UKH

54 days ago a poster started this thread [1], one of several where they have presented non-reviewed opinion pieces or oddball pre-prints as factual research.  They then framed it as evidence for an intelligent discussion about the merits of releasing lockdown to "save the economy".  As has happened several times, the work is first introduced in relative isolation and then the idea of "OMG we are killing the economy and not saving lives but actually killing people through lockdown" is gradually woven in to the discussion in a way that presents it as a rational, evidenced view point building on the link.

Well, the premise that poster pushed in that thread and in several others, namely that research showed that the infection had been asymptomatically widespread and that we were therefore largely immune and locking down for no reason has now been shown beyond all doubt to be totally wrong with an ONS report showing 7% of the population having previously been infected [2]; just imagine how much smaller that was when the thread was started 54 days ago.  It's potentially even more wrong than that with strong hints that asymptomatic infections don't grant much antibody based immunity.

I hope the OP from that thread takes this as a sobering lesson in the dangers of being carried away by "trash grade" research on a minority view that is being pushed by the alt-right.  Had they been in charge in the UK 54 days ago and relaxed lockdown significantly based on their evidence they could have been responsible for perhaps 50,000 to 100,000 more deaths to date, locked in before the scale of the mistake became apparent, as the virus tore a swath through an almost totally non-immune population.

This thread will be open for a couple of weeks if the OP wants to admit they were wrong.

[1] https://www.ukhillwalking.com/forums/off_belay/new_chinese_data_on_asymptomati...

[2] https://www.bbc.co.uk/news/health-52837593

People are allowed to have a different opinion and I feel such vengeance and public shaming in a free society is worrying.  The science on benefits of lockdown and actually death rates etc with cornavirus seems far from clear cut, with lots of distinguished scientist from top universities coming out against the current situation, surely the benefit of a free society is the ability to debate ideas and not shame other views that may be perceived as wrong.  All your post shows is a vengeance against someone you previously argued against and disagreed with which is rather poor, more humility would be shown in knowing you had maybe won a debate rather than shaming that person on a public forum.

They are.   Although you don't seem to like it that I do.

But when they introduce multiple highly questionable sources for their opinion and constantly refer to them as research and evidence (some threads now deleted), go to great lengths to paint the appearance of an intelligent debate around it, and insist throughout that they are taking an evidence based approach, I am going to call it out.  You can call it "vengeance and public shaming" - I call it education.  This is an anonymous forum.  I have offered copious feedback on the (lack of) quality of their sources before.  I am now closing the loop and evaluating some of that feedback against high quality evidence.  

Also, yes, it is a free society.

This has no relevance on the OP using deeply flawed and now demonstrably false evidence in support of that position.  Had they or you produced high quality evidence it would be a different matter.  

There is no "perception" in the wrongness of what I am calling out from the OP.  Their premise of widespread herd immunity was minority opinion at the time, and is now factually wrong, not perceptually wrong.  I am calling that out.

"Vengeance: punishment inflicted or retribution exacted for an injury or wrong."  

Is pointing out that someone else's premise was factually wrong "punishment" or "retribution"?

I'm sorry but I disagree fundamentally.  When people argue a dangerously risky position primarily off the basis of trash grade work that they present and treat as high quality scientific evidence I am absolutely going to continue calling it out.  Feel free to call it shaming or lack of humility.   In other - now deleted - threads the pattern continued with no sign of recognising the ever weaker basis of their position.  So now I have presented some rock solid data that they were building a house of cards.

As for humility in knowing I have won the debate; I don’t care to win the debate, I care that the OP is going round pushing a very unevidenced view whilst claiming to be guided by science, and has a dossier of what to the non-scientist looks like highly credible academic research to support it.  I doubt this is the only place they’re popping up occasionally to have intelligently framed debate around what is actually trash grade research.  I would sooner loose the debate (which counts for nothing) and put some stark facts in front of the OP to help them improve their relationship with academic research in their future conversations here and elsewhere.

I had a long think about this - do I send my thoughts by private message to the OP or do I put it on the forum?  I chose to put my words here.

