> Cough (7.5%), shortness of breath (1.4%), and fever (0.7%) were all uncommon among COVID-positive individuals
It seems the more important point here is that the majority of the COVID-positive individuals were asymptomatic, putting another datapoint towards the conclusion that there are orders of magnitude more people that have this disease than have tested positive.
We need more studies to gather data on these asymptomatic cases if we want to reopen the economy soon. Imagine if 10+% of the population already had COVID and where immune, we'd be much closer to heard immunity than we currently think.
We already have lots of data that says this is not true. For instance, on the Diamond Princess, widespread testing of a confined group initially found many asymptomatic infections, but the majority of those turned out to be pre-symptomatic, not asymptomatic.
Longer term follow-up found ~25% of infections were asymptomatic.
In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms. Even limiting our sample to people presenting with severe matching symptoms of COVID-19, we're finding ~20% PCR-positive for SARS-CoV-2.
Beyond that, we also have good evidence that the Basic Reproduction Number is somewhere between 2-3. Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet.
> In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms
Its not a significant amount of testing if we're only testing those with severe symptoms
Here in SF at least there are scores of people I know who all were sick with a "weird flu" at some point from February to now who would all kill for a test to show that they have COVID immunity. These are people who could potentially go back into society and do more work / enjoy their lives instead of being shuttered inside with anxiety
It is currently _IMPOSSIBLE_ to get any kind of test to prove that
Since they have coronavirus relatively under control and have been doing extensive testing and contact tracing for months, it's plausible that they've caught most cases. It's wishful thinking to believe the infection fatality rate is an order of magnitude lower.
The Diamond Princess likely had a very atypical (older) population than the general population though.
The CDC is currently estimating an R0 of 5.7, which has likely been repressed by shelter in place orders. But even if it was only 4 before any interventions, there's still a chance there there are closer to 20M cases in the US rather than the 660,000 now.
My point is just that there's still a lot we don't know, and small changes in our understanding could implicate massive changes in the reality on the ground.
>We already have lots of data that says this is not true... Longer term follow-up found ~25% of infections were asymptomatic.
Based on other available data the severity of the Covid symptoms are dependent on both the length of exposure and total exposure to the virus. A cruise ship with recirculated air likely means prolonged exposure to high concentrations of the virus that won't fit most other patients exposure.
"Initial estimates of the basic reproduction number (R0) for COVID-19 in January were between 1.4 and 2.5,[381] but a subsequent statistical analysis has concluded that it may be much higher.[382]"
> Study results revealed an overall pooled prevalence for asymptomatic carriers of 19.1% for any type of influenza, 21.0% for influenza A, and 22.7% for influenza A(H1N1). For subclinical carriers, the overall pooled prevalence of was found to be 43.4% for any type of influenza, 42.8% for influenza A, and 39.8% for influenza A(H1N1).
What's "significant amount of testing"? In Santa Clara country, for example, 16585 tests have been done[1], that's less than 1% of the population. I know from personal experience of several people that it's next to impossible to get tested if you don't have very severe symptoms. Positivity rate is 10.8% - over people which are sick enough to get tested.
> Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet
This sounds like circular logic - how we know it indeed started in January and not before? How do we know how many had it asymptomatically if we didn't test 99% of the population? We're making assumption based on knowledge gathered by select sample of 1% chosen by severity of symptoms - how can we make conclusion about how it works in the rest of the population and what's the dynamics there?
> We need more studies to gather data on these asymptomatic cases if we want to reopen the economy soon.
I don't understand what's so hard about measuring population infection rate.
Assuming the population infection rate is between 1-10%, we would only need to do around ~500 randomized tests to achieve a 95% confidence interval of +/- 1%.
For example, let's say we tested 500 random NYC residents for COVID and found that 10 were positive -- a 2% infection rate. The standard error (binomial approximation) for this sample is 0.6%. So, by doing a mere 500 randomized tests, we have a 95% confidence interval of 0.8%-3.2%.
Given that overall population infection rate is so important in planning for re-opening, why are we not doing randomized testing in hotspots like NY on a regular basis? Am I missing something?
There's good reason to suspect strong regional variation, which means that finding a representative sample of 500 is hard. But that would still be technically possible (look at South Korea and China); we clearly lack to political will to do proper testing in USA.
Well we need to measure if people have it and if people have had it. The have it test is currently $3000 a pop, and the had it test is hitting accuracy road blocks [1].
Amen. The whole scenario seems like a bad statistics lesson.
