Is there a TLDR version?

nortex97 said:

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BlackGoldAg2011 said:

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lockett93 said:

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BlackGoldAg2011 said:

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Lets say you lockdown 65 and older and tell the rest to go back to work. in the USA there are 214MM people ages 20-64. so lets use swine flu number to estimate. 14% infection rate gives us 30MM cases. 13% of those likely need hospitalization so thats 3.9 MM people needing hospital beds. Using an optimistic CFR of 0.2% that would put us at 60k deaths which is an 8.6% increase on the annual mortality of that age group. now lets assume that those 3.9MM start to overwhelm hospitals causing that CFR to rise. a jump to 0.5% takes the death toll to 150k or a 21% increase on the annual mortality of the age range. and this all assumes the quarantine works perfect and there are no deaths in the old or the young. You are not wrong for thinking about this, but the problem is just how fast this thing spreads.

edit to add this also does not account for increase fatalities from other causes that would have been preventable had there been hospital bed space

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The hospitalization rate for those under 65 is not 13% from what I'm reading, that's the rate for all cases, which we know is mostly those over 65 requiring it...

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sure looks like it is to me:
https://www.cdc.gov/mmwr/volumes/69/wr/mm6912e2.htm#T1_down
ICU rate may be a little lower at 5-10% for that age group

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Secondly, the expected IFR would not be 0.2% for the under 65 healthy group. It would be lower. But good point on if the hospitals beds and ventilators all get used...

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sure looks like that's what the data suggests to me:

if you have different data to counter the numbers a threw out i'm all ears. but you can't make quantifiable statements without any form of support

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ICU rate again depends on the (real) denominator. How does Germany have only .08 percent of it's active cases as serious (1.9 deaths per million)? That's based on the worldometer site data.

Some of the reasons Italy was so far off, imho, was that (a) they are elderly (we all agree), (b) have very few ICU beds anyway per capita , so (c) quickly ran out of space to treat people who otherwise might not have gotten so sick/died.

https://docs.google.com/spreadsheets/d/17R0Z5T063iqskP--0VXYtbnJqtkhU8RJ-5jL5_V1OZM/edit#gid=2103271839

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I read that Germany's severity started out skewed low because the majority of their early cases came from import from the ski season, so the first group that got sick self selected as younger and healthier than the average population. but as of right now they are at about 0.5% CFR so they are moving up daily in their severity rates. no idea how they are tracking their "severe cases".

CDC report for 2017 - 2018 season.

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The overall burden of influenza for the 2017-2018 season was an estimated 45 million influenza illnesses, 21 million influenza-associated medical visits, 810,000 influenza-related hospitalizations, and 61,000 influenza-associated deaths

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Deaths by age:

00-04 = 115
05-17 = 528
18-49 = 2,803
50-64 = 6,751
65+++=50,903
total == 61,099

Will this get as bad as 2017-2018 season? Who knows, but at the peak of that season 500+ were dying a day, for weeks.

Estimated Influenza Illnesses, Medical visits, Hospitalizations, and Deaths in the United States 20172018 influenza season

I really think this is baselining the flu vs. only CDC and public health lab testing.

https://texags.com/forums/16/topics/3102605/last

Appreciate the work/time/discussion, just want to note that.

It seems highly likely we hit 500 per day

Just so we're clear that's an estimate, and the 95% confidence interval is +/-25%. Right now at least covid19 deaths are lab confirmed.

BlackGoldAg2011 said:

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Ag12thman said:

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Is there a TLDR version?

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TLDR: By raw numbers this is not currently worse than the flu, but is only 6 weeks for COVID vs 24 for flu. Current trends show this being much much worse than flu without significant efforts to stop it.

TLDR caveat: this is obviously my interpretation of the data. if you want fully unbiased, you will have to look at the actual data and do your own analysis. no TLDR for that

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Exactly what I was looking for until I can read through the whole thread closely later this week / weekend. Thanks!

k2aggie07 said:

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Just so we're clear that's an estimate, and the 95% confidence interval is +/-25%. Right now at least covid19 deaths are lab confirmed.