The point about peer-reviewed research is that if they do, then they'd better have some bloody good evidence of at least equal quality to support their opinion. Otherwise, they're just another idiot blathering on.

T.

Isn't there a forum called 'pompous self righteous bores'? You'd fit in nicely there😀

Was it you who voted me resident windbag a few weeks ago?  Just living up to my award.  

That is maybe so, but the the problem just now is most research on cornavirus is pre published before peer review, so there is many papers on various views that haven't been peer reviewed, so what chance do normal non experts have,  they just have to read around as widely as they can and make up there own opinions as best they're can.  My own views are constantly changing as the evidence changes.  My personal view is the virus is in remission due to seasonality effect of European spring/summer weather, and no second wave will happen until the autumn, off course my view is highly contentious and I will rightly get slaughtered on forums like this for it, but at least I am reviewing the evidence and making my own mind up instead of going with current consensus, so I don't really care if I am wrong at least I have the guts to put my opinion against popular norm.

Have a like for a good humoured riposte!

7% of their sample. How big was that sample? About 800. Is this statistically significant for a population of 70 million? Probably not. 

It depends how random the sample was.  I’m giving the ONS the benefit of the doubt here given who they are.  Close to 900 people isn’t a bad sample size with decent random sampling.  It doesn’t put high confidence on the 7% but it demolishes claims of ~50% with very high confidence.  As do previous studies.  

But you're presenting this as the antithesis of unsubstantiated claims. Surely there is no 'benefit of the doubt'. You will have read the whole study and determined that their methodology was sound? No? 

We had all better hope that something has gone wrong with the stats.  If 7% or so is the real number, the next wave after the "thank God that's over" thing that we are currently experiencing is going to be as demoralising as the events leading up to Dunkirk.

Furthermore, if the UK is any sort of model for the USA there will be insurmountable social problems emerging over there.

No.  Something the ONS publish will have been rigorously controlled and reviewed by people quite capable of doing that.  I skimmed the text and decided that it wasn’t worth the time to do more, no red flags caught my eye and everything was as one would expect.  Most scientists most of the time don’t check every part of every paper they read and reference, or nothing would ever get done.   This is evidence based, statistically controlled data from a reputable source.  Having skimmed it it my professional opinion was that there is no need to dig further - lazy to call it the benefit of the doubt but it’s the same thing.  Where as the OP’s article - to the untrained eye resembling a peer reviewed article in the BMJ but actually a letter from a retired GP if I recall correctly (I may not) raised a lot of red flags to me so did not earn my professional trust or the benefit of the doubt.  

You might still call me out on not digging in to every detail of their study but most details are never published - the protocols for the lab procedures, the service and calibration data on the testing equipments, the QC process on test kits, 101 things that affect the accuracy of the data are never published, although there may be eg ISO processes associated with the lab.

Its a decision I am happy with.  Others may disagree!  If they can point out a signficant flaw in the ONS methodology I’m happy to be proved wrong.

Did you see last week that Sunetra Gupta from the Oxford team was being championed by Karol Sikora,  with regard to her claim that the Covid death rate could be as low as 0.01%, when somewhere between 0.55 and 0.9% of the population had already been killed by it.

I’d have though it’s closer to 0.1% (50k/66m)?  This still demolishes a claim of 0.01% beyond any reasonable doubt unless there’s another pandemic in progress we haven’t noticed...  0.9% is more where we end up if extrapolate to the whole population.

I didn’t see it but I have seen other cases of “respected academics” coming out with absolute horse shit.  I’ll go depress myself with google now.  I do have a lot of sympathy for people from outside of science trying to negotiate all the competing views put forwards, but this doesn’t extend to people cherry picking from those views.

I’m hopeful.  Testing is getting faster and more widespread.  Clinical care is much improved with lessons learnt and an anti viral drug now approved.  Workplaces are taking many steps to reduce transmission.  Many people are still taking big personal steps to reduce transmission.  If it flares up again I hope it will do so more slowly and with a state and population much more on the ball about responding to it.  Test and trace is coming.  Each of these are relatively minor in isolation but taken together let’s hope it’s enough...

