Over half of Covid hospitalisations tested positive after admission | Hacker News Reader

Over half of Covid hospitalisations tested positive after admission

telegraph.co.uk

126 pointsmrfusion229 comments

> Experts said it meant the national statistics, published daily on the government website and frequently referred to by ministers, may far overstate the levels of pressures on the NHS.

I don't understand this part. Isn't the important number here the total number of people in the hospital (or ICU or other ward) relative to the total number that the hospital (or ICU or other ward) can accommodate? Or alternatively, the total excess relative to normal years.

I can see the utility in differentiating these numbers for other reasons, although the accounting could be tricky, to handle cases where people are admitted for one thing then develop another, or show symptoms that could have a number of causes.

The reason to population numbers and trends are important is to work out what's happening in the population, and therefore plan for dealing with changes in case load. Measuring current pressure on the NHS is important yes, but knowing that cases in the population are rising or not, and if so by how much, is also vital information for resource planning.

Having said that, clearly the tests are being recalibrated and their usage adjusted as new information becomes available. These adjustments in tests seem to have increased accuracy. Isn't that what we want? There's no conspiracy or scandal here.

> I don't understand this part. Isn't the important number here the total number of people in the hospital (or ICU or other ward) relative to the total number that the hospital (or ICU or other ward) can accommodate? Or alternatively, the total excess relative to normal years.

I agree with this point and the article doesn't seem to mention this, surely the important statistic is number of in-patients per week comparing week by week with 2019. If it's much higher then there is a big problem regardless of whether these patients have covid or not as we haven't built any significant hospital capacity or trained a lot more medical staff since then.

"Available" beds/ hospital capacity is usually a floating number, and it's not an absolute capacity, it's just the instant capacity at that moment. It changes in response to demand.

Hospitals don't count closed wards/wings/floors that can be staffed and "activated." Same goes for converting other areas/depts of the hospital to covid units. Which is why it's better to monitor absolute cases or deaths, not % "capacity".

So their argument is: everyone is already infected, it's no big deal?

Whereas the actual questions are: why are people going into hospital without having a Covid test first (assuming non emergency)

And: What percentage of the people who tested positive in the previous 14 days in hospital because of Covid. And what percentage of the people who weren't tested went to hospital because of Covid related symptoms.

Yeah, those are the right questions. The point of the article is that people who go to the hospital for non-Covid reasons - eg, broken leg, heart attack, cancer - and then test positive are being counted as "hospitalized with Covid" even though they don't have a severe case.

So the statistics are being skewed. We don't really know by how much, because the article doesn't say how many went to the hospital for Covid-related symptoms.

Well, the you've got to differentiate what are covid related symptoms and what aren't. A lot of people with Covid, as with many such diseases, actually die of something else. Hence the "nobody ever died of covid, it was all because of pre-existing conditions" conspiracy theory.

The fact is it probably doesn't matter all that much. Anyway who gets to decide what is covid related or not? How do you ensure consistent application of selection criteria across teams and hospitals?

When your hospitals are filling to capacity with wheezing, coughing patients on ventilators the fact your numbers are off by a bit is by the by, and your medical staff have enough to deal with.

Anyway wouldn't this policy over-count patients who'd got vaccinated, went to hospital for an unrelated reason, but then tested positive for covid? After all, you can still catch covid if you're vaccinated, you just get to fight it off quicker. Most likely the statistical impact of all these factors isn't all that much though.

More actual questions:

- how soon after exposure do you test positive (eg. if they went to the hospital, tested negative, then tested positive later there - were they undetectably positive on the first test, or did they catch it in the hospital).

- Why do we not separate hospitalized "by" and "with" covid (and same for deaths). If half of the hospitalized are there because of broken legs and appendicitis, they'd be there, covid or not. Same with deaths, if you get hit by a bus and die, 20 days after a positive test, you're counted as a covid death.

Half the patients in hospitals over-run with covid patients are not there with broken legs and appendicitis. That's absurd. The numbers of such people are going to be reasonably well understood.

This is why excess hospitalisations and deaths compared to seasonal norms are used as a reality check on the test numbers. Newspaper headlines might trumped specific numbers that are attention grabbing, but actual policy is driven by an assessment of all the available data.

But half of those people are there with broken legs and apendicitis. Only half of those stats are due to covid. As an invidual, every person in a hospital is too much... but when considering lockdowns, because there are (eg.) a 1000 people with covid in hospitals, it's worth to know if those people are there because of covid, or 560 of them would be there normally.

In Santa Clara County COVID-19 deaths were originally over counted by 22% before they adjusted the methodology. Other public health agencies have had similar data quality problems. So not half, but a significant fraction.

https://sanfrancisco.cbslocal.com/2021/07/02/santa-clara-cou...

>why are people going into hospital without having a Covid test first (assuming non emergency)

The truth is that once you put aside the creepy fawning nationalism around the NHS it's actually got some serious systemic issues that never get properly resolved because it's a political football. It's not "joined up" very well at all, at least in my experience paperwork cockups are pretty much universal. The clinical staff are fantastic for the most part but the way it's administered and organised is almost comically dysfunctional. It's damn-near impossible to actually pin down an NHS service to a concrete date or time to get anything done in my experience, in some cases you just get ignored unless you specifically know that you have to chase them up yourself. I ended up going private at my own expense and the conspiracy theorist in me reckons that's probably the ultimate aim: let the service rot to the point anyone who can afford it will jump ship for the private sector.

I have a lot of respect for the people on the ground at the NHS, lions led by donkeys indeed.

> let the service rot to the point anyone who can afford it will jump ship for the private sector

I think that's pretty far-fetched and can't see a good reason for this purposefully being the case. It's just Hanlon's razor, really.

There's enough private healthcare interests with links to the Conservative Party to at least make it worth raising an eyebrow in my opinion. I'm not making any specific allegations but it wouldn't be the first time Conservative Party ministers got in bed with private interests, the PPE scandal of last year comes to mind for example.

You're right of course though, passive incompetence is probably more likely than active malice.

> passive incompetence is probably more likely than active malice.

Well this is pretty much the norm at most levels of government around the world. There are no real performance indicators being used to judge accomplishments or effectiveness for most government jobs.

A former health secretary (Jeremy Hunt) co-authored a book that laid out this exact strategy.

> comically dysfunctional

intentionally dysfunctional.. there has been a multi-decade effort to prep the NHS essentially for complete privatization

You mean the multiple decades that included a left wing Labour government, the same party that set up the NHS? A post-2008 crash spending freeze from which the NHS was exempt? The decades of huge budget increases?

The NHS is not intentionally dysfunctional any more than the USSR was. It's dysfunctional because the state cannot run large, complex operations regardless of how hard it tries. It's because the NHS is a top down command and control economy and those have never worked, in any period of history. It's because without competition the inevitable result is decay and steadily advancing institutional incompetence (paired with financial incontinence). That's why successful countries have economies based on free competition and why even China had to adopt it via Deng Xioping's reforms in the 1980s.

The NHS is an embarrassment to the UK and I say that as a British citizen. No other country has ever sought to emulate it because it is bad. The quasi-religious fervor with which it's viewed by the left occurs because it's an obsolete institution that nobody in their right mind would ever even consider proposing in the modern era, and they know it. If the NHS and BBC go then there would be no more socialist institutions beyond, perhaps, universities.

Keep in mind: efficient and organized or not, the government check keeps coming.

What are the incentives to improve then?

If say 10% of a randomly sampled population tests positive, and 56% of admissions test positive, then only 5.6% of admissions should be unrelated to Covid[^].

The premise of this article is bullshit. Sure, there will be situations where someone comes in with a broken leg (unrelated to Covid) and tests positive. Note that the article mentions PCR, so we are not talking antibody tests.

Are there figures for what percentage of randomly sampled UK population currently tests positive for Covid?

[^] Aside: The 5.6% example number isn’t quite right, but the figure should be of that order.

Actual UK population infection number is ~ 1.5% - see studies referenced by https://news.ycombinator.com/item?id=28037172

Great journalism at work here! So - the expectation is that people with symptoms of Covid19 would be tested before being hospitalized? I am actually impressed that 44% were.

It would be standard operating procedure for an hospital receiving a patient showing symptoms to give a test. In fact 88% received the test results within two days of hospitalization.

I am still waiting for an explanation of ICU occupancy [0] if it wasn't for Covid 19.

[0] https://www.statista.com/chart/23746/icu-bed-occupancy-rates...

As someone who works in the NHS, I would also like to know. My trust has hit full capacity yesterday for the second time in two weeks. Another trust I work for had full ITU capacity and has had to cancel elective surgery. According to more senior clinical staff the hospital is full of genuinely sick people.

But that's inevitable. The NHS runs at close to capacity in normal times, but there has been a period of over a year now when people were being told to avoid going to hospital, to stay isolated at home, when doctors were not seeing patients. I am actually more surprised that you are surprised. The NHS has collapsed: waiting lists are now so long there is no way they will ever drain except by people simply dying due to lack of treatment. You should expect all hospitals to be completely full from this point on, as a natural consequence of lockdowns (ironically, the thing the lockdowns were supposed to avoid).

I don't think it is off topic for me to say that your comment is arrogant with statements that are either incorrect or make a lot of assumptions. Maybe throw in a bit of schadenfreude in too. I think the style of discourse here colours the discussion, and your comment is a statement rather than a discussion.

I certainly saw patients over the past year - at no point did I stop. My patients were grateful that the hospital steered away from a dysfunctional breakdown, which allowed us to keep running our day unit and ward to treat our cancer patients. There were a couple of points where local hospitals became overwhelmed, and the diversion to our hospital threatened to overwhelm us as well. I would say the lockdowns allowed us to treat our patients during this last year.

The certainty in your belief that the lockdown has resulted in hospitals being full (?forever) makes several assumptions. There are other explanations, and my personal hunch is it is something to do with spread of infectious diseases with social restriction easing.

The problem is, even if they were asymptomatic and released from hospital e.g for their broken leg, they would still go in statistics as "This person was hospitalised for COVID-19".

You didn't read the article, did you now? The numbers say - according to the article itself - that of the patients hospitalized and diagnosed with Covid 44% had a positive test before being admitted - 43% had a positive test within 2 days and the remaining 13% tested positive within 2 weeks [they don't mention the distribution].

What I find repulsive about this article is that they never say 'someone with a broken leg was counted as a Covid case after the mandatory testing' - they just dance around it, make innuendos and let third parties dance closer to it.

Nowhere in the article they state 'asymptomatic cases with an other unrelated diagnosis were counted as Covid cases' - and I am guessing they don't because the don't have the numbers to prove it.

A real journalist would track down the cases - would try and find the 'I went in with a broken leg and was released with a Covid diagnosis', get the discharging papers and write about it.

Now: if there were really so many cases of people hospitalized with a different diagnosis and attributed to Covid to 'jack up the numbers' - where are they? Where are the articles about it?