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This discussion goes on ad nauseum. Everyone has their opinion of accuracy. The flu, and flu seasons have many consecutive years of data. This is the CDC, and I see no reason to think they screw with the data.

I also want to point out that I don't think C-19 is like the flu, as the health care people are at much more risk.

I'm just pointing out that looking at deaths, the term "just the flu" is disrespecting the flu. The flu is bad news period, especially for olds.

BlackGoldAg2011 said:

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It seems highly likely we hit 500 per day

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And if it over 500 per day for 5 or 6 weeks it will be worse........on a death basis.

And yet some areas are seeing a big drop in ER patients.

Nobody is having elective surgeries right now, and I damn sure wouldn't go into the ER right now unless I was pretty sure I *had* C-19 or thought I was otherwise at risk of dying.

Also as a country we have been doing various levels of social distancing and isolation for 2 weeks now. Some places more. You should absolutely expect to be seeing a drop off in all infectious diseases with the most dramatic being in ones like cold and flu that have relatively short incubation periods. It's why for comparison purposes this years data is worthless for the flu except as another data point that what we are doing is working.

Even if the actual current death rate for covid-19 were to be proven to be equal or less than the typical flu, it is still many times more dangerous.

The problem is that it puts a higher percentage of people in critical condition. This has the potential to exceed the capabilities of our healthcare system. If that happens, many of the people that would have lived, now can't get treatment. This would most likely result in a much worse death rate than the common flu.

So you can compare covid-19 to the flu and as long as all those infected get necessary medical treatment then the flu might look worse. That unfortunately is not the reality we are facing.

k2aggie07 said:

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Probably a lot of frequent fliers and minor problems with no insurance opting to stay home.

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The chart wasn't about hospitalizations but ER visits.

Plummeting ER visits over the past month? ILI admissions are what? Again, if this (COVID-19) is not related to temperature/flu season but is a mass-population threat all over then if Arizona is dropping precipitously it's another indicia of the falsehood of the panic narrative.

Here's the link to the CDC's weekly flu and pneumonia mortality rates info.

FluView

Updated through week 9 (Feb 23-29). Can be broken down by state. Lots of ways to play with it.

Also, here's the link to the CDC's Influenza-Like-Illness info for Week 11 (ending March 14). Week 11

Definite uptick in reported cases beginning in Week 10 under "Outpatient Illness Surveillance". Here's the Chart Data: Week 11 Reported Visit

Year to year, it looks like ILI visits start to decline around Week 6. That also happened this year, until Week 10. For everybody but ages 0-4, they start to climb in Week 10. Looking at everybody above age 25, there were about 35,000 ILI visits in Week 9. That increased to 37,000 in Week 10. Week 11 was 46,000. For the 25-49 group, there were almost 7,000 more visits in Week 11 than Week 9.

It sure looks like something was going on. Very curious to see the Week 10/11 mortality rates when those are available. Would have been nice to have been able to test some of these people.

I was talking about ER visits not hospitalizations. That's where people with no insurance go. Those folks are probably staying home.

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S. Korea is a great counter scenario to show a country that mostly controlled it in the wild. they also have great testing numbers at 357,896 tests run and currently 14k more pending. this puts them at 0.7% of their entire population tested. so their CFR is very likely close to an accurate number.

As for the sine flu, yes lets look at it. estimated US infections: 61 MM. now apply S. Korea's CFR for COVID to that number and see what you get: you get 800k deaths in the US which would make COVID the number 1 cause of death in the US this year by nearly 200k deaths. we currently have zero data to validate the hypothesis that the CFR for this is equal to or lower than flu, in fact all data currently support the opposite, showing this to multiples more deadly or in some cases multiple orders of magnitude more deadly than flu. but also more contagious. just look at those growth rates i posted. This is what fuels the drastic measures, because if this thing moves like swine flu and is only a fraction as deadly as what we are seeing, that would be devastating

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That is it in a nutshell. Ignore it if you want to.

nortex97 said:

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k2aggie07 said:

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Probably a lot of frequent fliers and minor problems with no insurance opting to stay home.