It's late, I'm muddling my numbers nearly as much as Professor Gupta. 0.055 and 0.09.

My very basic stats  ESTIMATE suggests that is 7% plus or minus 2% for 95% confidence and 885 sample size.

7% of 885 is 62. Statistical fluctuations or sigma is square root - 8 ish or 1% of sample. So 5% to 9% for 95% confidence (two sigma).

That looks statistically significant.

What do you work out for statistical uncertainty or confidence levels?

Looks like estimate about same as proper ONS stats, see below.

https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/con...

Around 6.78% of people who provided blood samples tested positive for antibodies to COVID-19

As of 24 May 2020, 6.78% (95% confidence interval: 5.21% to 8.64%) of individuals from whom blood samples were taken tested positive for antibodies to the coronavirus (COVID-19). This is based on blood test results from 885 individuals since the start of the study on 26 April 2020.

Still an order of magnitude more then is needed to demolish claims of fatality rate << 0.1%.  Her higher end claims of 0.1% also look quite unlikely now.  Having done some catching up on the news I’m now more fed up than ever with epidemiologists-turned-modellers.  We should be led by medical evidence and good old fashioned epidemiology, not models rooted in assumptions and simplifications.  I say this as someone who spends a lot of time making Monte Carlo models of biological processes.

Exactly my point.

Sorry yes didn’t actually say - totally agree.  I’d love to know more about what’s going on behind the scenes here.

Isn’t uneven distribution a major problem?  Pollsters work on those numbers, but they weight them and that massively changes the result.

Resident know-all? Engines, moths, politics, rivets on old planes, gravitational forces, the housing market, on which side of a U. S. fighter jet is the camera mounted... Are you UKc's Ozymandias or just good with a search engine? 

That's the sort of question you answer in further surveys that look at sub-groups.

And you’re confident the only way immunity is conferred is by a humoral response? Care to elaborate on other possible mechanisms?

The cognative dissonance is strong with this one. 

I'm sure you're right. The point was more aimed at the initial diatribe against unsubstantiated claims which the poster then when on to dismiss using something they hadn't read. 

I believe you spotted me out in a mistake recently!

First helped rebuild a V8 when I was about 5.  Mainly cleaning parts and helping with the hoist.  I’ve had things with engines in of one sort or another for about 20 years.  They’re very interesting.

I don’t recall ever taking about moths.  I know very little about them.

Lifelong aviation fan.  Days spent at duxford, visits to aircraft museums wherever I go, regular family lunches at the local airstrip cafe so little one can watch the planes.  One of the downsides of having given up flying is that my tick list of Major US aviation museums is incomplete.

Professional interest

Doesn’t everyone spend ages starting at Rightmove and thinking about this?  Beyond that it’s opinion and local knowledge.

I have spent time professionally on a USAF base working with optics people.  As an intersection of personal and professional interests I have a long standing interest in air and space borne instrumentation.   

No, hence qualifying that sentence with “potentially” and qualifying it to antibody mediated response.

Well outside my expertise.  I believe there are more innate immune responses and some that key to double stranded viral RNA, with some of the vaccines under development targeting each of these, and with a recent study of people who suffer severe responses showing the former to be a key factor.  I’ve not seen reports that asymptomatic infection can boost these without producing antibodies but I could be missing something.

The problem here is you are drawing hard conclusions on still incomplete evidence. In fact you point out one of these yourself, namely that there is a suspicion (but not proven) that asymptomatic infections don't grant much antibody based immunity, hence these would not be included in the 7% figure. The root causes of why the virus is so harmful to some people but not others is still not understood by the science community. 

The problem with your statement that 50k to 100k more people *would* have died, is that this eventuality has not necessarily been born out in other countries, some of whom have either had a soft lockdown or none at all. Looking locally in the UK if lockdown was the primary driver, then why is London (that locked down later relative to its localised outbreak) now in a better position that the rest of the UK? Again the reasons for this are still not understood.

I am not disagreeing with what you say, just that the picture is still not clear enough for you to be so sure that what you are saying is correct.

