I don't think this rules anything out, because this study was done on throat swab PCR tests. It's entirely possible a much larger percentage of the people in this study had already been exposed and cleared the virus. Not saying that IS the case, just saying it's entirely possible.

I don't see how this theory would be compatible with the rapid rise in hospitalizations and deaths that was observed in the last weeks. If many people had been infected a long time ago, why are they only now starting to get sick?

There's a logical inconsistency here. If we assume that the total number of cases is much higher than reported, then the hospitalization rate per infection is driven down by the larger denominator. There's a point at which there are so many total cases that the number of hospitalizations is problematic and noticeable. If we continue to assume that the total number of cases is much higher than reported, the death rate per infection (IFR) is also driven down by the larger denominator.

But if we had a large number of undetected cases in the past, then we should also have a large number of undetected cases now, contrary to the study. (Unless we already have herd immunity, but there is no data at all suggesting this.)

Perhaps in the past, earlier in the virus's exponential growth, many people had it but still an order of magnitude less than now. And that order of magnitude is the difference between a slammed hospital and a regular day. And because an order of magnitude people less had it, groups like the elderly were an order of magnitude less likely to be exposed en mass.

I'm not necessarily saying people got infected a long time ago. If anything I think we're just missing way more cases than people assume at this point.

A giant outbreak that had already passed weeks ago would be inconsistent with the shape of the curve of symptomatic cases, though. We know for sure that the bulk of people who have ever had this disease are still sick

> "We know for sure that the bulk of people who have ever had this disease are still sick"

Most people who contract Covid-19 fully recover by around 7 days after showing symptoms. Severe cases that go to hospital? Yes, recovery may take a long time.

The bulk of people who got sick enough to get tested and/or go to the doctor are still sick. Remember, the hypothesis is that there are a large number of infections mild enough to not be reported, tested, or hospitalized.

Yes, but if they are the same disease, then the asymptomatic/symptomatic fraction of cases must be the same over time[1]. So a bunch of people who had the disease asymptomatically weeks ago should have shown up in a spike of people with symptoms, and it didn't.

[1] Or if they weren't, that would be a BIG result and very surprising. It's absolutely not something you can assume to make an argument.

Pathogens evolve: https://academic.oup.com/nsr/advance-article/doi/10.1093/nsr...

Actually SARS-CoV-2 has been found to have a comparatively low mutation rate. But my point was that now you're not just positing a very large undetected outbreak of COVID-19, you're positing a very large undetected outbreak of an itself-undtected variant strain of COVID-19 that just happens to have the properties needed to produce the overmeasurement that you want to see in the case fatality rate.

See the problem with that logic?

> Actually SARS-CoV-2 has been found to have a comparatively low mutation rate.

Compared to what, a rhinovirus?

> you're positing a very large undetected outbreak of an itself-undetected variant strain of COVID-19

From the linked study, it appears that at least one variant has been detected:

"Population genetic analyses of 103 SARS-CoV-2 genomes indicated that these viruses evolved into two major types (designated L and S), that are well defined by two different SNPs that show nearly complete linkage across the viral strains sequenced to date."

How would PCR test results give us any sense of the relative spread of these two strains (or indeed others)? Is it possible that you're motivated to dismiss ideas that challenge your understanding? I'm not convinced that it's the correct explanation for these observations, but the argument that it's impossible seems pretty weak.

I'm not saying it's impossible. I'm saying it can't be simply assumed to make an unrelated point about case fatality rate. If you want to cite me a study showing a separate, weaker strain of COVID-19 that explains how the CFR is much lower than we think you need to show me the actual science, not just assert that it exist.

Because the obvious hypothesis is that it's one disease and one outbreak and the CFR is what we measure and not something else.

Different hypotheses are obvious to different people. You're hearing one of the scariest ones - partly because it's great business for the media and political industries, and partly because it supports the belief that we can accurately measure an in-progress epidemic of this kind with our modern technology. Here are some very experienced folks with less-scary "obvious" hypotheses:

https://www.youtube.com/watch?v=lGC5sGdz4kg

https://www.youtube.com/watch?v=d6MZy-2fcBw

https://www.youtube.com/watch?v=-UO3Wd5urg0

https://www.globalresearch.ca/open-letter-professor-sucharit...

The exponential curve is consistent with the exponential increase in testing.

If a stable 30% of a pop has X at any given time, and you test 10 people for X the first week, 100 the next week, 1000 the next week, etc. you will have a nice exponential curve of the number of cases while, in reality, nothing all that exciting is happening.