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The chart wasn't about hospitalizations but ER visits.

Plummeting ER visits over the past month? ILI admissions are what? Again, if this (COVID-19) is not related to temperature/flu season but is a mass-population threat all over then if Arizona is dropping precipitously it's another indicia of the falsehood of the panic narrative.

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Or so many people are staying home all cases of er visits are down. Fewer infections being shared, fewer miles driven so fewer accidents, etc. if the "flatten the curve" is working you would expect fewer er visits for all reasons. Especially here if Arizona got ahead of the covid infection in their state

I don't think CFR really captures the deadliness of Covid at all, but rather how well a location is doing at slowing it down (population density also factors heavily in this, NYC is not necessarily worse than a small town if they have more cases or higher CFR).

I don't recall the flu shutting entire populations down in order to slow it down. Cisgendered also made a good point about the baseline for starting cases.

The only reason CFR for Covid isn't 5% or some really ugly number when hospitals run out of capacity to treat the % of people that react poorly and become extremely ill is everything is shut down and people are sanitizing like hell. I don't know any location of the world where there weren't these type of significant steps taken to contain the virus.

If a minivan wins a race when it has a huge head start and can floor it really faster than a ferrari that you won't let out of first gear?

Or, so many people have had/have COVID that it is really much less deadly than thought; closer to .05 percent.

Once again, the real question is 'what is the actual denominator?'

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Not only are they not (yet) seeing atypical rates of fever, they're waaaaaay below where Kinsa's historical data would project them to be in a normal year. What's happening here, one would think, is that the social distancing being practiced by locals is sharply reducing the total number of seasonal infections caused by all "influenza-like illnesses." COVID-19 isn't the only bug out there; the flu is circulating, as are other well-known and milder forms of coronavirus. Because Kinsa can only measure fevers and not the underlying cause, it can't say definitively that rates of infection by COVID-19 specifically are decreasing. It's possible that that rate is still rising but is being offset (and then some) in their data by dramatically declining rates of infection by all other forms of "influenza-like illness." The overall trend is downward but maybe not the particular trend for COVID-19, especially since it's more contagious than flu. And that's the one we care about.

But. Obviously it's possible that social distancing is driving down the infection rate of COVID-19 too. That's what these lockdowns are designed to do, after all. The self-isolation strategy is probably working, too late for New York but hopefully not too late for a lot of places. Even Florida, the most worrisome fever hot spot in last week's Kinsa data, is beginning to cool off.

We're making BIG decisions as a country based on an assumption about how dangerous COVID-19 is to most of the population. If one in 50 or so need hospital treatment then we really are staring at a potentially apocalyptic load on our system and we need to do everything we can to start managing the spread for months to come. If only one in 5,000 need hospital treatment, then many millions of people may already have recovered and gained immunity, with no "second wave" on the way this fall. What we'll experience over the next month or so may be the worst of it, with herd immunity shortly to follow.

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Fear of Covid-19 is based on its high estimated case fatality rate2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, two million to four million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases
[T]he northeastern Italian town of V, near the provincial capital of Padua. On March 6, all 3,300 people of V were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That's more than 130-fold the number of actual reported cases. Since Italy's case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%
The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that's a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

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That's the same argument made in the Oxford study, and the same made by Stanford epidemiologist John Ioannidis in a widely read piece last week. We know the numerator in calculating the fatality rate from COVID-19; the momentous question is what the denominator is. What if the new coronavirus is extremely infectious, almost always mild (unless, perhaps, you get a high dose of it like front-line health-care workers do), but severe in some freak cases? There may be enough infected people out there, say the authors, that we should expect a death toll in the range of 20,000 to 40,000 people, which is serious business but in line with the death toll from the flu and orders of magnitude below the death toll of two million people predicted in some worst-case scenarios. The reason hospitals are being crushed by COVID-19 when they aren't crushed every year by the flu is because we have few ways of slowing down transmission of COVID-19 like we do with the flu (vaccines, naturally gained immunity, and so on). An enormous number of people are sick with it at the same time. It's just that only a very unlucky few actually end up feeling it.