You are right that there are a great many unknowns - at that is a solid reason to err on the side of caution based in epidemiological experience from past pandemics and guided by hospital admissions now, not speculative theories with minority support and build on very dubious evidence. 

That has been changing rapidly in the last few weeks.  

I said *could* have died, not *would*.   It seems likely but thankfully we don't know. I'm not aware of evidence for any country where infection was growing exponentially and then just sort of petered out all by itself without any lockdown or social distancing etc.  

Sweden is often used as a comparison but their lack of lockdown has not been so dissimilar to the UK's soft lockdown in practice or in results to date.  There are big differences between places, but there is also solid evidence that a proper swift, hard lockdown can hammer the virus.  For any particular country, the key principle to me is that whatever is working for any country shouldn't just the thrown away on a whim and garbage level evidence, but progressively relaxed driven by medical evidence.

You could be right, but the number of studies with different methodologies (anti-body testing, live infection testing, epidemiological analysis) that have emerged in the last two months make it almost inconceivable that we were anywhere near 50% infected/recovered 2 months ago.   That was a demonstrably false premise with what was know then and is now clearly more so.   Regardless of the merits of releasing lockdown 55 days ago it is ever more clear that the evidence presented for doing this was not sound.  

You might look at the most recent situation report Figure 22 - https://www.gov.uk/government/publications/national-covid-19-surveillance-r... - and revisit in a week?  But yes; many different factors are involved in the response.

Sorry, I don't understand this: 'Regardless of the merits of releasing lockdown 55 days ago'?

I mean that the quality of the evidence then presented on "widespread herd immunuty" was and remains weak, and that this criticism of the evidence is not affected by discussions over the merits or problems of releasing lockdown that had been hung off the evidence.  I hope that's clearer. 

You said that this figure is correct with 95% confidence.  I think I’m right in saying that confidence is only true presuming an even distribution in the population, and if so that’s a pretty misleading claim given we do not have that distribution, even if it is correct in stats terms.  Not a statistician though, hence why I’m asking...

I would be interested if you have any links on this? To me the lockdown is a sledgehammer to crack a nut type of policy, we know it is effective to a degree, but it is also essentially a policy born out of failure to understand what targeted action is required.

My own personal view is we need to be patient, it was a disease that the science community were clueless about a few short months ago, but over time we will understand better the chains of transmission, who is vulnerable, treatments that are effective and ultimately possibly a vaccine. 

I cant imagine the test subjects include those already with a positive test and those that are dead. as with any survey, the cohort are self selecting to a certain degree.

Specifically in that link:

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/...

Page 17.  London.  Not too sure you need to wait a week.

Incidentally, does anyone know any source of data for the number of people who are seriously injured by the virus, but not killed?

Do you have any evidence of a mistake in the study?

The sample design would have to be massively wrong (>2 parts in 7) to produce a systematic error comparable to the random uncertainty (7% +- 2 %).

The sample design could be wrong. However, unless they do the study in the staff car park of a hospital to get a preponderance of highly exposed health workers it's not very plausible the sampling is massively unrepresentative.

Not impossible, but not very plausible.

Imperfect data is not misleading data when it is so obvious that 885 people are not the entire population of the UK. 

PS I'm not a statistician

It obviously very plausible the sampling could be massively unrepresentative- without knowing who and how they sampled we cannot know.  Demographic? Geographic spread? you could get a great geo spread but only target healthy 40 year olds that respond to a facebook ad.  equally you could get a great cross section of society, but only from bumfunk village, nowhere that is representative of the country.  BAME people are historically neglected (in everything) when surveys happen, but they are the most affected by this.

my gut would also say that people alrady affected by Covid are alot less likely to want to be subjected to more testing, and so might self select against repsonding. The converse could be true. 

anyway- the point was, the poster was attacking unsubstantiated claims, or rather claims with poor evidence, and then used a small scale preliminary survey without review as gospel.

No, questioning it’s meaning.

Im finding it hard to guess how you design the sample.  We’ve got varying rates by location and job for sure.  Age?  Seems logical that makes a difference.  What else?