Happy to change my mind -- but there simply hasn't been any effort to use population testing in this way -- which is one of the only useful forms of testing. Otherwise, why test people in the hospital? It doesn't change treatment. Finding asymptomatics is actually useful -- and random sampling seems critical for understanding whether we are simply fucked or actually fubar'd.
My bet is that it's much more than 10%. In NYC I think it's at least 20%-30% by now. Obviously, I don't have any more data than what you can find online, but anecdotally, I think one of my sons had it; he most likely got it from his piano teacher who exhibited all the Covid symptoms (fever, dry cough, loss of smell), but was never tested. I think at least myself and my wife got this from him as well; likely his two siblings, but they were completely asymptomatic. Our kids' nanny has Covid now (tested at the hospital), and her son too (he's in ICU). I have other anecdotes, and no, I don't have systematic data, but I believe at least 20%-30% of NYC has had Covid by now.
Another point of reference is this: according to [1], a back-of-the-envelope estimate of the number of Covid-infected is 100 times the number of dead. It's about 8000 now in NYC, so about 800k infected. That's about 10% of NYC's population, exactly the number you mentioned.
15% of pregnant woman in NYC that delivered had active Covid infections (https://www.nejm.org/doi/full/10.1056/NEJMc2009316) detectable by PCR. It's highly unlikely under 20% of the population was infected. I'd bet closer to the 30% in fact.
Does this study change your mind on that 20-30% figure? After all, the study measured a 35% infection rate for people living in close quarters with other infected individuals. Surely, the overall population would yield a much lower infection rate than this?
Or the majority were presymptomatic. They don't give a timeline of how long after the first cases in the cluster were detected that the testing took place, so these individuals might have been in the first week of the infection.
> Imagine if 10+% of the population already had COVID and where immune
By some estimates we need over 80% of the population to get it in order to achieve herd immunity, so if only 10% of the population has it we're not very close at all to this being over.
The first 10% to be infected, are also likely to be the highest spreaders (people in close contact with a high amount of strangers). The effect should hopefully be higher than 10% reduction in the reproduction rate.
There are several variables here but it's also important to keep in mind that the 36% positive rate in this cohort presumably does not include people who had the virus and recovered.
A Diamond Princess ex-passenger died as late as March 24. The first patient was tested positive on February 1, and the ship was quarantined on Feb 4, and everyone left the ship on March 1. It doesn't seem unlikely you can die from this virus a month (or even two months?) after testing positive. Or maybe I'm missing something?
It is very important to distinguish asymptomatic (does not have symptoms and will never develop them) from presymptomatic (does not have symptoms yet, because the test caught the infection sufficiently early). The people in this study are mostly presymptomatic, and will develop symptoms later.
Asymptomatic means the person had no symptoms at the time of the test, and possibly never developed symptoms. They could also have been presymptomatic, in which case they subsequently developed symptoms after the test. This study didn't do any follow-ups to differentiate.
0.2% of nyc has already died from Covid-19. That will probably get to around 0.4% or so. This is a lower bound for lethality of the disease.
We also know from contact tracing and mass testing instances that only something like half of cases stay asymptomatic forever. It is likely that the people in this study are either asymptomatic because they no longer have the disease or because they haven’t developed symptoms yet. Also, they might just not be recognizing their symptoms. Even without covid-19, way more than 7.5% of homeless people are typically coughing.
> Imagine if 10+% of the population already had COVID and where immune, we'd be much closer to heard immunity than we currently think.
We’d be about 1/7 the way there. Meaning we’d see another 6x current deaths to get through this. That’s not even close to acceptable.
And the 10% aren’t realistic, anyway. At least nationally. Assuming nationwide rates of 10%, then scaling up by death numbers, would put infection rates far above 100% in New York.
Why would the rest of the country have the exact same percentage of infected as New York City, the only place in the country where most people don't own cars, and almost everyone takes cramped public transportation. NYC clearly has a MUCH higher infection rate than anywhere else in the country.
(Regarding the Headline) Surely you mean 35% of homeless who were tested. We can't say for certain that the sample is an exact representation of the general population of the homeless in Boston.
"Upon observing a cluster of COVID-19 cases from a single large homeless shelter in Boston, Boston Health Care for the Homeless Program conducted symptom assessments and polymerase chain reaction (PCR) testing for SARS-CoV-2 among all guests residing at the shelter over a 2-day period. Of 408 participants, 147 (36.0%) were PCR-positive for SARS-CoV-2"
The key thing here is they tested people from one single homeless shelter. Is this one homeless shelter in Boston representative of all homeless shelters in Boston? There is not enough info in this article to make that assumption. Nor is it enough information to make generalizations about the populations of the homeless who do not live in shelters.
> We can't say for certain that the sample is an exact representation of the general population.