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Your CDC run flu test comparison is flawed as the number of non CDC COVID19 tests the last two weeks has swamped the total CDC run tests.

Also, your exponential for includes two data points with vastly increased testing (not as much as we want, but much more than before). That could make the slope on the exponential plot look larger than it really is.

That said, thanks for the data. I have been frustrated since early Feb with all the "flu kills this many per year but CoV has only killed this many" posts I have seen on social media.

nortex97 said:

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Or, so many people have had/have COVID that it is really much less deadly than thought; closer to .05 percent.

Once again, the real question is 'what is the actual denominator?'

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Not only are they not (yet) seeing atypical rates of fever, they're waaaaaay below where Kinsa's historical data would project them to be in a normal year. What's happening here, one would think, is that the social distancing being practiced by locals is sharply reducing the total number of seasonal infections caused by all "influenza-like illnesses." COVID-19 isn't the only bug out there; the flu is circulating, as are other well-known and milder forms of coronavirus. Because Kinsa can only measure fevers and not the underlying cause, it can't say definitively that rates of infection by COVID-19 specifically are decreasing. It's possible that that rate is still rising but is being offset (and then some) in their data by dramatically declining rates of infection by all other forms of "influenza-like illness." The overall trend is downward but maybe not the particular trend for COVID-19, especially since it's more contagious than flu. And that's the one we care about.

But. Obviously it's possible that social distancing is driving down the infection rate of COVID-19 too. That's what these lockdowns are designed to do, after all. The self-isolation strategy is probably working, too late for New York but hopefully not too late for a lot of places. Even Florida, the most worrisome fever hot spot in last week's Kinsa data, is beginning to cool off.

We're making BIG decisions as a country based on an assumption about how dangerous COVID-19 is to most of the population. If one in 50 or so need hospital treatment then we really are staring at a potentially apocalyptic load on our system and we need to do everything we can to start managing the spread for months to come. If only one in 5,000 need hospital treatment, then many millions of people may already have recovered and gained immunity, with no "second wave" on the way this fall. What we'll experience over the next month or so may be the worst of it, with herd immunity shortly to follow.

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Fear of Covid-19 is based on its high estimated case fatality rate2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, two million to four million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases
[T]he northeastern Italian town of V, near the provincial capital of Padua. On March 6, all 3,300 people of V were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That's more than 130-fold the number of actual reported cases. Since Italy's case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%
The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that's a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

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That's the same argument made in the Oxford study, and the same made by Stanford epidemiologist John Ioannidis in a widely read piece last week. We know the numerator in calculating the fatality rate from COVID-19; the momentous question is what the denominator is. What if the new coronavirus is extremely infectious, almost always mild (unless, perhaps, you get a high dose of it like front-line health-care workers do), but severe in some freak cases? There may be enough infected people out there, say the authors, that we should expect a death toll in the range of 20,000 to 40,000 people, which is serious business but in line with the death toll from the flu and orders of magnitude below the death toll of two million people predicted in some worst-case scenarios. The reason hospitals are being crushed by COVID-19 when they aren't crushed every year by the flu is because we have few ways of slowing down transmission of COVID-19 like we do with the flu (vaccines, naturally gained immunity, and so on). An enormous number of people are sick with it at the same time. It's just that only a very unlucky few actually end up feeling it.

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This ignores South Korea which seems like our best example of how to handle the virus. Their CFR is going to be at least 1.5%.

South Korea is largely packed into one huge urban sprawl a la NYC. I don't think they represent anything near an accurate data point vs. the whole US. I also don't really trust the tests they used.

nortex97 said:

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South Korea is largely packed into one huge urban sprawl a la NYC. I don't think they represent anything near an accurate data point vs. the whole US. I also don't really trust the tests they used.