Or you exclude those known to be infected and deceased, as la benya said, which will shift the figures the other way.

Of course it’s obvious, but we’re used to polls which on similar numbers quote the same confidence figures and are generally pretty close to reality.  It sounds like you’re saying there’s a 95% likelihood those figures represent reality.

Fair enough.

There are other serology surveys out there and there is good agreement.  I could have produced a more researched meta study for my OP but that seemed disproportionate.  I didn’t claim it as gospel but if you factor 7% now back in time by 55 days and compare it to claims of around 50% it might as well be in terms of confidence for demolishing such claims...

I’ll dig one out later - in a rush now.

I totally agree, but sometimes it’s important to crack a but first then worry about finesse.

Exactly and that sledgehammer bought us the time to do that.

How plausible is it that the ONS would commission a survey based on a facebook ad or the inhabitants of little bumfunk? 

To me it is extremely strange that there is a reluctance to accept a sample of 885 people as evidence when the maths to support 7%+-2% with a 95% confidence is almost 200 years old.

Very plausible-  how would they contact these people?  do you think those in poor areas or minorities respond to these requests in the same numbers as the middle classes?  Blind faith because 'its the government' is mental... especially after recent events.

That confidence is nothing without the supporting information regarding their sampling method.

If DMM sampled to the same standards, but only on the first run of their carabiners and no the subsequent 10, would you be happy as long as they hit the magic number to achieve the numbers you quote?

I often think its more important to bust my nut without any finesse, but my wife doesn't always appreciate that approach.

Read the ONS report to find out. I haven't but I do assume they can deal with the basics you describe as they have a pretty good reputation.

Definitely happy with DMM as the do test a sample from each batch and use the same maths I used for 2 -sigma to achieve their magic number (3-sigma). What else should they do given they cannot test something to destruction before they sell it?

https://dmmclimbing.com/About/Quality

"3-Sigma Testing

This is our system for setting and monitoring the strength ratings as marked on our products, in line with the minimum requirements of the relevant European and other Standards, the ‘3 Sigma Testing’ method. DMM were the first company in our industry to use this Statistical Quality Control [SQC] technique. Using test data derived from samples tested to destruction at the design stage we can set the strength rating of the product. We then have a system of ongoing batch testing which monitors and ensures that the rated strength is maintained and actually exceeded.

Part of our philosophy at DMM is to continue to improve the breaking strength of our products in excess of the standards which may be required. We do this to lessen the chance of failure in situations and conditions which might not be reflected in the standard but which we know as climbers ourselves can cause product failure."

To quote the report

'A number of serological collections have been established by PHE to provide an age-stratified geographically representative sample across England over time'

Also - if you read through it, there are about 5 other methods of tracking prevalence of COVID19 in the population (such as hospital admissions, rates of infuenza-like symptoms reported at doctors surgeries, queries to NHS111 about COVID symptoms) All of these have their own weaknesses and biases - however when they are consistent with one another this is good evidence that the individual methods don't suffer from any significant bias.

Both points completely missed... intentionally?

I chose DMM as I know how good their testing is.  But that is all useless if their sample is from one batch and they ignore the other 9.  I'm not saying they do that, but I was using the analogy to compare to the topic at hand. Apologies if that was not clear.

T cell response 

- https://www.crick.ac.uk/news/2020-05-22_blood-test-could-track-immune-respo...

- https://www.immunophenotype.org/wp-content/uploads/2020/05/COVID-IP_220520-...

Some media reports have suggested low T-cell count before infection could be the risk factor but their data is based on hospital admissions, but it is still taken before the progress worsens and so offers both the possibility of targeted interventions and direction in studies to identify upstream risk factors.

So other batches (countries) should test too? I would agree with that.

I agree with you, the sample size is far too small to be taken too serious despite the obvious creditable nature of the source.