Until you have these, please: go back to your little green field to play with your friends - the adults are trying to have a conversation here.

Adults do not throw tantrums. Maybe you should take your own advice.

So they tested people when or before they arrived and it said negative for covid, and then they tested again later while they were still in the hospital and it said positive for covid?

reads article

Of course people with Covid tested positive after admission because the test only occurs after admission.

reads article again

Of course the admission symptoms were not "for Covid" as the symptoms help you lead down the path of what the ailment is!

This study is about potential errors in reporting, which still need to be investigated.

Is the Telegraph a paper of good repute? The article feels to me as somehow manipulative however I'm not local to the UK. I am wondering if this is propaganda or if these results are actually plausible.

it's historically a reasonable newspaper but lately is extremely closely aligned with the ruling Tory party and their desires, to the point of everyone reading the online edition on Sundays to see what will be announced by the government on Monday.

Didn't The Telegraph endorse Boris Johnson? I'm not super well versed in UK politics, but as Prime Minister Boris Johnson is also the "Leader of the Conservative Party" right? And the Tory party merged with another party to form the Conservative party so are they now a wing or subset of the Conservative Party? Is Boris Johnson in the Tory subset?

"Tory" is just a colloquial term for "member or supporter of the Conservative party". It started out as an insult a couple of centuries ago, but has long since lost that association.

The Telegraph didn't just endorse Boris Johnson - he worked for the paper back in the 1990s, and after resigning his position as Foreign Secretary in 2018, he wrote regular columns for them.

Tory is still an insult in Ireland. Probably Scotland too.

That happened 150 years ago. Today, “Tory” is another name for a member of the Conservative Party.

It's a Tory (conservative) paper and always has been, traditional or reactionary depending on your point of view. Not sensationalist.

The Irish comic Dave Allen characterised the British press as follows:

One of the things about Britain, actually: you can always tell the way a person votes by the paper they read. For example, The Times is read by people who run the country. The Financial Times is read by people who own the country. The Daily Mail is read by the wives of the people who own and run the country. The Daily Mirror is read by the people who think they run the country. The Guardian is read by people who think that they should run the country. The Morning Star, or as it used to be known as, the Daily Worker is read by people who think that the country should be run by another country. The Daily Express is read by people who think that the country should be run as it was. The Daily Telegraph is read by people who think that it still is. And The Sun is read by people who don’t care who rules the country as long as they’ve got big boobs.

You get the idea

Wasn't that in Yes, Minister? Or was it a shorter version... it's been awhile since I saw that show but that's almost the only joke a remember distinctly. Oh, that and the line, "If you want to stab someone in the back you first need to get behind them," which I reference not infrequently.

It was, but it wasn't the original source of that quote.

Someone tried tracking down the source here: http://www.dirtyfeed.org/2021/04/what-the-papers-say/

It's a mainstream paper and it's pretty good by the standards of the British press. It's got a right-wing slant but that's not a bad thing in and of itself, it's not sensationalist in the same way the tabloids are. It's been more overtly Tory (in contrast with small-c conservative) over the last few years but I suspect that has a lot to do with our current Prime Minister having once been on their payroll as a journalist.

I tend to read a range of ideological slants when it comes to the British press, I find the Telegraph's and the Guardian's takes to be the most interesting of the bunch usually.

This is a newspaper that decides what the news is going to be and then goes out to find the sources to support that.

I mean, it employed Boris Johnson as a columnist; you do the maths.

More seriously, it's a bit of an oddity, really; it's a broadsheet under the normal classification, but certainly has tabloid-y elements.

this seems to suggest there's a lot more undiagnosed cases walking around in the wild than we know about.

That's already been established. Many cases are asymptomatic or present mild symptoms that won't motivate the ill to seek out a test. Testing by country, state (province, etc.), and even region varies wildly.

right, i'm not making a new claim. i'm saying, that's one of the few conclusions we can draw from this data. it doesn't say anything about e.g. catching covid at the hospital, whether existing data on health consequences and mortality is less relevant, or that "covid is mild / just a flu" as some people seem to be concluding.

This was apparent last year from serologic antibody testing. The prevalence of antibodies was anywhere between 2-10x what we were finding in the tests, which made it pretty obvious that way more people had mild COVID than is being reported. Unfortunately, if someone picks up a runny nose and mild cold-like symptoms and then recovers, it doesn't make the news. But if you have a one-in-a-million freak case where a 25 year old ends up in the hospital testing positive, it gets plastered on every news publication and is repeated ad-nauseam even though it is a misrepresentation.

Well, yeah, but we knew that already. The UK has been monitoring the actual number of people infected with Covid via random sampling of the population for well over a year and it's always been rather higher than the detected cases, despite having a lot more mass testing than other countries.

Keep going. What does that say about the reported IFR that’s used to justify lockdowns?

nothing conclusive. we should lock down harder, could be one of the conclusions.

The CDC estimates that only about a quarter of infections are officially counted as cases.

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/burd...

I decided from the beginning to only focus on COVID deaths, and maybe intubation rates. Everything other measure seemed too fuzzy and ripe for manipulation. Death is a pretty definitive finding.

But even this death metric is fraught with issues of “death from COVID” v. “death with COVID”. Deaths among the elderly are often ascribed to just “old age”…nobody cared about exact root causes until COVID came along. Most of the fatalities came from the “under-forensic-ed” elderly population and (I read somewhere…source needed) hospitals got increased financial compensation if a patient was coded as a COVID patient. Who is doing the forensics and what is their motivation? So even assigning a cause of death by COVID is a mess, but less than the mess of defining “COVID cases”.

Modulo the “cause of death” issue, fortunately, for COVID deaths, the CDC has a nice website that presents the relevant National and State data

https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

Ignore the silly “red +” over the data — just compare the deaths by week (in blue bars) to the expected deaths (as presented by the orange line).

(Any “statistically significant” overage gets a “red +” no matter how trivial the excess, so it distorts the essential trends. And the height of the “red +” over the data is the same no matter if it is one death over or 1000 deaths over the threshold for that week. Really questionable chart design veering into “lying with statistics” territory.)

I do the same. It's extremely sad to know the United States has lost more people to this than every war casualty since the Civil War.

Another weird trend I picked up reading France reports on the pandemic is that non-Covid nosocomial infections decreased significantly during the pandemic.[1] As if Covid took over antibiotic resistant bacteria (a little) and other infections (a lot).

There is no definite explanation, but mistaking other diseases for Covid is one hypothesis, along with anti-covid rules affecting other diseases.

[1] https://www.santepubliquefrance.fr/media/files/01-maladies-e...

Edit: I don't know why the downvotes (no problem with that), but in case someone thinks it is a conspiracy theory of some kind, Santé publique is an official agency tied to the french ministry of health. The conclusion is of course up to debate but you are unlikely to find better data.

You're going against the narrative, your data and your ideas don't matter no matter how legitimate they are. So you get downvotes.

I am weary of this newspaper's reporting - they wage a continual war on the NHS, and they seem to have some writers paid to continually put out negative news on the NHS.

Two points:

1. COVID-19 is the most thrombogenic infectious disease known to man. It likely has a serious impact on co-morbidities in a way that hasn't been clearly studied yet. This means it's likely to exacerbate current conditions.

2. Hospitals are full in the UK at the moment. It's not COVID numbers, but it's not clear what is causing this. Normally at this time in the year bed occupancy is low and elective surgical work can proceed, but at the moment elective lists are being cancelled due to full ITUs.

> Hospitals are full in the UK at the moment.

New Zealand hospitals have been in “crisis” pretty much all year, and we have no Covid. Currently it is due to a respiratory virus called RSV, but there were severe problems in other months too, not due to RSV.

https://www.google.co.nz/search?q=nz+hospitals+overrun+OR+cr...

Yes, I think other (non-covid) infectious diseases are partly to blame. They also have a knock on effect for other conditions like coronary heart disease, COPD and dementia, etc.

Could it be as simple as baby boomers ageing?

Well, the RSV problem affects babies the worst. I have a friend who’s baby is in hospital due to RSV: very worrying. https://www.health.govt.nz/your-health/conditions-and-treatm...

Note that one theory is that the RSV wave is due to relaxing rules on contact, hand cleaning, and mask usage.

2. Isn't that from all the rescheduled surgeries and such? I know that here in the Netherlands there is still a huge backlog of care that couldn't happen when the hospitals were full, that has to be caught up on.

Sadly the rescheduled care is getting cancelled due to lack of ITU beds for post-surgery. I don't know what's going, but there seems to be a backlog of complaints that people are only now getting investigated, and with increased social mixing I guess infectious diseases are going up. Still, it's a bit strange to be this overwhelmed at this time if year.

I think you're reversing cause and effect. The NHS constantly generates a flow of negative news that other outlets mostly suppress. The Telegraph does this less so than others, so it may appear to be "waging a war" on it but in reality it's just showing what others would have you not know.

Wow - I was re-reading the article, and it jumped on my face:

"The breakdown of daily Covid hospital diagnoses shows that of more than 780 hospitalizations dated last Thursday...with 13 per cent made in the days and weeks that followed"

Can we say that 13% was definitely tested in "days" not "weeks" since last Thursday?

So their:

"Experts said the high number of cases being detected belatedly – at a time when PCR tests were widely available – suggested many such patients had been admitted for other reasons."

At worst would indicate 13% misdiagnosed Covid cases, with the word "belatedly" doing a lot of lifting.

I thought this article was bad - but the more I read it the more it looks like a pile of journalistic manure.

Since they will take up space in a covid ward, it's not that strange that they are counted as hospitalized by covid in some statistics.

But they will clear up spaces (and doctors and nurses) in other wards.

And they're hospitalized "with" covid and not "by" covid. They might even be asymptomatic, in the hospital because of a broken leg, and they count towards the statistics that we then use for new lockdowns.

Same with deaths "by" covid and deaths "from" covid. I know it's hard to say, when an 85yo patient with 6 different illnesses dies, if it was the covid that killed them or if it was unrelated heart failure.

There was even a time where once you tested positive for covid, you could only die from that, and nothing else: https://www.cebm.net/covid-19/why-no-one-can-ever-recover-fr...

> In summary, PHE’s definition of the daily death figures means that everyone who has ever had COVID at any time must die with COVID too. So, the COVID death toll in Britain up to July 2020 will eventually exceed 290k, if the follow-up of every test-positive patient is of long enough duration.

This was changed to 28 days (i think) later, but atleast having a soft separation of "with" "by" and "maybe/probably by" would also mean a lot.

Yes, the data should be published— all relevant data should be published. But it says they just started gathering data a couple of weeks ago. So does the fact that it hasn't been officially packaged and published mean it's leaked as they repeatedly intimate? Or maybe it just wasn't published yet? Maybe they found anomalies? Just being the NHS and moving slowly?