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You think they had more positives than they showed even tho they controlled it better than anybody else in the world? As in their clusters were shut down and isolated and the infection rate went to almost nothing.

I find it hard to believe they had this large population of positives that they didn't find but I guess anything is possible.

nortex97 said:

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I also don't really trust the tests they used.

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please explain in detail why you distrust their tests?

I'm just a guy forced to work from home now, but there is a lot of skepticism about their tests; you can trust them and their figures if you'd like to do so. No worries.

When you rush to approve/produce a rapid test kit in weeks you get things like 30% sensitivity. Same thing with the Chinese kits (or much worse).

https://www.reddit.com/r/CoronavirusDownunder/comments/fiedl5/south_korean_covid19_test_kits_not_accurate_falls/

https://fortunascorner.com/2020/03/25/80-of-coronavirus-test-kits-gifted-to-czechs-by-china-faulty/

nortex97 said:

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I'm just a guy forced to work from home now, but there is a lot of skepticism about their tests; you can trust them and their figures if you'd like to do so. No worries.

When you rush to approve/produce a rapid test kit in weeks you get things like 30% sensitivity. Same thing with the Chinese kits (or much worse).

https://www.reddit.com/r/CoronavirusDownunder/comments/fiedl5/south_korean_covid19_test_kits_not_accurate_falls/

https://fortunascorner.com/2020/03/25/80-of-coronavirus-test-kits-gifted-to-czechs-by-china-faulty/

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The questions about the South Korean tests were from 12 days ago.

I would think that would've shown in current figures now unless you think they're faking their data like China apparently has. I don't think you're saying that.

nortex97 said:

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I'm just a guy forced to work from home now, but there is a lot of skepticism about their tests; you can trust them and their figures if you'd like to do so. No worries.

When you rush to approve/produce a rapid test kit in weeks you get things like 30% sensitivity. Same thing with the Chinese kits (or much worse).

https://www.reddit.com/r/CoronavirusDownunder/comments/fiedl5/south_korean_covid19_test_kits_not_accurate_falls/

https://fortunascorner.com/2020/03/25/80-of-coronavirus-test-kits-gifted-to-czechs-by-china-faulty/

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These are excellent points that most people are not thinking about. The tests we use are not FDA approved which means we have no idea what the sensitivity is. Most of the ID docs I have read think there is likely 70% sensitivity which means 30% of the negatives are actually positives. If/when we get widespread testing if this data point holds true we may get a significant spread due to people testing negatives and spreading it anyway.

I don't think they have as many folks testing now, and besides, when you have your whole population wearing masks transmission will be lower anyway. But no, I don't think they are lying about their numbers a la China. It's just that their numbers aren't really as good/meaningful/accurate at all as many think they are.

Most of us have had a kid/ourselves test negative for strep many times, but doc smells the breath and diagnoses as positive etc., you get the pills/shot. There's no such 'sanity check' for these kits. Some are under the misnomer that all diagnostic tests work really well, and that even CT scans are fool proof etc, and that's just...not how it works.

Until we get to genomic testing, a lot of this is just three blind mice with calculators and keyboards is my contention, and I think the truth is that the spread is vastly larger than folks think it is (but innocuous to almost everyone).

nortex97 said:

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I don't think they have as many folks testing now, and besides, when you have your whole population wearing masks transmission will be lower anyway. But no, I don't think they are lying about their numbers a la China. It's just that their numbers aren't really as good/meaningful/accurate at all as many think they are.

Most of us have had a kid/ourselves test negative for strep many times, but doc smells the breath and diagnoses as positive etc., you get the pills/shot. There's no such 'sanity check' for these kits. Some are under the misnomer that all diagnostic tests work really well, and that even CT scans are fool proof etc, and that's just...not how it works.