I was shoot down on a previous thread when i presented surology data from a study on a small town in Germany that has a large out break.  They tested close to 1000 for antibodies, out of a town of maybe 10000 people and found out that 15 percent of the population of that town had covid antibodies and that gave a Infection fatality rate for that town of about 0.3 percent, such information was dismissed on here at the time, but i would believe a large study of a small town to give more accurate information than a small study in UK.  I am not saying the fatality rate found in Germany will be same as UK due to demographics but it provides good indicator of how fatal the virus is.  Large scale studies in new York state give a fatality rate of around 0.65 percent.  Looking at both studies that sampled a bigger proportion of the population i would hazard a guess that the fatality rate for UK would be between around 0.3 and 0.7 percent, and my best guess for proportion of UK that have been infected will be between 10 and 15 percent.  I welcome all the negative comments that will follow.

It depends what you’re using it for - the results are highly incompatible with a theory of significant herd immunity 55 days ago. That’s what I was using it for.  Even with a small sample size the results are highly incompatible with a theory of 50% herd immunity now, let alone ages ago which is my original point.  I agree that the confidence interval on the 7% is only meaningful on the sample being drawn or controlled in an appropriate way.  The probability I am using this for in my OP is that the 7% is a noise biased measure of a true value of 50%, and that probability is so vanishingly small that i challenge anyone to produce a sample bias that delivers this.  It’s a few more than the six sigma another poster keeps mentioning...

None of those seem unreasonable.  The weekly serology data on blood donations makes it clear that measured rates vary geographically across the UK and that range is similar to various studies.

Again I don't see why people are disputing maths that has been around for approaching two centuries. However low our opinion of mathematicians, they are not THAT thick.

15% of 10000 is 1500 infected, 0.3% fatalities of 1500 is 4.5 deaths. Sigma about square root (2), 95% certainty two sigma (4). Starting to get into the range where Guassian less good approximation for Poisson.

Hence fatality rate is 0.3%+-0.3% (about 0.0 to 0.6% with 95% certainty). So yes, that is a big enough study for level of infection (15%+-1.5%, 95% certainty) but a small study for fatalities 0.3%+-0.3% with same 95% certainty. 

Curious that a sample size of 885 is "far too small" but a sample size TWO HUNDRED times smaller of 4 or 5 fatalities is not.

Edit: line above not a fair comparison

Curious that a 60 infected within 885 people surveyed is "far too small" but a sample size TWELVE-FIFTEEN times smaller of 4 or 5 fatalities in 1500 people infected is not.

If memory serves (I can’t find the thread), these fatalities came before all cases yet symptomatic and in hospital had run their course.  I could recall wrong - apologies if so. 

Here is a simulation of why a sample size of 885 is sufficient to detect a something at a level of 7% with an about 95% certainty that the result will be in the 5% to 9% expected range (my numbers, you can modify with the slightly different ONS numbers if you wish).

https://jsfiddle.net/de3tj1yc/

It's a web page, no install on your computer and jsfiddle is widely used by geeks to share code snippets.

Press the Run button, see the 1000 simulations of 7% infection in a sample of 885.
Observe how few results are outside the expected range of 5% to 9%.
Scroll down to see how many of the 1000 surveys were in the 95% uncertainty limits for 5% to 9% infections. 

It all points to a sample size of 885 being very adequate at least 95% of the time.

I can't remember the exact population of the town surveyed, but was guessing it was around 10000 as i cant be bothered looking for the data again as it was widely published at the time.   My own thoughts on why the fatality rate was so low in Germany is probably because of few or no deaths in care homes compared to large number of care home  deaths in new York l, which suggest our fatality rate will be similar to that found in new York.

I still don't think blood donation surveying is all that accurate for population as whole as the demographics of people giving blood is not representative of society as a whole, i think it acts as a guide in level of infection in society but further evidence when it comes might well suggest it was a under representation.

Households were selected and invited to join the survey. It is a blood test but the participants are not blood donors, or no more so than average.

https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/con...

There is a different weekly survey which is done on blood donors.

https://www.gov.uk/government/publications/national-covid-19-surveillance-r...

Thanks for clarifying that for me.

I saw Gupta say that on an alternator news Chanel in the last week  (0.01% to 0.1% IFR). I’m surprised an expert from oxford uni can’t do the maths and work out that that already around 0.05% ish of the uk population have died of this so we aren’t going to see anything Like 0.01% IFR.