Is it also hard to imagine that many people hospitalized because of COVID wouldn't regularly get COVID tests, even when sick? Most are older people more likely to have limited mobility, limited financial means, and difficulty navigating the world.

I don't mean to insinuate that their suppositions are false! Maybe everything is as they say, the government is counting people hospitalized for any reason at all as a COVID hospitalization, AND the number of people hospitalized with COVID who would not have otherwise been hospitalized is significant. Maybe they're doing it to justify overbroad public health intervention, as many assert. They don't provide any evidence of that, though. We just don't know.

This data could help us know, and I wouldn't be so critical if they were just dinging the NHS for not releasing it quickly enough. The Telegraph, however, is using this to bolster an ostensibly uninterrogated postulation without presenting any empirical evidence.

(malformed quotes are on them) Prof Carl Heneghan, director of the Centre for Evidence-Based Medicine at the University of Oxford, said: "This data is incredibly important, and it should be published on an ongoing basis. "When people hear about hospitalisations with Covid, they will assume that Covid is the likely cause, but this data shows something quite different – this is about Covid being detected after tests were looking for it."

The one expert they quoted. I read this quote as saying "people hospitalized for covid" is a different number than "hospitalized people who were found to have covid," which could be what those numbers represent, but we don't know. The Telegraph, however, is really grabbing the reader's steering wheel with bits like this:

"Experts said the high number of cases being detected belatedly – at a time when PCR tests were widely available – suggested many such patients had been admitted for other reasons."

That sentence wouldn't even pass muster on Wikipedia because of the weasel words. That's at the very least a heavily slanted interpretation of a quote and possibly a deliberate misrepresentation. That they attributed uncited "experts" rather than "this particular professor," I'd guess they're leaning towards the latter and completely aware of it.

Question if it's even possible to answer.

How does the average cycle count for a Covid-19 test compare to a flu test?

The most baffling thing is not standardising CT values for RT-PCR tests.

I have looked and I cannot even find how increasing CT values affect the false positive rate for the PCR testing. If my understanding is correct a single increment of CT essentially doubles the sensitivity of the test, so difference between CT value of 35 and 40 is 32 fold.

CDC is suggesting CT value of 28 for detecting breakthrough infections after vaccinations. And if I am not mistaken, a lot of places was using 35 for the CT value in RT-PCT tests.

So that means, a breakthrough infection needs to have 128 times viral load in someone who has been vaccinated to be considered as positive, than it is required to have considered as positive in a non-vaccinated person.

That is quite ridiculous.

Apparently it's even worse: "Different machines can produce different Ct values for the same sample, and the same machine can give different Ct values for different samples from the same person." [1]

I'm not sure I even understand the statement, but I guess it means it could be that they (somehow) couldn't report them even if they wanted to.

[1] https://medical.mit.edu/covid-19-updates/2020/11/pcr-test-re...

I ran one of the first labs to validate the original CDC assay (we got the controls to work). Ct numbers were a slippery slope we should never have gone down for COVID-19 PCR tests because snot is not like blood, a homogenous substance with well known homeostatic parameters that are under tight physiologic control. Do you know someone went swimming? Do you know if they were crying? Did they just eat some particularly spicy tacos? Do you know if they have Sjogren's disease? What's the humidity? Are they dieting? Add in the presence of long COVID, and just long post infectious shedding, and it's mildly amazing we can get this to work at all. Yes, the test platform produces the data and no, it should not be reported. The only thing we can really do is confirm presence of the virus.

I would like to see QC statistics from some of the large test-processing centers which have IIRC been established. Surely they send a blind fraction of known-negative or control samples through, to get good statistics on false-positive rates?

Yes, CMS requires clinical labs to submit to external proficiency testing under CLIA'88. The College of American Pathologists is a designated accrediting body and the one I'm used to using. You are not allowed to do anything out of the ordinary with proficiency testing samples. You can't send them out to someone else and report what they reported to you. You just report the results. If you fail, they test you again. If you fail again, you're on probation. If you fail a third time, you're not allowed to report that analyte any more. Results of proficiency testing are reviewed on site in a bi-annual inspection. Officially there are 3 inspections: Joint Commission, CAP, and FDA, that all inspect the lab. Generally, the Joint Commission folks and FDA folks ask for your CAP certificate, and if it's good, they just skip all those items. CAP does not mess around. They will fly to the ends of the earth, they will cite you, they may decertify you. And then no one in the lab gets paid and they have to find new jobs.

So, yeah, rest assured, labs work really hard to make sure they report honestly and accurately. Better to fail an occasional proficiency test and repeat, than get sideways on the inspection.

I was working in a hospital when they discovered the blood lab was not prepared for the Joint Comission, and I saw the panic based on the scale of consequences you describe.

My question refers to blinded testing meaning the lab in question does not know which, and handles, [in this case unexposed swabs from the factory] and it might range around 1-2% of samples on a continuing basis. To me that is the more industrial and continuous connotation of "QC". And the potential importance of "blind" testing.

AFAIK, in any hospital lab there are tests which are still sent out, because they are either more challenging to build and train the right [accurate, low-error] procedures around, or too rarely done for the local investment. What if PCR tests for Covid were also too challenging to ramp up to mass scale in a regional startup lab? There are reports around of horrible controls -- perhaps true or not. That is something sending "blinded" samples through, proportional to mass testing being done, could disclose.

Again, in the industrial setting there is the procedure you reported to the last ISO9000 auditor, and there is the actual procedure. The true spirit of that is that you should also build in procedures to detect when the production procedures are not being followed. Again back to ongoing QC.

Um, the samples submitted by the external auditor may be positive or negative. And clinical labs re-validate tests routinely, including drawing samples from our own lab personnel. But we don't have dummy patients in the electronic medical record tied to perfectly healthy actors coming in to donate 7 mL of blood in a red top.

Yes, surely for established labs with a culture of competence, care, and conscience, which I am sure is the norm in your parts of the world.

I suspect we are framing in terms of two different, almost non-intersecting kinds of institution.

My impression is of reports of "startup" regional labs which have scaled immediately in a pandemic, reportedly hired off the street (not people whose specific vocation and training and life-choice is toward lab technician or manager or scientist), and have resulted in anecdotal reports -- all heresay technically -- of swabs being left lying about in quantity, picked up off the floor, etc etc etc. To me these reports -- perhaps false -- do not intersect with the concern with detail in a lab that knows how to prevent cross-contamination when running at very high PCR amplifications.

I am not bringing any new evidence to this, so I will leave it with clarifying the focus of my concern. I appreciate your standing up for the integrity and integrity-of-process in established labs.

s/the lab in question/the startup lab in question/ a level or two up

> I have looked and I cannot even find how increasing CT values affect the false positive rate for the PCR testing. If my understanding is correct a single increment of CT essentially doubles the sensitivity of the test, so difference between CT value of 35 and 40 is 32 fold.

I have never used this particular set of primers, but have done a lot of PCR. In general, at 30+ cycles, PCR is prone to spurious amplification. It depends on the primers, temperature profile, and other details, but at these cycle counts you need to be skeptical of your results. It's easy to get noise.

I've never been able to fathom how a PCR amplification at 30+ cycles with no downstream purification or gel visualization is considered definitive diagnosis of an illness. I strongly suspect that the goal was to cast a wide net (i.e. bias toward false positives) at the expense of accuracy, but then "cases" became some kind of top-line media metric...

> I strongly suspect that the goal was to cast a wide net (i.e. bias toward false positives) at the expense of accuracy, but then "cases" became some kind of top-line media metric...

Then in January the WHO updated the diagnostic protocol [1] because of that false positive/low confidence problem. Unsurprisingly, case counts plummeted in the following weeks.

[1] https://www.who.int/news/item/20-01-2021-who-information-not...

Yep. It was stunning to me that this was rarely mentioned in the press.

When I bring this up in conversations with people they make me feel like a kook. I am not sure what to think anymore.

Because what to do is highly variable doesn’t mean we need to take unnecessary risk to know literal truth.

Urban area population density requires different mitigations than rural, except rural communities rely on urban ones as logistics pipelines.

So normalize; mask up, stay home. Prefer all gas, no brakes, based on stats? There may not be enough real people to keep the internet on later.

Nothing about the lockdown was for saving you or me specifically, but systems of behavior we rely on.

That isn't a valid reason. The infection fatality rate for most people who keep the Internet running is way less than 1%.

https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scena...

For me this is interesting, but not really material to anything. Sure, the tests we have for this new virus have needed to be adjusted and calibrated as we learn more about it. It's unfortunate if the numbers are a bit messed up, it would be better if they were more accurate, but real life is messy.

I don't think you're a kook, and I can only guess what those people were thinking. Maybe they just wondered... and therefore, what?

Abusing high cycle thresholds for false positives isn't a new strategy.

PCR inventor Kary Mullis is on video calling Fauci out for doing exactly that. Unfortunately I can't even link the two videos because they keep getting memory holed. If you search around you might get lucky, otherwise I'll upload my saved copy when I get off work.

Note that the background for this is that Kary Mullis believed AIDS wasn’t caused by HIV and was therefore angry at Fauci and the entire medical/scientific establishment for linking HIV and AIDS. He died in 2019 so his criticisms of Fauci were related to HIV, not SARS-CoV-2. https://en.wikipedia.org/wiki/Kary_Mullis#Views_on_HIV/AIDS_...

The video they are referring to has a very specific part about pcr testing (relevant to the discussion here). I think it is reasonable to trust his opinion on the matter regardless of what he thinks about AIDS.

He is also a Nobel laureate.

The video pretty clearly shows that his view is that testing for HIV is a conspiracy by the CDC to get funding to fight AIDS.[1] Unless you agree with him that AIDS isn’t caused by HIV, it doesn’t make much sense to trust him rather than all the scientific experts who have worked on PCR testing and virus detection in the last few decades. ( edit: Moreover, suppressing HIV using drugs has been successfully treating AIDS, which wouldn’t make sense if the disease wasn’t actually caused by the virus. )

Moreover, PCR testing during the covid epidemic, which he was not alive for, has clearly been working well. High cases later correspond to high hospitalizations and high covid-19 deaths and high excess deaths across many different countries.

Frankly I don’t put much trust in his Nobel, any more than Michael Levitt who is also a Nobel laureate and has repeatedly made falsified predictions about the Covid-19 pandemic.[2] It seems pretty clear that Nobel prize winners can later lose touch with reality.

[1] https://www.youtube.com/watch?v=MkqQIY7J0fQ

[2] https://en.wikipedia.org/wiki/Michael_Levitt#Covid-19

PCR testing during the covid epidemic, which he was not alive for, has clearly been working well

There is no correlation between COVID health outcomes and levels of testing.

