percentage of the underlying population that has had the virus, i.e., a higher incidence rate? I recall seeing models suggesting we'd need incidence rates into the 20-30% range at least to bring a test with a 3-4% error rate down to sufficient accuracy that individuals could reasonably rely on the results.


I guess I'm starting to worry that a widely disseminated quasi-reliable antibody test might cause as much harm as good, but it's not clear to me who is going to stop such tests from being distributed and relied upon by people desperate to try to return to normal?

OK, to figure out an acceptable specificity, you would have to start with the acceptable positive predictive value and work backward.  The positive predictive value is the proportion of people with a positive test who are infected, and it is not characteristic of the test; it depends on both test characteristics and the baseline prevalence of disease.

So, let's say you wanted to have a 95% positive predictive value (that is, if you had a positive test, you wanted to be 95% sure that you really had been exposed to Covid-19.  You can pick your own value, but let's take 95% to be our target.  Now, let's say that the prevalence of disease is 5%.  In order to hit your positive predictive value, you need very few false positives.  In fact, even if you detect every single positive case (100% sensitivity), because there are so few true positives, you would actually need the false positives to be 5%/19 (because you the positive tests in individuals with Covid-19 need to be 95% of the total number of positives, or 19-fold higher than your false positives), so your specificity has to be along the lines of 99.75%.  If your prevalence is a bit higher (more like 10%) then you will have more true positives and your false positives (and thus specificity) can be lower.

If you want, you can play around with the disease prevalence and test performance characteristics (sensitivity and specificity) and see how it affects the positive and negative predictive value (NPV is the probability that you don't have the disease if you tested negative).

https://docs.google.com/spreadsheets/d/1...sp=sharing

BC

---

Do you want your cancer operated on? Or your heart attack treated?

There is no functional economy or society without functioning hospitals, just not realisetic.

That's almost comically myopic. Don't you realize that the converse is equally true? That there are no functional hospitals without a functioning economy?

I wonder what definition of "functioning hospital" is.  I mean, aren't a ton of non-critical medical appointments/procedures - you know, the ones that keep hospitals afloat financially - being canceled now?  I'm not in medical profession and don't pretend to know anything.  But that's also why I am limited to layman terms/common sense, like linking "re-opening" to capacity to address those needing hospitalization for COVID virus.

And btw, tying these points together, it wouldn't shock me if hospitals put all COVID patients in some non-hospital site (though one fully equipped to handle treatment) so that hospitals can, in fact, go back to more regular operations.  [Maybe this is going on already, IDK].   This, of course, is also dependent on capacity (doctors and staff availability being the most important aspect of that, which will also be tied to how much of those resources need to be devoted to COVID patients).

You can put mild COVID patients out of the hospital, which is what they are doing by telling people to stay quarantined at home and recover.  You can in theory put moderate COVID patients in a large event center or, if push comes to shove a hotel, but it is not going to be ideal in terms of monitoring patients.   It's also not ideal because you want them in a negative pressure room, so that all the virus they are shedding is sucked out of the room by the ventilation system.  But it looks like the hardest hit areas did that. It would be very hard to run an ICU from a non-hospital setting just because of the equipment need (ventilatos, monitors, battery back-ups for everything, specialized beds (especially if you prone patients).  That's not to say that it can't be done, but it would be a very big challenge and would be sub-optimal.

My guess is that for non-ICU patients, unless there is a surge demand, you set one ward up for COVID patients to keep them isolated.  For ICU patients if you are a big enough hospital (like Stanford or UCSF), you devote one of your ICU floors to COVID-19 patients.  For other hospitals, maybe you develop a regional agreement where COVID patients are centralized in a single regional hospital.

I think the biggest challenge is going to be if there are silent spreaders out there, and you don't know if the patient next to you in recovery who seems to be fine after their knee replacement is actually asymptomatically infected and about to get you and everyone else in the recovery room sick.

BC

[BostonCard]

What would be an acceptable rate of false positives? 1%? Do we just need to wait until there's a sufficient percentage of the underlying population that has had the virus, i.e., a higher incidence rate? I recall seeing models suggesting we'd need incidence rates into the 20-30% range at least to bring a test with a 3-4% error rate down to sufficient accuracy that individuals could reasonably rely on the results.