The better stats to use are New York State and the Spanish antibody surveys (with 70000 random tests in the Spanish one) They are both pointing to an IFR around 1%. I did the maths on the NYS stats and it came out around 0.8% IFR at the time, interesting only 11 percent if Madrid were thought to have had C 19 and IIRC around 13% of NYS. Jersey did some random antibody tests too that I worked out to point towards and IFR around 0.5 -1%.

youtube.com/watch?v=BKsVd4M1pK8& https://www.gov.je/News/2020/Pages/Antibody-survey-report-published.aspx  youtube.com/watch?v=ypsUIh41xUw&

There has been an ability to work this backwards for some time... just divide deaths by the mortality rates assuming a conservative low number (like 0.5%). ONS have over 40,000 C19 deaths so that's a maximum of a bit over 8 million infections (~13%). I'd expect the percentage who have had it to be lower as the mortality rate in care homes would be much bigger than 0.5%. We probably have about 20,000 deaths from C19 now in care homes so the experimental estimate of 7% from the research sounds about right to me.

If a wintertree fan club is formed I will certainly join. He is my UKC hero of the year and I would happily buy him alcohol all night once the pubs open; to celebrate his work here sense checking the idiots who made ridiculous claims. If the infections grow again (and the pubs don't open), in a lull we can be sad socialy distanced people with brown paper bags in a park.

Some of those threads were standard alt right propaganda... especially the new poster with their first ever UKC post proving lockdown wasn't needed.

It's really tiresome to see mainstream science so often having to argue on a level playing field with climate science denial, anti vaxer's, conspiracy theorists, and the 'every one has had C19 so lockdown was a waste of time' brigade. It's good to see social media companies clamping down on the biggest idiots (Trump top of the list given his influence).

C19 deaths per million in NY are over 1,500 so if nearly everyone had it there (very unlikely) the minimum mortality rate is 0.15%

Why is wanting lockdown to end considered right wing? 

Freedom vs state control.

I  would hope most people want lockdown to end. The question is it it sensible based on the science. If you open too early and the population behave badly the virus kicks off again and we are back to square one on lockdown.

The alt right are probably not the only people who make shit up to try and influence political decisions to open US states where the rate of infection is still increasing. Their particular style is so well shared it is just easier to spot. You can certainly add people who put religious faith above science in trying to get their churches open again.

It's not right wing in and of itself, but it's very popular with libertarian neo cons who subscribe to the "devil take the hindmost" type of view. Also the guys who fund all that frothing brew of pestilence are suffering because us drones aren't buying their useless crap.

Exactly. However, without the state interference in freedoms hundreds of thousands would have died in the UK and millions in the US.

We agree on that too.  I don’t really know why things have to be looked at in that way though, why everything must be left/right.  IIRC Alicia was posting most and she’s a long term poster not noticibly right wing who just disagrees in this case that the strong lockdown is necessary.  La benya too.  That doesn’t make them alt right, it doesn’t make their POV therefore wrong.  The wish to get back to normality is universal, as you say, that it’s shared by anti vaxxers should be irrelevant.

Right... Which word best describes those that would eb against state control... Conservative or LIBERAL 

Exactly. It's not just the right. 

It's not helpful to continuously distill every subject to a right vs left situation. It breeds a them and us mentality where people become entrenched in their views based on what side they think they should be on rather than what the situation merits. 

My point was its not right or left to have a different opinion on whether the measures used to contain the virus and save a certain subset of people is appropriate when contrasted against the other subset of people who are being sacrificed to achieve this. It does no one favours to pigeon hole people and entrench them and yourself to a camp. It stifled active discussion. 

As an aside--the 'science' might say that if we all give ourselves over to the machine overloads and live in goo pods we will live 5 years longer without and chance of injury or illness. Does it make me a far right extremist to say no thanks to that? 