> Moreover, PCR testing during the covid epidemic, which he was not alive for, has clearly been working well. High cases later correspond to high hospitalizations and high covid-19 deaths and high excess deaths across many different countries.

In the case of Covid, "hospitalizations" are largely defined as "in the hospital with a positive PCR test", so this is a truism. Deaths are predominantly downstream of "hospitalizations", so again, this is a truism.

Any pathology in PCR testing would equally affect "hospitalizations" and "confirmed deaths".

Denialism and skepticism are often used as slurs in the absence of strong evidence by those who favor popular consensus over evidence.

A PI once confided in me that he didn't believe in the big bang. I was startled because creationism was on the rise, and I knew that he was Catholic. However, I also knew he was a natural empiricist, and after taking a quiet moment to think things through, I realized I was being tested to see if I could think critically and ask the right questions as a scientist.

He didn't deny the big bang, and he wasn't replacing it with a worse theory. After a few questions, he demonstrated that his understanding of the evidence and his tools to evaluate it were far better than mine, and that while it was the most probable and best supported explanation, because it was not observed and was not currently reproducible, it wasn't anything that warranted "belief".

Reality doesn't require our consent to exist.

> Denialism and skepticism are often used as slurs in the absence of strong evidence by those who favor popular consensus over evidence.

OK? That doesn’t change the massive weight of evidence in favor of HIV causing AIDS.

Somebody so pretentious to claim he doesn't "believe" HIV causes AIDS should be inoculated with HIV and settle the debate.

Last year I discovered this fact about Mullis and became very curious about how such an eminent scientist could have believed that about AIDS. But, I'd also realized by then that a lot of the so-called "science" about COVID was nonsense and based on invalid methodologies, that often scientists knew their results were wrong but published them anyway, and the whole system seemed hopelessly corrupted by bad incentives. So I didn't write it off, and went looking for his justifications.

It turned out Mullis had written an introduction to a book called "Inventing the AIDS virus" by a (former?) virologist called Peter Duisberg. This introduction laid out his case quite clearly and the book went into great detail, elaborating a theory about why AIDS and HIV are not in fact linked.

I ended up not developing any strong opinions about the merits of the theory, but I will say that it is a scientific theory and not easily dismissed. To do so would require a lot of detail because the people arguing that HIV isn't the cause of AIDS are scientists and have many scientific arguments.

Here is a brief tl;dr summary of Mullis' argument:

1. In the 1980s when AIDS was newly discovered, he was writing a paper about the use of PCR in the detection of HIV. He wrote "HIV is the cause of AIDS" and decided he should provide a citation for this claim, but he wasn't sure which paper actually established this. To his surprise, when he asked around, nobody else seemed to know which paper he should cite for this either, despite it being a by-then standard belief.

2. As he broadened his enquiries and did more research, he came to realize that nobody knew what paper to cite for this claim because none existed.

3. When he tried to find out why there was no paper proving the link between HIV and AIDS, he concluded the whole thing was built on groupthink and a strong desire by certain researchers for it to be caused by a virus, as the field of virology was at that point in deep distress due to the apparent lack of any serious viruses on the scene after the defeat of polio and the lack of any meaningfully sized link between viruses and cancer.

The Duisberg book then elaborated on exactly what was going wrong in a lot of detail, most of which I've now forgotten. But a few claims really stood out to me and I double checked them after reading the book. My fact checks passed, increasing my confidence in Duisberg's claims:

1. That the gender ratio of AIDS victims is radically different between Africa and the west. In the west, AIDS victims are predominantly men and always have been. In Africa there is no gender skew. This makes no biological sense because HIV is a very small virus and cannot know the gender of its host, let alone know/care whether the host is in Africa or not, at least not according to any current theory of genetics or biology. Duisberg provides a much simpler explanation: once AIDS hysteria reached a high enough point, western aid agencies started handing out money in proportion to reported AIDS incidence in a region, and handing it directly to doctors. Combined with the vague nature of AIDS symptoms (it's a syndrome, so the symptoms are the symptoms of whatever disease your broken immune system can't fight off), this gave a strong incentive for doctors to mis-label cases as AIDS in order to get more cash for their clinics.

I verified this claim against a database held by ourworldindata, if I recall correctly. Although the book is old, the claim is still correct.

2. That at some point people started cropping up who had AIDS but were not HIV+. This posed a major problem to the theory, but it was fixed by inventing a new disease with an incredibly long and technical name that had identical symptoms to AIDS but differed only in not testing HIV+. In other words, at some point having a positive HIV test became a "symptom" of the disease, and cases where it was missing were retroactively redefined as "not AIDS", thus making the theory unfalsifiable.

I verified this claim was true by looking up the Wikipedia page and a scientific paper talking about the "AIDS without HIV" disease and confirming the description. Unfortunately I can't remember now off-hand what it was called. I'd have to dig through the book. I recall Duisberg asserting that the name appeared to have been chosen to be very difficult to remember, and I'm inclined to agree.

Note: the same thing has happened with COVID, in which having COVID requires you to have a positive COVID test rather than any specific symptoms.

3. That (western) AIDS never broke out into the heterosexual population in the way that was predicted. That should have happened if AIDS was in fact caused by a virus and AIDS researchers therefore routinely predicted that it would happen ... but it never did. That makes no sense for a disease caused by a virus.

After reading the book I went looking for debunkings of it. The only ones I could find were very poor and mostly concerned with whether Duisberg should be allowed to speak at all. Of the remainder they made arguments that Duisberg had already successfully tackled in his book, so I wondered if there might have been multiple editions. At any rate, it's clear that "mainstream" AIDS science had chosen to simply ignore the problems flagged by Mullis and Duisberg. Given the behavior of health researchers with COVID science I can easily believe the same problems existed back then too.

I'm no expert, but it seems that the dramatic successes since 1996 in treating and preventing AIDS using antiretroviral drugs to suppress HIV viral load would be a pretty solid debunking.

It's probably just worth reading the book as I have only summarized a tiny fraction of it, and I suspect any debate about the topic could end up as just re-writing the book in forum comments. Obviously Duesberg discusses the history of AIDS treatments. Indeed it doesn't discuss treatment history after the book was written, but it makes a convincing case that the AIDS treatments that did exist up to that point were fraudulent in various ways and being presented as successful whilst actually killing patients (this is the justification for the book, in fact).

If I recall correctly, the gist of his argument is like this:

1. When AIDS was new scientists confidently predicted that everyone who caught HIV would die within a year or so. But then people who were HIV+ kept living longer than a year. Rather than treat this as evidence against the link, 'the science' as we call it these days kept being retroactively changed to stretch the supposed incubation period of HIV. This kept going until HIV was claimed to be able to hide non-active for a decade or more.

2. At some point AZT and other anti-retrovirals were developed. These were extremely toxic treatments because they work by stopping cells dividing. They're more like a form of chemotherapy. The drug trials didn't follow the rules of good trials and became hopelessly corrupted, e.g. patients were able to unblind themselves as to whether they were in the placebo group or not and then started trading with others who weren't. They had been told they were guaranteed to die without treatment, so obviously everyone in the process was highly incentivized to get their hands on this supposed miracle drug via fair means or foul. There were many other problems with the trials but that's the one I remember.

3. Not surprisingly given the nature of AZT, people put on it frequently ended up dead even though they hadn't previously been sick. This was interpreted as a failure of the treatment to treat the finally appearing AIDS, rather than the treatment itself killing the patient. The picture was muddied by admissions that of course this therapy had extreme side effects, but it was justified by the guarantee of death that came with HIV.

4. Nonetheless, they kept decreasing the dosages and mixing it with other drugs to reduce the toxicity of the treatments. This was then written up as improvements in the treatment. Duisberg argues they merely kept making a treatment known to be toxic less so. Because (in his theory) HIV wasn't killing the people in the first place, this then led to improving life outcomes which were interpreted as a success for medicine.

5. At this point the HIV/AIDS theory became unfalsifiable. Because HIV was claimed to be a special virus that might kill you very quickly, or might wait decades to do so, everyone with it was given treatment. If they survived a long time, the treatment was the cause. If they died, HIV was the cause. Regardless of what happened the data was interpreted in such a way as to reinforce the theory. Any evidence that disagreed with it was swept under the carpet or fixed via redefinitions, like the addition of HIV positivity to the required symptoms list for AIDS that I previously mentioned.

If you'd like more background then this article by a former science journalist who worked at the Sunday Times might be interesting. At first he believed what he was being told about AIDS, but eventually decided he was being misled and came to feel guilty about his role in promoting AIDS hysteria. He wrote about his experiences here:

https://dailysceptic.org/immunity-hysteria/

https://dailysceptic.org/new-variant/

Seems weird to me. My brother in law literally works with HIV every day in a biology lab. There are thousands of academics who do the same. Why would they bother if it was just some random virus?

I can't really speak to the arguments you've presented. Frankly, they seem totally explicable for any number of reasons, but it's not my field. My feeling is simply that tons of people who work in the field believe that HIV causes AIDS (it also totally makes sense to me you could have an immune deficiency without some specific virus, but whatever). So I believe it. If tomorrow, it's discovered not to be the case, I'll probably believe that too. It's not my field, so why would I have a strong opinion? What's the point of even reading a book about it, unless you're working in microbiology?

If you look at what happens to the scientists who dissented, it's no real surprise that nobody investigates this any more. Look at this thread. Mullis invented the PCR test and won a Nobel prize for it, but his beliefs about AIDS were immediately written off without investigation (except by me) and in fact used as a reason to attack and undermine him. Now what happens if you raise questions about this without being a Nobel prize winner? The HIV faction won decades ago, fighting it would be impossible.

Science is often said to be self correcting. I no longer believe this. Rather it's ridden with groupthink, politics and power games. I watched in 2020 as the scientific "consensus" about COVID models became defined by whichever factions were most aggressive, most shameless and most willing to lie, despite the evidence right in front of my face. Like I said, I never developed a strong opinion on the "HIV not the cause of AIDS" theory, partly because I don't really care. COVID is far more important. But could scientists end up collectively believing something that just isn't true at all for decades? Yeah, absolutely. I totally believe that's not only possible but quite likely. Scientists will still be claiming that COVID models worked well when we're all in care homes.

As to why anyone should care: because how do you know who to listen to, if you don't evaluate their past reliability? You say that you'll believe anything academics tell you because it's "not your field". Sounds like you might be a scientist? I think a lot of us would like to know what's true even in fields that aren't our own, especially because governments have a habit of making the pronouncements of scientists everyone's problem.

I'm not a scientist - I'm actually an ex-philosophy student.

I guess part of my feeling is, sure, science has problems (every scientist will tell you that) but are there better institutions to give us actionable information in the middle of a pandemic? My feeling is no. So, even if I accept your diagnosis of science as "groupthink, politics and power games", I'd say that's just humans. All institutions, all fields are like that. Nonetheless, science has a pretty good record for delivering more or less solid consensus assessments, so even if it does need some reform, I think it's a pretty reasonable bet that the consensus is more or less on the money.