Have you seen a scary graph anywhere in the media that normalizes for the number of tests given? I haven't.

The exponential curve in deaths and ICU admissions is independent of testing (and wouldn’t exist if the virus had been endemic in the population before March).

The exponential curve in deaths would be reflective of exponential testing/ Once again, if you have a stable X percent of people dying from Y, an exponential increase in testing for Y will give the illusion of an exponential increase in Y deaths.

As far as ICU admissions, that is an extremely subjective number, based on individual hospital policies; from my conversations with local HCPs, of two patients in the same degree of distress, the one who tests positive will have a greater likelihood of being put into a quarantined ICU for covid cases. There is no sinister reason behind this; its just that the covid patient has a much greater chance or taking a rapid turn for the worse.

Anyway, my statement (now downvoted) isn't meant to be controversial. It's just a fact. We have had an exponential increase in testing in many parts of the countries... posting the results and then having a newscaster say, "Look at the scary exponential curve" is absurd. There could be -- and most likely is -- an exponential rise in the number of cases. But, using the graphs without backing out the curve in the testing would get you an F on a freshman statistics quiz.

There's some places doing blood testing and it looks like it is going to be about the same:

https://www.sanmiguelcountyco.gov/590/Coronavirus

Very few positive PCR tests, very few positive blood tests, so not as interesting as blood tests in a region with more positive PCR tests, but it demonstrates there's not a big group of people in the county that have immunity.

Just a note, no evidence of how much immunity yet. We are hoping that is the case but there are also a few loose stories of people getting covid a 2nd time. We should know more in a few weeks to a month...

There are a few reports of people returning a positive test a second time. That is not the same thing as getting infected a second time.

The blood test looks for antibodies, so it detects whether the person has had an immune response to the virus.

The GP is pointing out that having an immune response to a first infection has not been riguorsly demonstrated to prevent future infection. If we are unlucky, immunity may only persist for a short period of time.

I believe in those "recovered patient tested positive again" cases, they are talking about PCR testing (which detects virus RNA), not blood antibody tests.

Okay, I see what you are saying.

Both things can be true though, we don't know how persistent the immune response will be.

Antibodies (Immunoglobulins) will fade over time, and may not be detectable in the blood after a while. So a negative antibody test for Covid-19 wouldn't necessarily mean you're not immune.

However, immunity should persist for a long time, perhaps even for life. That's because the immune system retains memory of past pathogens and knows how to make new antibodies quickly if needed.

The reason we seem to keep getting infected with cold and flu, year after year, is because these are actually different viruses each time.

You are carefully explaining the mostly true generality.

The fact remains, we simply don't know how long immunity will persist for a given novel virus. We will find out over the next months and years, but at this time, we do not have concrete knowledge about SARS-CoV-2.

Which blood test currently in use looks for antibodies?

It's explained on the page I linked earlier in the thread. A founder of the company that developed it is paying to have the county where he lives tested.

Yes, "not a large group that had a positive blood test" would be better.

Also, according to [1], only a third of throat (pharyngeal) swabs from patients known to have the virus were positive.

1: https://www.jwatch.org/na51116/2020/03/17/pharyngeal-and-nas...

Given how difficult it is to get a test in many US states, the high number of reported negative test results should be surprising.

Correct me if I'm wrong, but this used PCR testing to determine the number of _currently_ infected people. It says nothing about the number of people that _were_ infected, but fought off the virus and are now potentially immune.

Simple exposure is not enough to become immune. You need a significant infection which triggers a strong immune system response to build long term immunity. Thus in the initial stages of an outbreak you can basically ignore people that became infected weeks ago, had a significant infection, and are now immune due to the exponential growth curve.

It’s only after the rate of infection stayed the same or falls for a month+ that you need to adjust for such people.

>You need a significant infection which triggers a strong immune system response to build long term immunity.

I don't think this is true. I get the flu shot every year and have never had a strong immune response to it, yet I'm still immune to the major flu strains each year.

Point being, it's possible for your body to create long term immunity to a virus without suffering from a severe infection.

I am specifically referring to COVID-19 where we don’t have a vaccine. Vaccines fake a significant infection to get that same strong immune response. This is also why some vaccines require multiple doses over a short period.

If we did know the true current infection rate (which this report does not give, as there are too many unresolved assumptions), then could we not, with some reasonable assumptions about the rate of spread and the duration of an infection, estimate the number who have recovered from it?

I think that requires an antibody test

Indeed PCR tests only test for the presence of the virus itself. Their big advantage is an extremely high specificity. Antibody tests are plagued by large numbers of false positives.