“While the pilot is based on a nationally representative survey sample, some individuals in the original ONS survey samples will have dropped out, while others will not have responded to the pilot. To address this, we apply weighting to ensure the responding sample is representative of the population in terms of age (grouped), sex, region, housing tenure and household size.“

Some potential bias since the sample was households in which someone had previously been part of an ONS study and agreed to be contacted again. So if a particular type of person was more likely to agree to future contact, and that characteristic was relevant to covid risk, that might be an issue. Equally if the previous, larger scale, studies had fundamental sampling issues then that would be problematic for this one. On balance though, having just skimmed through their sampling write up, it seems like they’ve given due consideration to confounds and potential biases

Thats BS. If someone is distributing memes identical to those from the alt right that doesn't mean they have the same politics but they do deserve to get called out on it. If the science behind their claims are provably wrong that's not a viable alternative opinion it's wrong.

It’s not just that but a lot of these people are simply sharing populist memes to get their page shares up. Sharing something that you believe in is one thing, but be wary that you are often also sharing the page of the originator.

Nobody has said that it is.  Almost everyone across the political and non-political spectrum wants to end lockdown.  

However, many of the "grassroots" anti-lockdown or "let it rip" protests in the USA were traced back to the alt-right, and anti-lockdown movement in New Zealand turned out to be an effort orchestrated by the alt-right.  At the same time, a series of posters on UKC raised similarly worded anti-lockdown sentiments here all using very similar messaging and abuse of trash grade science.  It was a mix of new and existing posters, and several threads were rapidly pulled (not at my request).  

There is always a political and social debate to be had about the different costs of locking down vs not locking down, and that discussion can be had freely at any time - and has been to a high standard on UKC several times.  Afraid I'm going to continue being a windbag when people try and build such a debate around trash grade "science".

As another poster remarked up thread that it's a difficult time for non-scientists to keep abreast of what's happening, with a lot of the data being written up on pre-print servers.  Here are some tips for following these.  (Another poster told me I needed to speak to an expert in education if I was to understand why pre-prints were being used so much.  I didn't see the benefit of replying to them in detail but it might be useful for others, or it might add to my windbag status) :

• If it's a pre-print, is it genuinely pre-publication, or is it being put on the pre-print server by someone with an agenda to lend its content credibility with non-scientists and with no intent to publish it?  You have to decide on this - some things to look for - is it from an established research group in a relevant field or is it a sole-author paper carping on from an unrelated discipline?  Through an investigation I did (unrelated to covid or the alt-right) I am aware of an orchestrated effort to build a false impression of scientific credibility using pre-prints hosted in various places including in "Nature Precedings" which was a way of giving something a nature.com URL and a DOI without any peer review.  There are experts out there at creating a false impression of scientific credibility for political/fraudulent purposes.  
• Is the content impartial?  Are there emotionally loaded words or connotations in the introduction?  Does the narrative tension the subject material of the paper against wider issues or does it just seek to provide those whose job is to make the trade offs with the best presentation of the best data they can get?
• Do the headline claims in the document stand up to basic "fag packet" maths scrutiny - an example being the IFR recently given by an academic that doesn't stand up to the current (let alone eventual) death rate in the UK.
• Remember that game playing is a pathway for junior academics to get to be senior academics.  It's not the only pathway but people who are experts at sussing out systems and working them can certainly thrive on those abilities over others.  
• Many people have their views and their political leanings, and it can be difficult to fully decouple them subconsciously - which is one good reason to treat sole author pre-prints or papers with some skepticism.  Another is that this isn't Knight Rider, one person can't make much of a difference; high quality data gathering and analysis takes a team which also guards against bias seeping through. 
• It's a fast moving situation and there are still many unknowns - which makes really controlling for all factors very difficult, so individual studies are definitely wary of some skepticism without corroborating studies; I linked to one in this thread but I did so having seen many others that all also demolished the "widespread infection 2 months ago" theory.  Look for different studies from different groups that have concordance.
• Make a list of what you read with notes; making such an aide-memoir helps lock things in your brain making you more effective, and helps you keep track rather than bouncing from one source to another.

Thats an entirely separate matter, you don’t need to smear people to discuss that.

One of the many ways that the left/right split is rather unhelpful...  Old school (freedom pro) liberal = libertarian though, so it’s right wing if you like to box things.