I actually think we can say for certain this is NOT a good representation of the general population. The general population has not been living in close quarters with multiple COVID positive people.
This is fair feedback on the headline, as the linked article does NOT make that claim. Instead, it makes the same point as @zadkey that "illustrate the rapidity with which COVID-19 can be widely transmitted in a homeless shelter setting and suggest that universal PCR testing, rather than a symptom triggered approach, may be a better strategy for identifying and mitigating COVID-19 among people experiencing homelessness."
The Boston Globe this morning ran an op-ed advocating testing a random sample of residents to get a better sense of community-wide infection rates.[1] It's amazing that this needed to be stated in a major market newspaper four weeks after most business and school was stopped due to the virus. Goverent is doing some interesting things, random sampling apparently isn't one of them, for reasons it's hard to understand.
Everybody knows this, but the US healthcare system was so unprepared for this that there simply weren't (aren't) enough test kits around to do a proper study. Even people who have the symptoms struggle to find a place that will test them in some cities.
It's probably low prevalence in the population based on our understanding of when covid-19 first appeared.
The UK has some randomized seriological surveillance and it's about 13% prevalence. That matches with the pregnancy study of 15% prevalence (which may be enriched due to hospital visits).
The idea that nobody has thought to do them seems absurd. I'm getting more and more suspicious the longer we see no results from randomized studies in US cities - it's getting more and more likely that either the tests are turning out to be inaccurate, or the results are turning out to be problematic.
But either way folks are probably being very careful because the results will have significant impact.
In the developing countries without universal health care, there are government health workers, who are into vaccination, prevention, etc. In situations like this, these workers are mobilized for random testing. However, in the states, I don't see such a workforce. It is mostly done by volunteers, such as that Stanford drive in testing.
NYC has something like 15x the death rate per capita of the the US ex-NYC. Even if you think that NYC is approaching herd immunity (debatable), that means the rest of the country is only 5-10% of the way there.
Many of those people testing positive were presymptomatic (some even developed symptoms during the follow-up period). It typically takes several days to develop symptoms.
Also worth considering is the period mentioned in the correspondence is one in which there was very fast exponential growth. When more of the positive cases are recent, it's only normal that they don't show symptoms yet.
Besides the test used showing a lot of false positives, the population of pregnant women looked at had a much higher rate of symptomatic infections 1 month ago than the entire population does today... we should be very cautious about concluding much from that sample.
That is mind-boggling. You don't test positive if you've cleared the virus, either, so that 14% is actually a lower limit because some portion of them might have had it long enough ago to clear. I don't know what pregnancy does to the immune system -- but we do know that these women were all young enough to give birth (likely <40 years old).
That's really not that much, I would expect the infection rate in NYC to be anywhere between 10-20%, that makes sense given the numbers we're seeing in hospitals.
I really don't understand why people immediately want to discredit the idea that US patient zero was not the first in US. Or that this virus was around earlier and that there are limitations in contact tracing capabilities.
This seems to have the toughest aspect of gaining consensus.
Need antibody tests now, and ones that work reliably.
It seems to indicate this disease infected a lot more than what we see, and maybe mortality rate is lower than what we currently assume. Maybe it's around 0.1% to 0.5%.
So is it possible this disease appeared in China way before December, maybe a few months back. Then in December it reached a saturation point (i.e. infected hundreds of thousands of people, so deaths started to get noticed by respiratory specialists). Then around January/February this disease spread to the world, but it went unnoticed. Then in March it reached the same saturation point that the deaths became too many not to notice.
Regarding the title "Covid+", it seems that most people (even on the news) don't care about the difference between SARS-CoV-2 (the virus) and COVID-19 (the disease). Is this distinction being abandoned? (I'm not trying to be pedantic here; I'm just curious about the common usage.)
Nobody ever cared. The names are confusing (the virus is named after the disease, and the disease after the virus), and the virus name obtuse. The obvious consequence is that nobody ever used the virus name, and never will.
The best you can hope for is for people to call it the "COVID19 virus".
As always, the distinction between two tightly bound things is not important when you talking about features common to both, such as which people have them.
Humans tend to migrate toward shorter more pronouncable, easier to type terms. Language evolves like a virus ;-)
"I am realizing more and more how unusual, unscientific, unmedical, and counterproductive it is for WHO to select the name #COVID19 and reject SARS2. In fact it would be most consistent with medical practice to just call it SARS. Here's why..."
People were never good about making a distinction here. HIV and AIDS are synonymous in popular culture, even though HIV is the virus and AIDS is the disease. No reason to think that SARS-CoV-2 and COVID-19 are going to receive different treatment.