Do we need institutions to give us actionable information? That starting point contains quite a few assumptions that aren't obvious to me. It's obviously convenient if you have such an institution that's accurate, and there's some logical and cost effective action that comes with it, but if no such institutions exist then the right thing to do is not trust one anyway.

On the topic of consensus specifically, I don't believe that's actually true. Science is full of people claiming there's a consensus but often when investigated it turns out not to be true, and instead there is an ongoing attempt to cover up or suppress disagreement. A claim of scientific consensus always needs to be checked, unfortunately, although that check can often be quite an easy one of the form "does someone make some well functioning technology requiring this belief to be correct".

There is no requirement that information come from institutions, let alone that it be actionable. If you look at where the most accurate information has been coming from throughout it's been bloggers, skeptics, bands of anonymous researchers like DRASTIC and so on. It's not good and it's not better than having trusted institutions, but all such institutions have been hopelessly destroyed from within, largely thanks to ideology. I see no reason to continue genuflecting at their feet of their smoking hulks. Perhaps better institutions will arise, or perhaps people will learn how to filter information and make decisions without being told what to do. Or perhaps both.

> Do we need institutions to give us actionable information?

We're at a point where scientific work is the sum of an enormous number of specialists, most of whom are only marginally able to judge the work of those outside their field.

That implies that, to engage with a scientific fact (say, global warming) you are always engaging with a gigantic aggregate of facts from an enormous variety of disciplines.

It's just not realistic for a layperson to absorb all the literature that leads to a consensus and come to an informed conclusion. Sometimes, people who are experts in their fields can do something on that level, but ultimately, they're making those summary judgements at the mercy of implicit or explicit consensus, hierarchy, reputation - all the elements of group-think that make up institutions.

I think what you're describing in regards to consensus is just what a consensus is. Take evolution for example: you can't imagine a more starker difference in views between like, Dawkins or Lyn Marguiles over what that word means. So there's a 'consensus', in that both of them are evolutionary biologists, but a dissensus insofar as what they mean by that. People, in a vacuum, have an infinite variety of opinions, many of which are superficially similar, but are different on a ton of subtle points.

There are a lot of problems in this kind of setup, but I feel if you're going to call institutions in western society 'smoking hulks' when it comes to trust or credibility, mainstream science is one of the last ones you should come to.

AZT was demanded by the gay community, in street marches and protests.

Well yes, because they had been told HIV was a death sentence and only AZT could save them. What relevance does that have?

It didn't help that the WHO released the updated guidelines the day Biden was inaugurated.

For that reason alone it became another thought-terminating political topic -- you're either dismissed as a conspiracy theorist for correlating these events, or you're dismissing the value of the vaccine rollout/lockdowns/other measures, or you're a sheep following the dominant media narrative.

It's harder to dismiss when you also consider the first vaccine approvals kept getting delayed until they were released immediately after the election.

Note that it was hardly “delayed” since all initial predictions for the vaccine to be approved were around 12 months, in the end it only took about 10 months.

Reports last year indicated Trump’s own FDA was responsible for setting out the needed time for data gathering and review that pushed it into mid-November. https://abcnews.go.com/Politics/white-house-okays-fda-months...

Meanwhile other countries including China and Russia didn’t approve their own vaccines faster, seeming to indicate the timeline had little to do with U.S. politics.

It is worth considering that maybe Sinovac (and whatever the Russian one(s) is/are called) may have been released far earlier than they would have been if the U.S. and others had not developed their own faster. Think of space wars - even if you lose the race to first, you still want to be in 2nd vs 500th. If they were developed at a more traditional pace, would they be more effective? Would any of them be? And what would be the consequences of waiting? Would it be millions more deaths, or would natural herd immunity emerge? Both? Would the more virulent variants have appeared without a marginally effective strain evolving as a result of marginally effective vaccines?

The alpha variant (B117) emerged in the UK in November 2020, there’s no indication it had anything to do with vaccines. The delta variant (B.1.617) was detected in India in October 2020. So saying the vaccines caused these variants to evolve would suggest that vaccination also has a time-travel component?

Both Russia and China started using their vaccines in August 2020:

https://www.nbcnews.com/news/world/putin-claims-first-corona...

https://www.reuters.com/article/us-health-coronavirus-china-...

As your article notes, Russia was similar to allowing people to join the phase 3 trial. It was not a widespread deployment of vaccines and was not analogous to the EUA for Pfizer and moderna. “In effect, Russia will be conducting its Phase 3 trials live, treating it more as a demonstrator group than a control group meant to ensure there is nothing dangerous awaiting the larger population.

The first two phases involved just a few dozen volunteers.

Phase 3 trials will be conducted not only in Russia but in partner countries including the United Arab Emirates and Saudi Arabia, Dmitriev said in Tuesday's statement.”

According to https://en.wikipedia.org/wiki/Sputnik_V_COVID-19_vaccine#Aut... the first authorizations outside Russia occurred in December 2020.

Similarly for the Chinese vaccine it took time for the trial results to arrive. Sinovac was approved for general use in February 2021, months after the FDA had authorized Moderna and Pfizer vaccines. https://www.scmp.com/news/china/science/article/3120855/covi...

Aren't their vaccines significantly less effective than Moderna, Pfizer, etc.? In that case, I'm not sure we should let their earlier release reflect negatively on those that took longer to be ready. On the contrary, maybe we should instead consider the possibility that the Russian and Chinese vaccines were rushed.

That definitely smelled like an intentional muddying of the waters.

Things that occur after the election, such as changing testing standards, do not affect the election

so what does correlating these events have to do with anything while ignoring verifiable causation, such as the WHO already having documents about these changes going back to September 2020

On inauguration day.

Sure, and it could be political. In fact, most things of this nature are at that level. So, maybe, the people in charge didn't like the previous US government admin so they didn't help improve its numbers.

That is certainly more likely and believable than some vast left-wing conspiracy to implant Bill Gate's microchips in to your iPhone carrying ass to "track" you.

Instead you're just talking about a left-wing conspiracy to lie to the public in order to take control of the government.

Things like that make people suspicious, and make it easy for people who don't know the difference between a quantum dot[1] and a microchip to misunderstand when Bill Gates calls for a national tracking system[2].

1: (a quantum dot to store medical information beneath the skin really was funded by Bill Gates)

https://news.mit.edu/2019/storing-vaccine-history-skin-1218

2: https://www.forbes.com/sites/mattperez/2020/03/18/bill-gates...

>Instead you're just talking about a left-wing conspiracy to lie to the public in order to take control of the government.

To take control of the government or for good PR/propaganda? Governments have never had any issues conspiring and lying to the public, remember when Fauci said not to use masks because they didn't help? Or those WMDs that we will surely find any day now?

I'm not who you're replying to, but I'd like to know, what reason would WHO or anyone else have to maintain a high false positive rate under one admin and correct it for the next, other than to lessen the chances of the previous admin's reelection? It wasn't "good PR" it was bad PR, specifically for the previous admin in an election year. That sounds a lot like "lie to the public in order to take control of government" to me.

Or using whatever agency they had to direct the US voters towards what they feel is more effect public health policies and stopping millions of unnecessary deaths?

Look, I am not defending anyone, I am saying that _all_ things of this nature are political.

Is there evidence that the cdc/other testing labs significantly changed their protocols as a result of this new advice?

Are you sure this is the right link? I looked at this notice, and compared to the previous version from December 2020 (https://www.terviseamet.ee/sites/default/files/MSO/2020_ohut...) and they appear broadly similar... there's perhaps a bit more upfront on the need to deal with weakly positive results, but they both tell you to read your device IFU and adjust your thresholds accordingly.

Probably changed post-publication. That's a super common thing now. And why you always need to both use an archiver site and possibly save a local copy.

Rather than speculate why didn’t you just do a google search? A quick google and check of archive.org finds the document released in December with an archive date of dec 16.

https://web.archive.org/web/20201216033740/https://www.news-...

This WHO statement has been widely misinterpreted, is is not the case that PCR tests were resulting in inflated numbers of false positives, see Reuters fact check [1] from February 4, 2021, and [2] from April 8, 2021.

[1] https://www.reuters.com/article/uk-factcheck-who-instruction... [2] https://www.reuters.com/article/factcheck-who-pcr-idUSL1N2M1...

“The WHO information notice is not a retraction; rather, it is a clarification for laboratory professionals on how to interpret PCR results.”

Why would WHO feel the need to tell people to read the operating manuals closely? I’m sure its not because the accuracy was too high.

WHO did give a good reason: “ WHO reminds IVD users that disease prevalence alters the predictive value of test results; as disease prevalence decreases, the risk of false positive increases (2). This means that the probability that a person who has a positive result (SARS-CoV-2 detected) is truly infected with SARS-CoV-2 decreases as prevalence decreases, irrespective of the claimed specificity.”

Given that reason, cause and effect would be hard to pick.

To a less-frequent degree than with 'cases' the meaning of 'gold-standard' seems to have changed as well, or be starting to. As I understand it, a proper gold-standard test is proven to have essentially 100% correlation to verified clinical symptoms or findings.

Please correct me if I am wrong, but I feel like you are trying to say more with "but then 'cases' became some kind of top-line media metric".

Should cases not be an important metric for people to know?

I think his point is that having a minute amount (possibly non-viable) of viral DNA in your respiratory tract does not necessarily make you a true "case" in terms of being actively infected with the virus.

He's saying the definition of cases in 'actual science' vs 'the media' is different.

Not a shocker that the media would sensationalize things.

Science and PCR amplification... has a much looser definition with the possibility for much more false positives with such small number of cycles of amplification.

It was done ostensibly for cautionary purposes but the media seized on it and painted red death map visualizations for people to see with inflated death counts.

I understand that. But I would hardly call it sensationalizing. It's a mixture of the best of what we had at the time (others have posted talking about how the tests have changed/improved), and the fact that reporting on things in a simple and straight forward manner is hard because people simply don't have the time, or don't give a shit about nuance.

I suspect that a pattern of not disclosing that statistics that are implied to be factual are actually to some degree ~estimates contributed to the extreme level of polarization over "facts" and "the science", as well as the increasing distrust of the media. Sure, most people don't consider these things too logically, but then if those distributing the facts can't be bothered either, how shall we accurately assign blame for the final outcome?

>how shall we accurately assign blame for the final outcome?

That's a feature not a bug.

Whose to blame for 60,000 people dying in Vietnam?

Whose to blame for Lobotomies winning the Nobel Prize?

Whose to blame for Thalidomide being widely distributed?

Almost anything can be passed off as legitimate without accountability with a concerted effort by 'authorities' and the 'news media', it's even worse in the modern short attention span news cycle.

Who's to blame for 600,000 dead in the United States?