I guess I'm starting to worry that a widely disseminated quasi-reliable antibody test might cause as much harm as good, but it's not clear to me who is going to stop such tests from being distributed and relied upon by people desperate to try to return to normal?

OK, to figure out an acceptable specificity, you would have to start with the acceptable positive predictive value and work backward.  The positive predictive value is the proportion of people with a positive test who are infected, and it is not characteristic of the test; it depends on both test characteristics and the baseline prevalence of disease.

So, let's say you wanted to have a 95% positive predictive value (that is, if you had a positive test, you wanted to be 95% sure that you really had been exposed to Covid-19.  You can pick your own value, but let's take 95% to be our target.  Now, let's say that the prevalence of disease is 5%.  In order to hit your positive predictive value, you need very few false positives.  In fact, even if you detect every single positive case (100% sensitivity), because there are so few true positives, you would actually need the false positives to be 5%/19 (because you the positive tests in individuals with Covid-19 need to be 95% of the total number of positives, or 19-fold higher than your false positives), so your specificity has to be along the lines of 99.75%.  If your prevalence is a bit higher (more like 10%) then you will have more true positives and your false positives (and thus specificity) can be lower.

If you want, you can play around with the disease prevalence and test performance characteristics (sensitivity and specificity) and see how it affects the positive and negative predictive value (NPV is the probability that you don't have the disease if you tested negative).

https://docs.google.com/spreadsheets/d/1...sp=sharing

BC

---

Do you want your cancer operated on? Or your heart attack treated?

There is no functional economy or society without functioning hospitals, just not realisetic.

That's almost comically myopic. Don't you realize that the converse is equally true? That there are no functional hospitals without a functioning economy?

I wonder what definition of "functioning hospital" is.  I mean, aren't a ton of non-critical medical appointments/procedures - you know, the ones that keep hospitals afloat financially - being canceled now?  I'm not in medical profession and don't pretend to know anything.  But that's also why I am limited to layman terms/common sense, like linking "re-opening" to capacity to address those needing hospitalization for COVID virus.

And btw, tying these points together, it wouldn't shock me if hospitals put all COVID patients in some non-hospital site (though one fully equipped to handle treatment) so that hospitals can, in fact, go back to more regular operations.  [Maybe this is going on already, IDK].   This, of course, is also dependent on capacity (doctors and staff availability being the most important aspect of that, which will also be tied to how much of those resources need to be devoted to COVID patients).

You can put mild COVID patients out of the hospital, which is what they are doing by telling people to stay quarantined at home and recover.  You can in theory put moderate COVID patients in a large event center or, if push comes to shove a hotel, but it is not going to be ideal in terms of monitoring patients.   It's also not ideal because you want them in a negative pressure room, so that all the virus they are shedding is sucked out of the room by the ventilation system.  But it looks like the hardest hit areas did that. It would be very hard to run an ICU from a non-hospital setting just because of the equipment need (ventilatos, monitors, battery back-ups for everything, specialized beds (especially if you prone patients).  That's not to say that it can't be done, but it would be a very big challenge and would be sub-optimal.

My guess is that for non-ICU patients, unless there is a surge demand, you set one ward up for COVID patients to keep them isolated.  For ICU patients if you are a big enough hospital (like Stanford or UCSF), you devote one of your ICU floors to COVID-19 patients.  For other hospitals, maybe you develop a regional agreement where COVID patients are centralized in a single regional hospital.

I think the biggest challenge is going to be if there are silent spreaders out there, and you don't know if the patient next to you in recovery who seems to be fine after their knee replacement is actually asymptomatically infected and about to get you and everyone else in the recovery room sick.

BC

[stupac2]

Translation: You're super mean for even posing an uncomfortable question, Teejers...

I don't know why I would expect you to be able to actually engage with someone's point instead of repeatedly attacking straw men, but could you at least try?

Raising the point that people who are least effected by the SiP have a biased perspective once is one thing, saying it over and over and over after it has been repeatedly rebutted is another. I'll note that neither you nor teejers actually even attempted engage my point (just put words in my mouth about age or make a snide comment). It would be one thing if you were actually attempting to have some sort of dialog, but it seems like you're mostly interested in winning a shouting match with talking points that are obviously inane.