I certainly don't have a better read on the numbers than anybody else. But I think that the rising number of reported cases and deaths is going to make it harder and harder to think that there is a huge hidden pool of asymptomatic or immune people in the population.
For instance as of today, the number of unreported to reported cases in the US can't be more than about 500.
The time period when the disease could have been prevalent in the US can't have been very long, because at its present level it kills about 15000 per week -- a number that could not have gone unnoticed even a month ago.
Eventually, the curves of hopes, reported data, and reality will all have to intersect, I just don't know where or when.
Readit News
It seems the more important point here is that the majority of the COVID-positive individuals were asymptomatic, putting another datapoint towards the conclusion that there are orders of magnitude more people that have this disease than have tested positive.
We need more studies to gather data on these asymptomatic cases if we want to reopen the economy soon. Imagine if 10+% of the population already had COVID and where immune, we'd be much closer to heard immunity than we currently think.
Longer term follow-up found ~25% of infections were asymptomatic.
In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms. Even limiting our sample to people presenting with severe matching symptoms of COVID-19, we're finding ~20% PCR-positive for SARS-CoV-2.
Beyond that, we also have good evidence that the Basic Reproduction Number is somewhere between 2-3. Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet.
Its not a significant amount of testing if we're only testing those with severe symptoms
Here in SF at least there are scores of people I know who all were sick with a "weird flu" at some point from February to now who would all kill for a test to show that they have COVID immunity. These are people who could potentially go back into society and do more work / enjoy their lives instead of being shuttered inside with anxiety
It is currently _IMPOSSIBLE_ to get any kind of test to prove that
https://www.worldometers.info/coronavirus/country/south-kore...
Since they have coronavirus relatively under control and have been doing extensive testing and contact tracing for months, it's plausible that they've caught most cases. It's wishful thinking to believe the infection fatality rate is an order of magnitude lower.
The CDC is currently estimating an R0 of 5.7, which has likely been repressed by shelter in place orders. But even if it was only 4 before any interventions, there's still a chance there there are closer to 20M cases in the US rather than the 660,000 now.
My point is just that there's still a lot we don't know, and small changes in our understanding could implicate massive changes in the reality on the ground.
Based on other available data the severity of the Covid symptoms are dependent on both the length of exposure and total exposure to the virus. A cruise ship with recirculated air likely means prolonged exposure to high concentrations of the virus that won't fit most other patients exposure.
May be about double that. Per wiki article, I noticed this a few days ago (https://en.wikipedia.org/wiki/2019%E2%80%9320_outbreak_of_no...)
"Initial estimates of the basic reproduction number (R0) for COVID-19 in January were between 1.4 and 2.5,[381] but a subsequent statistical analysis has concluded that it may be much higher.[382]"
From that link wiki provided (https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article) (edit: and note this is published on the CDC website)
"...we calculated a median R0 value of 5.7 (95% CI 3.8–8.9)"
So this sucks harder then.
Source: https://www.contagionlive.com/news/asymptomatic-influenza-in...
> Study results revealed an overall pooled prevalence for asymptomatic carriers of 19.1% for any type of influenza, 21.0% for influenza A, and 22.7% for influenza A(H1N1). For subclinical carriers, the overall pooled prevalence of was found to be 43.4% for any type of influenza, 42.8% for influenza A, and 39.8% for influenza A(H1N1).
> Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet
This sounds like circular logic - how we know it indeed started in January and not before? How do we know how many had it asymptomatically if we didn't test 99% of the population? We're making assumption based on knowledge gathered by select sample of 1% chosen by severity of symptoms - how can we make conclusion about how it works in the rest of the population and what's the dynamics there?
[1] https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx
The BPR is estimated from the known cases, so it cannot tell you anything about a hypothetical large number of unknown cases.
Antibody tests in a recent German study of households gave 15% infection rate.
I don't understand what's so hard about measuring population infection rate.
Assuming the population infection rate is between 1-10%, we would only need to do around ~500 randomized tests to achieve a 95% confidence interval of +/- 1%.
For example, let's say we tested 500 random NYC residents for COVID and found that 10 were positive -- a 2% infection rate. The standard error (binomial approximation) for this sample is 0.6%. So, by doing a mere 500 randomized tests, we have a 95% confidence interval of 0.8%-3.2%.
Given that overall population infection rate is so important in planning for re-opening, why are we not doing randomized testing in hotspots like NY on a regular basis? Am I missing something?
[1] https://www.wsj.com/articles/health-authorities-roll-out-new...
https://news.usc.edu/168497/antibody-testing-covid-19-pandem...