The average death is 80 years old with two comorbidies so....the natural cycle of life?

There's nothing natural about dying from COVID-19, except in the broadest of definitions of "natural" (i.e. the definition that we developed technology to minimize, control, and avoid).

I don't know how you define Natural.

It's a good question and definitions vary. My working, broadest definition is "That which exists / that which occurs if humans do not use their intellect and ability to cause something else to exist / happen."

Starvation is natural. Death by predator is natural. Death due to exposure is natural. Death due to disease is natural. Tornadoes are natural. A biosphere-disrupting asteroid impact is natural. There are other things that are natural that are positives too, but it's good, I think, to keep in mind that "natural" doesn't always imply "good."

The true (accurate/correct) multi-dimensional causality is unknown.

It's looking like the reported numbers may be over-estimated by one or more orders of magnitude....that's the definition of sensational.

This is completely contrary to what "excess death" statistics suggest, which is that we might be under-counting COVID deaths by quite a bit. We've had many more unexpected excess deaths in 2020 and 2021 than can be explained by the official COVID death counts, so it's highly possible that some COVID-caused deaths aren't being recorded as such.

It could be that a bit more than 625,000 people have died in the US due to COVID. Or it could be higher than that, and it may be a couple of years before we know for sure. It's not lower, though. Not at all.

> red death map visualizations for people to see with inflated death counts.

There is no indication of inflated death counts. Death counts from covid correlate closely with excess deaths.

Some have claimed that deaths did rise but because of lockdowns, however in “locked down” regions where reported Covid cases and deaths were low, so were excess deaths.

If you inflate infections, you are therefore are also inflating deaths, it's a 1 to X correlation.

Wrong, all-cause death statistics are tracked separately from infections. See for instance https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm

How does reporting things that have nothing to do with covid separately have anything to do with it?

Cause of illness is linked to cause of death and they will track proportionally.

You can see that covid-19 related deaths aren’t “inflated” by comparing the numbers to excess deaths and seeing they correlate (not just nationally, but by region and time).

When 100,000 people are reported to die of covid in the USA or another western country with a high quality reporting system, in the same region and time around 100,000 more deaths from any cause are recorded than would normally be expected. Therefore, there’s no reason to believe the covid-19 deaths are inflated (the “with covid not from covid” theory).

Edit: see for instance https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/t... which is visually quite striking. Figure found in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7852240/

Ah that's interesting. Thanks for sharing. Here's a good visualization as well. That looks pretty indisputable.

https://ourworldindata.org/excess-mortality-covid

"The raw death count helps give us a sense of scale: for example, the US suffered roughly 360,000 more deaths than the five-year average between 26 January and 3 October 2020, compared to 209,000 confirmed COVID-19 deaths during that period."

The Covid death counts may be correct or a even little lower than expected then.

Further confirms my thoughts that I would not like to be an 80 year old with two co-morbidities around Covid.

So you quote an eight-month figure, ignoring the nearly-nine months since then, and still cling to your narrative even when presented with facts that directly contradict your earlier assertions. Okay.

Try some math: 360,000 deaths higher than average over 251 days is 1434 excess deaths per day. From Oct 4 through yesterday is another 296 days, and 1434x296=424,464, so we're talking about a scale of around 780,000, which very much supports the total US COVID death count of 627,370.

If you think that's all 80-year-olds with multiple pre-existing conditions, and that you therefore have nothing to worry about, then I hope for your sake and the sake of those around you that you aren't proven wrong by an ICU stay.

????

Read my comment again.

Prior to the vaccine rollout (at least in the US), positive cases were used as a metric for public health officials to gauge whether the virus was spreading, whether containment efforts were effective, and how to manage the presumable change in hospitalizations and fatalities.

As vaccination efforts have rolled out, there is still a relationship between positive cases and deaths, however the ratio of cases to deaths has dropped dramatically.

If you Google "uk covid cases" and flip between new cases and deaths you will notice that the "2nd wave" in December/January had an increase in deaths 2 weeks after the increase in cases. The "3rd wave" has had a large increase in cases but no resulting massive increase in deaths.

The only metric the public should be concerned about is whether they have or have not been vaccinated.

>The only metric the public should be concerned about is whether they have or have not been vaccinated.

That would be quite stupid. Because if the risk of the disease is low, vaccines does not make sense when you do risk/benefit calculation.

Hence the people should know about the cases.

Of course, instead, if you are looking to push vaccines no matter what, you would say something like

>The only metric the public should be concerned about is whether they have or have not been vaccinated.

> That would be quite stupid. Because if the risk of the disease is low, vaccines does not make sense when you do risk/benefit calculation.

The risk of symptomatic illness is low if you are vaccinated. The risk of symptomatic illness is high if you are unvaccinated. The risk of death is high if you are unvaccinated and have pre-existing conditions and are under the age of 65. The risk of death is very high if you are unvaccinated and over the age of 65.

Please cite studies with randomised control trials to justify these claims.

Regardless of number of cases, most of us will be exposed to SARS-CoV-2 eventually. Just like with other endemic coronaviruses such as HCoV-OC43.

>Regardless of number of cases, most of us will be exposed to SARS-CoV-2 eventually.

If the no of cases is nearly zero, that means the virus is no longer dangerous, so it does not really matter at that point.

At the latest low point in the epidemic, some areas were seeing test positivity rates of under 0.5%. If false positives were a large portion of positives, this would seem to be impossible.

> At the latest low point in the epidemic, some areas were seeing test positivity rates of under 0.5%. If false positives were a large portion of positives, this would seem to be impossible.

Its quite possible, especially if there is a testing bias toward people who are less likely to have the disease

Even if they were testing people that were all externally known not to have COVID, if only 0.5% of people are testing positive, that's the false positive rate.

All the data we have indicates that false positives on PCR are extremely rare. The only place it gets fuzzy is the definition of positive. People who were previously infected can test positive, and people with very mild infections can also test positive. People who have never been infected though essentially do not test positive.

The problem is the false positive isn't truly independent of environmental factors.

PCR determines how many exponential amplifications are necessary to get a detectable amount of the target RNA sequences.

The amount of that target RNA floating around in the environment does slightly impact the base amount present in even covid-negative patients.

It's true that people who had COVID can still have viral RNA in their noses for a while and still test positive.

The most sensitive tests have a limit of detection of a couple hundred copies/ml, and the collection kits usually use 1ml of VTM or equivalent. I find it hard to believe that a significant number of people will have enough viral RNA in their nose to put hundreds of copies onto a swab unless it's their own body that's producing those copies.

> I find it hard to believe that a significant number of people will have enough viral RNA in their nose to put hundreds of copies onto a swab unless it's their own body that's producing those copies.

This has been confirmed in studies. Researchers have taken samples that are PCR positive at various cycle counts, and tried to culture viruses from them. Here's one:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427302/

"RT-PCR cycle threshold (Ct) values correlate strongly with cultivable virus. Probability of culturing virus declines to 8% in samples with Ct > 35 and to 6% 10 days after onset; it is similar in asymptomatic and symptomatic persons."

(Note: this is not the only one of these papers that has been published. This is just the first one I found with a quick search.)

ANY molecular biologist will tell you that it's NOT.

At 30+ cycles, you are generated false positives off of both everyday Common Cold coronavirus, influenza and probably even bacteria. Literally you are amplifying noise and then calling it a positive.

It is worth noting here, as you didn't say it explicitly, that COVID labs routinely report positives as late as 40 cycles.

This link was often cited by fact checkers last year.

“Most tests, like the Broad Institute test used by MIT, use a 40-cycle protocol. If the virus isn’t detected within 40 amplification cycles, the test result is negative. If viral RNA is detected in 40 cycles or less, the PCR machine stops running, and the test is positive. Because you received a positive result, we know that the test detected the virus in your sample by the time it reached its 40-cycle limit.”

https://medical.mit.edu/covid-19-updates/2020/11/pcr-test-re...

A PCR test that is sensitive is a great tool. Remember the NBA bubble? A less sensitive test would have allowed outbreaks inside the bubble, making some player sick and unable to play, as well as eroding the public's confidence on PCR tests.

Factories and meat packing plants used negative PCR tests to create their own bubbles and keep them running.

There is large positive economic value to a highly sensitive test with a small false negative and a larger false positive. There is much less economic value in a test that allows escapes (rapid tests).

> A PCR test that is sensitive is a great tool. Remember the NBA bubble? A less sensitive test would have allowed outbreaks inside the bubble, making some player sick and unable to play, as well as eroding the public's confidence on PCR tests.

A hammer is a great tool. It is not a great tool for repairing broken pottery.

PCR is the ideal tool if you want to detect infinitesimal amounts of a specific nucleic acid sequence. It is not a great tool if you want to use it to define "illness" or "infectivity", for it cannot tell you anything about those questions.

Can you use PCR to cast the widest possible net, and isolate literally everyone who has any shred of viral RNA? Yes. That's essentially what we've been doing. It is a strategy, and this strategy is appropriate in some situations. This strategy becomes a problem when you forget that you're allowing a lot of false positives to be caught up in the process, and start behaving as if "a positive" is a meaningful clinical diagnosis. Now that we have highly effective vaccines and are out of the acute phase of the crisis, it's time to adjust our definition of "infection" to more accurately reflect the true clinical meaning of the word.

this is at the heart of what "Covidiots", "Querdenker" and other tin foil hat people have been saying for more than a year ... just b/c you find a single virus or a part of it somewhere doesn't mean anything. but ... LOCKDOWN! and think of the children!

Well if you want to "control public fear" for political and economic gain, you just adjust the CT value as required to bump up the positive rate or to lower it.

Note that the US CDC is using two different CT values: a higher one for unvaccinated and a lower one for vaccinated. That doesn't make any sense until you start thinking Hobbsian/Hegalian/Machiavellian.

If I was wanting to exploit the situation, this is exactly what I'd do. Instead I have ethics however.

Is there any proposed logic behind the difference in thresholds between the two groups? It seems designed to do just one thing - overestimate cases in the unvaccinated, and underestimate cases in the vaccinated. What is the actual rationale the CDC provides?

Vaccinated people have a strong immune response to the virus, and presumably it would take a much higher viral load to make them clinically ill.

To me this seems like a much more plausible explanation for dual thresholds than some kind of conspiracy to inflate numbers for political reasons. Immunology is not my field though.

No. Nearly all EUA PCR COVID tests are qualitative. On saliva/sputum samples, that's really the best that can be done. They can report one or more Ct values, but those reflect specific characteristics of the platform and can not be normalized across platforms and cannot be used even to infer things like viral load.

Well apparently it is possible, and it has been done, probably more than once.