[stupac2]

Translation: You're super mean for even posing an uncomfortable question, Teejers...

I don't know why I would expect you to be able to actually engage with someone's point instead of repeatedly attacking straw men, but could you at least try?

Raising the point that people who are least effected by the SiP have a biased perspective once is one thing, saying it over and over and over after it has been repeatedly rebutted is another. I'll note that neither you nor teejers actually even attempted engage my point (just put words in my mouth about age or make a snide comment). It would be one thing if you were actually attempting to have some sort of dialog, but it seems like you're mostly interested in winning a shouting match with talking points that are obviously inane.

[2006alum]

OK, to figure out an acceptable specificity, you would have to start with the acceptable positive predictive value and work backward.  The positive predictive value is the proportion of people with a positive test who are infected, and it is not characteristic of the test; it depends on both test characteristics and the baseline prevalence of disease.

So, let's say you wanted to have a 95% positive predictive value (that is, if you had a positive test, you wanted to be 95% sure that you really had been exposed to Covid-19.  You can pick your own value, but let's take 95% to be our target.  Now, let's say that the prevalence of disease is 5%.  In order to hit your positive predictive value, you need very few false positives.  In fact, even if you detect every single positive case (100% sensitivity), because there are so few true positives, you would actually need the false positives to be 5%/19 (because you the positive tests in individuals with Covid-19 need to be 95% of the total number of positives, or 19-fold higher than your false positives), so your specificity has to be along the lines of 99.75%.  If your prevalence is a bit higher (more like 10%) then you will have more true positives and your false positives (and thus specificity) can be lower.

If you want, you can play around with the disease prevalence and test performance characteristics (sensitivity and specificity) and see how it affects the positive and negative predictive value (NPV is the probability that you don't have the disease if you tested negative).

https://docs.google.com/spreadsheets/d/1...sp=sharing

BC

Very belatedly, thanks for this! Looks like with tests with roughly 96% percent sensitivity and specificity, we would need to reach roughly 50% prevalence to get into the 90% confidence range for positive predictive value. Alternatively, if the tests could get to 98%, even 20% prevalence would get us to into the 90% confidence range. We obviously have to tolerate some amount of error, but I feel like anything less than 90% might be a gamble given a disease where both asymptomatic and presymptomatic carriers can shed the virus for over a week. (Though if we had rapid and widely available testing that would diminish those concerns, too...)

[2006alum]

OK, to figure out an acceptable specificity, you would have to start with the acceptable positive predictive value and work backward.  The positive predictive value is the proportion of people with a positive test who are infected, and it is not characteristic of the test; it depends on both test characteristics and the baseline prevalence of disease.

So, let's say you wanted to have a 95% positive predictive value (that is, if you had a positive test, you wanted to be 95% sure that you really had been exposed to Covid-19.  You can pick your own value, but let's take 95% to be our target.  Now, let's say that the prevalence of disease is 5%.  In order to hit your positive predictive value, you need very few false positives.  In fact, even if you detect every single positive case (100% sensitivity), because there are so few true positives, you would actually need the false positives to be 5%/19 (because you the positive tests in individuals with Covid-19 need to be 95% of the total number of positives, or 19-fold higher than your false positives), so your specificity has to be along the lines of 99.75%.  If your prevalence is a bit higher (more like 10%) then you will have more true positives and your false positives (and thus specificity) can be lower.

If you want, you can play around with the disease prevalence and test performance characteristics (sensitivity and specificity) and see how it affects the positive and negative predictive value (NPV is the probability that you don't have the disease if you tested negative).

https://docs.google.com/spreadsheets/d/1...sp=sharing

BC

Very belatedly, thanks for this! Looks like with tests with roughly 96% percent sensitivity and specificity, we would need to reach roughly 50% prevalence to get into the 90% confidence range for positive predictive value. Alternatively, if the tests could get to 98%, even 20% prevalence would get us to into the 90% confidence range. We obviously have to tolerate some amount of error, but I feel like anything less than 90% might be a gamble given a disease where both asymptomatic and presymptomatic carriers can shed the virus for over a week. (Though if we had rapid and widely available testing that would diminish those concerns, too...)