Until we get to genomic testing, a lot of this is just three blind mice with calculators and keyboards is my contention, and I think the truth is that the spread is vastly larger than folks think it is (but innocuous to almost everyone).

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The current testing is genomic AFAIK- mostly PCR or NAAT. The problem is getting a good swab that has adequate viable viral RNA on it. In my lab order interface it is listed as COVD-19 by NAA (nucleic acid amplification) and the swab is a deep nasopharyngeal swab which is not very pleasant.

Maybe you mean blood titers by "genomic"? If so yes those are nearly 100% accurate but usually not until 5-7 days of illness if this one behaves like every other viral infection. Most of my experience with infectious titers are the mono viruses CMV & EBV.

nortex97 said:

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I'm just a guy forced to work from home now, but there is a lot of skepticism about their tests; you can trust them and their figures if you'd like to do so. No worries.

When you rush to approve/produce a rapid test kit in weeks you get things like 30% sensitivity. Same thing with the Chinese kits (or much worse).

https://www.reddit.com/r/CoronavirusDownunder/comments/fiedl5/south_korean_covid19_test_kits_not_accurate_falls/

https://fortunascorner.com/2020/03/25/80-of-coronavirus-test-kits-gifted-to-czechs-by-china-faulty/

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sorry if i came across as argumentative, i don't "want to trust them". I want the best data available. If there was reason to doubt the data i wanted to know, and this discussion led me to this study (https://www.mdmag.com/medical-news/comparing-rt-pcr-and-chest-ct-for-diagnosing-covid19)
which gives some solid data to suggest the negative tests could have a rather alarming false-negative rate. I don't know enough about the korean testing to say one way or the other if this applies to them, but it is actual data to suggest the possibility that they are alarmingly under-identifying. I asked the way i did because too often people try to discount data simply because it doesn't agree with their initial position. i'm not trying to accuse you of that, but i also don't know a thing about any of you other than an online persona.

that being said i think at this point we can all agree that we don't have a solid handle on "the denominator" and it could be a pretty wide range of numbers.

but even with that, i just wanted to point out that we have a lot of data pointing to the possibility that this could be much worse than flu unchecked. we may decide it's not when we have more data in and the benefit of hindsight, but from a forecasting perspective right now, the data available (good or bad) points towards this warrants a stronger reaction from us than the seasonal flu

Yes sorry, it's impossible to go down this rabbit hole of statistics and testing methodology/sample types without losing the big picture in a broad discussion. Appreciate your input. Genomics is still today a broad term encompassing a lot of different modalities; ISH, NGS, PCR, etc. (Full disclosure: I work for a company that makes a lot of the NGC sample prep/library QC materiel, and like everyone can't wait until NGS is basically a routine turnaround like, a regular chem panel).

The bottom line for all here is that the quality of the sample, it's preparation/handling, and how much it is amplified/replicated, in addition to how it is read, matters a lot. Biofire/Cepheid types of automated near-patient testing are neat today, but not widespread and still very expensive.

Big drive thru testing of a new test with quick results looks great from a helicopter on the news, but I'm dubious of the quality of the test/results.

PJYoung said:

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nortex97 said:

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South Korea is largely packed into one huge urban sprawl a la NYC. I don't think they represent anything near an accurate data point vs. the whole US. I also don't really trust the tests they used.

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You think they had more positives than they showed even tho they controlled it better than anybody else in the world? As in their clusters were shut down and isolated and the infection rate went to almost nothing.

I find it hard to believe they had this large population of positives that they didn't find but I guess anything is possible.

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The other explanation is they had bad tests, had 3x the cases, the CFR is significantly lower that what people are saying because the asymptomatic cases are 50%+ of the total cases, and the infection burned through the population already, resulting in the decline they are seeing.


Hard to tell, and wanting tests that were decent is part of the delay in getting testing in the US. I guess the question is which is better, testing soon with a lot of false negatives so people think they don't have it and continue to spread it, or delaying testing until you have a good test and have a bunch of people not knowing if they have it and continuing to spread it.