In his German language podcast Dr. Drosten, a Coronavirus specialist from Charite Berlin, is addressing this exact issue. In case you have never heard of him, his lab was the first to publish a working PCR test protocol for SARS-CoV-2 back in January 2020 [1]

Here is an DeepL translated excerpt from the transcript for his latest podcast [2]

"The whole thing has a certain complication. The Ct values that we have here are not easily comparable between the individual test manufacturers. Basically, you can say that a high Ct value always indicates a low viral load. And if the Ct value then becomes lower, then that also becomes a higher viral load. But we can only compare them numerically as long as we are in the same test system. The differences there are sometimes considerable. There are test manufacturers where a value of, let's say, 25 is nothing at all worrying, while the same value of 25 in another manufacturer's test shows that this is already a seriously infectious concentration. This is simply because these test manufacturers do not standardize on the Ct value. That would not make sense either. Instead, it makes sense to simply determine what lies behind the Ct values, namely the actual viral load. You can do that, you have to calibrate that."

and further

"We did that in the fall. All the laboratory work that is necessary for this was done in September and October. I had already explained that to the public in the summer, how that works. We worked in the lab to make this possible. We have also come so far that viral load standards... You really have to imagine it as a small plastic vial with a test solution in it. It contains killed virus of a known, defined concentration. You can order it in two or three defined concentrations from a company that sells such a thing. The purpose of this company is to provide quality assurance for laboratories and to offer the necessary calibration standards. And these calibration standards are produced here in our laboratory, this killed and exactly quantified virus. So we have produced this calibration standard. We have also developed instructions, which are then recommended by the Robert Koch Institute, on how the laboratories can use this calibration standard to convert their Ct values into viral load ranges, which either actually lead to an exact viral load or which - and this is our recommendation - lead to assessment ranges. And that is to an assessment of highly infectious, low infectious, and borderline. So roughly speaking, that is expressed a little bit more genteel and precise. There's even a recommendation on how to express that on the medical findings then. Medical laboratories can do all that. This is also done in practice in the hospital sector. routinely used for discharge decisions. For example, a patient is in the intensive care unit. He is getting better. He should be transferred to a normal ward. Now the question is: Can we do that? Is he still highly infectious? Then a quantitative PCR test is carried out with these findings."

[1] https://www.eurosurveillance.org/content/10.2807/1560-7917.E... [2] https://www.ndr.de/nachrichten/info/coronaskript306.pdf

Do you have source for that claim? I tried to find that recommendation, but all I came up with, was this fact check [1]. According to the fact check the CDC did NOT change cycle threshold, and the thresholds used to decide if test result is positive, are not different for vaccinated and unvaccinated. The quoted 28 cycle threshold is apparently only used for deciding if a sample can be submitted for sequencing.

[1] https://www.politifact.com/factchecks/2021/jun/03/tweets/cdc...

Also, PCR is not one test, one method, one process. There are hundreds of distinct PCR-type molecular nucleic amplification tests. CDC guidance would only apply to the one process they provide/support. For a survey of the ecosystem and the difficulties in standardizing Ct values, see e.g.

https://www.aacc.org/science-and-research/covid-19-resources...

https://news.ycombinator.com/item?id=27995222

Imagine the CDC yelling: "Don't throw that away! I need more details! Please! If you won't finish the job, please let me do that work!"

That's my translation of the document I found when looking into this issue. More details below...

===

"CDC is suggesting CT value of 28 for detecting breakthrough infections after vaccinations... So that means, a breakthrough infection needs to have 128 times viral load in someone who has been vaccinated to be considered as positive, than it is required to have considered as positive in a non-vaccinated person."

This sounded strange to me, so I searched for more information about it. It looks like you just misunderstood the CDC's policy.

This document regarding breakthrough case investigations was the second result in a Google search for "cdc ct value 28". The relevant text can be found on page 5 of that document.

https://stacks.cdc.gov/view/cdc/105217/cdc_105217_DS1.pdf

"If SARS-CoV-2 sequencing will not be performed locally and a specimen is available, the state public health laboratory should request the residual clinical respiratory specimen for subsequent shipping to CDC. For cases with a known RT-PCR cycle threshold (Ct) value, submit only specimens with Ct value <=28 to CDC for sequencing."

In other words... Imagine some lab just found a breakthrough case. And this breakthrough case had an especially high viral load (Ct 28). And the lab was just going to report a positive and throw away the sample...

Imagine the CDC yelling: "Don't throw that away! I need more details! Please! If you won't finish the job, please let me do that work!"

That's what the document is saying. There's a rare event that needs extra analysis. CDC is just letting the labs know in advance that if they ever see this event, and didn't have the resources to fully analyze it, please send that sample to the CDC so it gets the attention it deserves.

Nothing to do with whether the test is considered positive or a breakthrough - just about whether to put extra effort into gathering more details on that particular case. CDC is volunteering to do this extra effort only for higher Ct values. Whether or not they do this extra work, it's still a positive result either way.

I am not sure I like someone vocalising CDCs thought. It is kind of disturbing. I mean, you can be cutting someone throat and saying "be quite my child, it is all for best"..

anyway here is what I have responded to a similar comment

https://news.ycombinator.com/item?id=27995222

Very disappointing that the top comment on this article is COVID misinformation. The forcry account was created 3 weeks ago and specializes in COVID misinformation.

No, CDC isn’t messing with the tests like this. And all this fancy talk about CT values is just cover for a false statement about CDC policy.

It is not misinformation.

This is the actual document that provides guidelines to labs to assess breakthrough infections

https://www.cdc.gov/vaccines/covid-19/downloads/Information-...

but it is no longer available at that location, for some reason, and here is a link to the old version..

https://web.archive.org/web/20210429184157/https://www.cdc.g...

Also, nice try to look up and discredit what I am saying on the basis of the age of my account. I am afraid such tactics won't fly well here.

So forget breakthrough infections for a second.

Covid has both pre-sympomatic AND asymptomatic transmission. This has been proven.

In many places, a negative PCR test means you do not have/carry the disease and can participate in risky activities. The NFL, and the NBA, did this. Movie studios did this. Australia and New Zealand did it as a whole country.

To do that, you need a very sensitive test, not something that only confirms symptomatic infection.

Of course, a very sensitive test has more false positives. But you have to weigh that with the possibility of an outbreak among those who tested negative. Imagine what would have happened if NBA had an outbreak after PCR tests--"The Tests Are USELESS!" the media would say.

How many false positives? Look at how many players sat out during the NBA bubble.

Now back to breakthrough infections. The CDC's thought is that vaccines protect well against existing strains, and their guidelines follow that assumption. Nothing in their guidelines accounted for the Delta, though they are changing their stance now, but slowly.

>To do that, you need a very sensitive test, not something that only confirms symptomatic infection.

Now, that makes sense.

But you have also take into account that these are not just numbers. But these are numbers that can destroy countries and communities by implying perpetual lockdowns.

It becomes even more comical that RT-PCR does even when positive, does not imply presence of the virus, but some fragments of a dead virus or even genetic material of some other viruses.

I can only be appalled at the indifference of these people to mandate lockdowns that destroy lives and businesses, based on positivity rate of such a test.

This pandemic is a lie. Get over it and act accordingly.

What a shitty headline. Completely obscures the point of the article.

hmmm is this a new variant?

or have they got bad testing processes outside of hospitals? So many things this might be...

The main point of the article (at least as I understood it) is that I could be hospitalized for an open fracture in my leg, tested for COVID while there, test comes back positive (either true or false positive) and be counted as a "hospitalized COVID case".

but couldn't this also mean? :

false positives new variant that infects but doesn't overtly affect or maybe a larger number of asymptomatic types than originally thought.

what suggests to you that there is any notable number of false positives?

Primarily that "all lab tests have errors" and if you test everyone who is hospitalized for any reason (which is sensible), you're inevitably going to get some false positives.

Secondarily, in any low-incidence scenario (such as might be the case for "COVID infections among the vaccinated"), even high specificity tests have a high false rate among positive tests.

Not an epidemiologist, but prior to Covid I have never seen a professional risk-benefit discussion around screening tests, which did not give serious weight to the various costs of false positives. Patient anxiety. Rounds of invasive biopsies not without risk. Financial costs of the same.

I agree (and declined a particular medical screening test [with the advice and consent of my doctor] at my most recent physical because the overall outcomes are worse for testing than not).

I think this one as applied to COVID is some mix of fear and human logical frailty. I can only imagine the hue and cries that we'd get if "Hospital XYZ isn't even testing all their patients for COVID!" came to light. That could be used to feed into the "COVID is a hoax!", "Insurance companies are evil; we need single-payer so that costs don't become an obstacle", and many other narratives.

The vaccine is rendering infected people asymptomatic. So they never think to get tested because they don't feel sick. Then they break their leg, go to hospital, get tested as a matter of course, and now get counted as someone hospitalized with COVID.

Or they feel vaguely sick, it feels like a flu (due to delta having more cold-like rather than covid-like symptoms) and go to the hospital without getting tested for COVID first, and then get tested in the hospital.

We don't know, the data doesn't say.

>The vaccine is rendering infected people asymptomatic.

woo didn't think of that. that would be not so great if still infectious.

Misleading article since as they state "44 per cent involved people who tested positive in the 14 days before hospital entry. A further 43 per cent were made within two days of admission". Thats 87% are positive within 2 days of start of admission but the article is very blustery about the non-common case that people test positive after discharge for some non-covid admission reason.

They say this in the article, so I'm not sure how it's "misleading".

The point (which the article discusses) is that it's fairly unlikely that someone being admitted for severe Covid has not already had at least one positive test prior to admission.

It's entirely misleading. They don't write 87% of patients tested positive before or early on in their admission. Even, the headline is written to convey the opposite. What they are doing is breaking it into two numbers that are each less than 50% to obscure the magnitude of the sum and then lumping the second number (patients who tested early in their admission) with those who tested positive later. It's easy to overlook that testing positive in the first 2 days of admission includes people who test positive at t=0 of their hospital admission, people who did not get tested prior to arriving at hospital. It's more amazing that 44% tested positive prior to arriving at hospital!

But all of that is besides the point because the reported statistic wasn't even labelled or reported by the original source (the NHS) as "covid as cause of admission." The stat is labelled "covid positive admissions" which is not logically equivalent to "covid, as primary cause of admission" The article does mention this distinction but they've already led readers on by framing things and setting the scene for FUD/ suspicion toward public health institutions. Knowing how many patients that were admitted and were covid positive is a useful statistic to be tracking on it's own right without necessarily attributing the admissions to covid. I'd imagine the report that they plucked this single statistic from from is filled with lots of other data which may include numbers that more closely track attribution of the admission to covid. The article implies that bad decisions are being made on account of this single statistic, which is hard to believe or should be better supported in the article's reporting if that is the intended takeaway.

Also, consider the usage of the word "leaked" in the article and reconcile that with the statement "the leaked statistics come from NHS daily situation reports" I'm not even sure what they mean by leaked, do you? The NHS is not the GCHQ, their data isn't exactly classified top-secret. The entire article is written to leave readers with the impression that the wool is being pulled over their eyes by public health institutions. It plays into paranoia and distrust toward government and public institutions.