Happy to change my mind -- but there simply hasn't been any effort to use population testing in this way -- which is one of the only useful forms of testing. Otherwise, why test people in the hospital? It doesn't change treatment. Finding asymptomatics is actually useful -- and random sampling seems critical for understanding whether we are simply fucked or actually fubar'd.
Deleted Comment
Another point of reference is this: according to [1], a back-of-the-envelope estimate of the number of Covid-infected is 100 times the number of dead. It's about 8000 now in NYC, so about 800k infected. That's about 10% of NYC's population, exactly the number you mentioned.
[1] https://www.solipsys.co.uk/new/BackOfTheEnvelopeCOVID19.html...
By some estimates we need over 80% of the population to get it in order to achieve herd immunity, so if only 10% of the population has it we're not very close at all to this being over.
Does it mean the period for which a patient is infectious before they become symptomatic?
Or do some people never become symptomatic?
And if it's the second, do they cease to be infectious like symptomatic individuals after a time? Or are they infectious long term (aka carriers)?
We also know from contact tracing and mass testing instances that only something like half of cases stay asymptomatic forever. It is likely that the people in this study are either asymptomatic because they no longer have the disease or because they haven’t developed symptoms yet. Also, they might just not be recognizing their symptoms. Even without covid-19, way more than 7.5% of homeless people are typically coughing.
We’d be about 1/7 the way there. Meaning we’d see another 6x current deaths to get through this. That’s not even close to acceptable.
And the 10% aren’t realistic, anyway. At least nationally. Assuming nationwide rates of 10%, then scaling up by death numbers, would put infection rates far above 100% in New York.
Is there a choice?
If so, what does that mean for herd immunity?
"Upon observing a cluster of COVID-19 cases from a single large homeless shelter in Boston, Boston Health Care for the Homeless Program conducted symptom assessments and polymerase chain reaction (PCR) testing for SARS-CoV-2 among all guests residing at the shelter over a 2-day period. Of 408 participants, 147 (36.0%) were PCR-positive for SARS-CoV-2"
The key thing here is they tested people from one single homeless shelter. Is this one homeless shelter in Boston representative of all homeless shelters in Boston? There is not enough info in this article to make that assumption. Nor is it enough information to make generalizations about the populations of the homeless who do not live in shelters.
I actually think we can say for certain this is NOT a good representation of the general population. The general population has not been living in close quarters with multiple COVID positive people.
Submitted title was 'Boston study finds 35% of homeless are Covid+ (via PCR)'
https://www.nbcnewyork.com/news/local/nyc-hospital-finds-hig...
[1]. https://www.bostonglobe.com/2020/04/15/opinion/how-get-bette...
The UK has some randomized seriological surveillance and it's about 13% prevalence. That matches with the pregnancy study of 15% prevalence (which may be enriched due to hospital visits).
https://www.kansascity.com/news/local/article242010356.html
But either way folks are probably being very careful because the results will have significant impact.
Also worth considering is the period mentioned in the correspondence is one in which there was very fast exponential growth. When more of the positive cases are recent, it's only normal that they don't show symptoms yet.
Besides the test used showing a lot of false positives, the population of pregnant women looked at had a much higher rate of symptomatic infections 1 month ago than the entire population does today... we should be very cautious about concluding much from that sample.
https://www.nejm.org/doi/full/10.1056/NEJMc2009316
This seems to have the toughest aspect of gaining consensus.
Need antibody tests now, and ones that work reliably.
So is it possible this disease appeared in China way before December, maybe a few months back. Then in December it reached a saturation point (i.e. infected hundreds of thousands of people, so deaths started to get noticed by respiratory specialists). Then around January/February this disease spread to the world, but it went unnoticed. Then in March it reached the same saturation point that the deaths became too many not to notice.
Is this a realistic scenario?
The best you can hope for is for people to call it the "COVID19 virus".
Doesn't matter for nearly 100% of my daily discussion about the pandemic.
I typically say Coronavirus or sometimes covid because it's faster to say or type.
As always, the distinction between two tightly bound things is not important when you talking about features common to both, such as which people have them.
Humans tend to migrate toward shorter more pronouncable, easier to type terms. Language evolves like a virus ;-)
https://www.merriam-webster.com/words-at-play/synecdoche-met...
https://threadreaderapp.com/thread/1245791851342229504.html
For instance as of today, the number of unreported to reported cases in the US can't be more than about 500.
The time period when the disease could have been prevalent in the US can't have been very long, because at its present level it kills about 15000 per week -- a number that could not have gone unnoticed even a month ago.
Eventually, the curves of hopes, reported data, and reality will all have to intersect, I just don't know where or when.