> It's entirely misleading. They don't write 87% of patients tested positive before or early on in their admission.

Well, no, they didn't. They wrote the entirely true statement that over half tested positive after admission.

The fact that you disagree with one possible interpretation of this fact does not make it misleading. It's just a fact.

(I will grant you that the subhead is sensationalized, but the title on this one seems fine to me, and the article is fairly balanced.)

> It's more amazing that 44% tested positive prior to arriving at hospital!

It isn't "amazing"...we've been mass-testing for the better part of a year. I'd be shocked if most people who show up to the ER with respiratory illness didn't have a prior test result.

> But all of that is besides the point because the reported statistic wasn't even labelled or reported by the original source (the NHS) as "covid as cause of admission." The stat is labelled "covid positive admissions" which is not logically equivalent to "covid, as primary cause of admission"

Well, yes. That's exactly the point. Maybe you are not surprised by this, but a great many people are. And when you see that half of those "covid positive admissions" were only confirmed after admission, then it starts to raise alarms.

https://twitter.com/CT_Bergstrom/status/1421554277319729153?...

Comments so far seem to misunderstand the issue. People are not catching Covid in the hospital. They are in the hospital for non-covid reasons (broken leg, pink eye etc) but if they test positive it will show up in statistics as a "Covid Hospitalization". That is terribly misleading because we want to understand if Covid is causing an increase in hospitalizations, this is attributing other causes to Covid.

I mean, they may be catching covid in hospitals, there's no way to know for sure, but it seems unlikely to account for all these cases.

But yeah this is going to be picked up by covid-deniers as more "proof" that covid is exaggarated.

I am not by any means a "covid-denier," but it seems to me this is evidence that the impact of Covid may be exaggerated. It's hard to say by how much (and I would be interested to learn if this is happening in US hospitals also).

> this is evidence that the impact of Covid may be exaggerated

I don't think so. When assessing the impact of Covid, we look at the change in overall, all-cause numbers, like all-cause deaths. (Which do show a big impact.)

The reason we watch covid hospitalizations is that it is a good leading indicator of covid deaths. The "leading" part is important, because that allows health policy to react faster to what's happening, which makes it more effective at reducing the impact of Covid.

(You may also worry that covid deaths are being similarly over-counted, but the all-cause death numbers tell us we're actually undercounting the overall number.)

Anyway, I guess ultimately we can't stop people from misusing the covid hospitalizations number, but it is a very useful number.

I don't think "Covid deniers" make up any significant percentage of the population, but that doesn't change the fact that this is proof that Covid is exaggerated.

I think covid deniers do make up a significant percentage of the population, and they would take this as proof of exaggeration even though it really isn't.

US has had 1M excess deaths. That's a million people more than usual. http://www.healthdata.org/special-analysis/estimation-excess...

How is this not proof of exaggeration? Somebody in the hospital for a broken leg being counted as a "Covid hospitalization" just because they also happened to test positive for Covid means that the numbers are inflated. Period.

Covid is real. Covid numbers are inflated. You're arguing against a fictional "Covid denier" boogeyman which doesn't really exist.

Regardless of why they were admitted they still had covid.

You’re trying to answer what sent someone to hospital, not who has covid.

Your paper isn’t fact. It is an estimated published by perhaps one of the worst modelers out there. The IHME has been publishing scary models that couldn’t even accurately predict what was happening the day they were published.

Not significant percentage?

https://www.politico.com/states/florida/story/2021/07/26/sel...

"People are not catching Covid in the hospital" that is nonsense. They are, and the question is how many. The next question is if it is a significant number, is there a good way to prevent it.

I think OPs point is that this scenario is not the focus or point of the article.

I should have said, that is not what the article is talking about. This is about miscategorization.

I know (anecdotally) of one person who was in the hospital for an orthopedic surgery, caught Covid during their 3-day recovery stay, then got pneumonia and ended up having to stay for 10 days.

Another issue that is skewing the data:

Early in the pandemic, the United States had an undertesting problem. Now we are overtesting those who are immune and asymptomatic. A person with immunity to the coronavirus will fight off an infection. But during and after the person’s exposure to the virus, it’s common for a low number of virus particles to be detectable in the nose. In medicine, we call this virus a “colonizer” — a pathogen that does not cause illness or spread the illness. It’s an incidental finding. But in today’s world of routine coronavirus testing of vaccinated people, these positive tests are inflating the number of positive cases in a misleading way.

https://www.washingtonpost.com/outlook/2021/07/21/covid-test...

The trouble is that there's this unfortunate tendency to try and deal with this by having different standards for what gets counted as a covid case depending on whether the person's vaccinated - either by testing vaccinated people less as suggested in that article or by interpreting the test results differently. Which makes all statistics about the proportion of people who catch Covid, are hospitalized with it, etc who are vaccinated complete and utter garbage - at that point you're not finding Covid cases amongst vaccinated people simply because you're not looking. It resulted in initial numbers out of Israel that seem to have wildly overstated vaccine effectiveness against current variants, and I suspect the same might be happening in the USA right now.

> in today’s world of routine coronavirus testing of vaccinated people

It's worth noting that the CDC is explicitly telling people not to do this:

If you’ve been around someone who has COVID-19, you do not need to stay away from others or get tested unless you have symptoms. (https://www.cdc.gov/coronavirus/2019-ncov/vaccines/fully-vac...)

Agreed that people are still doing it though. That seems reasonable to me given the mixed data around to what degree the vaccine prevents spread.

I haven't checked this as the full data the article was based on wasn't given in the article, but it wouldn't make much sense to count out-patients as part of the covid hospitalisation statistics, so I imagine that the word "hospitalisation" means in-patients specifically i.e. people who are sick enough to stay in a bed in a ward for a night or more, so things like pink-eye, fractures, even child birth (without complications) wouldn't count.

Very good point!

Am American, not UK, but have worked in hospitals and surrounded by family working in hospitals during the pandemic.

This is a grey area here, because people don't always "come in because of COVID," they come in for symptom X, which might be exacerbated or caused by COVID. If someone has a set of chronic diseases, sure they have that, but the question is "why did they come into the ED today?" The answer to that is sometimes COVID even though they didn't know it. How this looks on a hospital chart is really fuzzy because it depends on all kinds of things; ICD coding can be ambiguous.

There's also been some cases of COVID contracted in the hospital (the ones I have person familiarity with), but that is much less rare, and rarer as the year has gone on.

There are also cases of people coming in for reasons unrelated to COVID, and finding out they were positive just coincidentally.

There's also cases where it's really unclear.

Well let's see, covid is clearly airborne as proven several times in the past year and the one place guaranteed to have covid in the air from severe cases (shedding) is a hospital.

I'm more impressed with people at the hospital not for covid with an extended stay who leave without covid.

Imagine an emergency waiting room in the USA.

I went to a US emergency room during the peak of a wave. Everyone was masked. They also did COVID-19 symptom tests before admitting people. This isn’t perfect, but it greatly reduces the odds of having some person with unexplained “breathing problems” or whatever accidentally contaminating the ER.

As opposed to the Covid-skeptics, I tend to view the rules and regulations as half-assed, based on last year's information, and not enough. You wrote "Everyone was masked" as if that's enough. Hopefully the room was well ventilated, because if someone had been breathing out virus particles for a long time in a stuffy room and you walk into it, it's probably very likely you'll breathe in the virus, especially if you're just wearing a surgical mask and not N95.

https://english.elpais.com/society/2020-10-28/a-room-a-bar-a...

There is absolutely zero evidence offered to suggest that the majority of these cases are people with broken legs who test positive.

SARS-CoV-2 causes heart attacks and strokes due to thrombogensis, particularly in the younger adults.

If someone strokes, they can be admitted for that and then later test positive, and the cause was most likely COVID and counting them is essentially accurate.

Since most old people have been vacccinated we are mostly now seeing the younger unvaccinated crowd coming down with COVID and it isn't very surprising that there's a lot more thrombogensis now than ARDS.

That’s a pretty generous interpretation that offers about as much evidence as the article does for the opposite.

Link is paywalled on mobile, thanks for the archive. Hospital tents that house the plague victims would be safer for regular hospital patients who were not originally infected. Doctors and nurses interacting with plague victims shouldn't work with any other patients and should stay in the quarantine zone until they are cleared.

Have you been to an ER recently? At least at my hospital this is exactly what they do. There’s a tent next to the ER entrance. They ask a bunch of questions about symptoms and do a temperature check. If you appear COVID+ they send you to the tent, otherwise you go to the regular ER.

The doctors and nurses work with non-covid patients and covid patients, it could be that the state I'm in hasn't gotten the memo.

Off-topic, but there could come a day when it is safer as a regular patient to be operated upon in a makeshift tent.

A doctor with Doctors Without Borders once said in an interview that with field tents, they did not have problems with the usual hospital-borne infections. He said it was due to the constant turnover of air and organisms.

Could you tone it down a bit, please?

In common English parlance "plague" or "the plague" almost always refers to bubonic plague or diseases caused by the same bacterium (https://en.wikipedia.org/wiki/Bubonic_plague).

COVID and "the plague" have very little in common. In particular the former is caused by a virus, the latter by a bacterium. Beyond the obviously different types of pathogen, their symptoms, mechanisms of transmission, prevention, management, and treatment are also quite different.

Moreover using unnecessarily incendiary language to discuss COVID, even if you think you're just being funny, isn't helpful because it's too easy for people to misinterpret.

"A further 43 per cent were made within two days of admission, with 13 per cent made in the days and weeks that followed, including those likely to have caught the virus in hospital."

While I'm glad that they're looking at this, it seems less shocking than at first glance. This looks like 13 percent of those who are currently listed as Covid hospitalisations, were actually there for other reasons. Of the rest, nearly half had not bothered to get a covid-19 PCR test before going to the hospital.

Given that this group is (we know from other sources) quite disproportionately from those who did not get vaccinated, is this surprising at all? They're people who for whatever reason shun interactions with medical procedures until they are in desperate straits.

Now, the 13% who were did not test positive until more than a couple days after admission, that is something that should be investigated. But it wouldn't change the current picture hugely.

They don't really explain much about that 13%. So it's a bit misleading. How many of the 13% tested positive on day 3 for example. Testing positive on day 3 would still lead one to believe they had contracted covid prior to admission and covid illness could be contributing factor to their admission or even the primary reason. It seems more that the article wants to give the impression that the 13% entirely is comprised of post-admission covid positive being retroactively recategorized as covid admission. That may be true for some portion of the 13% but we have no way to know from this reporting. It's ironic that an article criticizing categorization/attribution being overly broad to do exactly that with the minority percentage that it hangs the entire thrust of its point upon.

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