Headline begs the question - what the hell did we think we were doing between August and November?
Wasn’t R<1 the magic number for ending the first lockdown?
FWIW I’ve always been suspicious of the way R is used by the government and media. It’s always going to be a best guess averaged over an area, but with asymptomatic transmission and initially poor access to testing, seems like it should be treated with caution. Not dismissed, but not the main driver, I guess.
The R number is in essence the driver of this pandemic. But like you say the published figure is at best a conservative estimate and at worst an educated guess. Imo the way it’s reduced down into this singular all-explaining number belittles the sheer scale of variables and complexities going on in the real world. But hey, explaining that would be too much like hard work for many tabloid outlets.
I have found it consistently disappointing that the BBC has been putting out UK government statistics and interpretations uncritically - as we see (for example) in the headline here.
The More or Less podcast, also from the BBC, does a good job of digging into what the stats actually mean and whether they're correct or misleading.
Their main beef over the pandemic has been when ministers and the government have been lying fairly explicitly about testing targets (counting posted tests as completed tests).
I find BBC as a whole hasn't been as critical, but they certainly seem to be at least making an effort to explain and contextualise. They aren't parroting government statistics as much as they could be doing.
It's the number to eventually end the largest restrictions but keeping it low was always going to require either continued light lockdown or a large monitoring project to catch and quarantine random popup cases like China is doing. Just recently in the US I've only had two places doing temperature checks which is wild to me at this point, it was the local courthouse and a random artists collective store I was visiting.
Wall-to-wall testing would be my preferred route. In fairness I think that would be gov.uk's preferred route too if they could organise it (they can't).
I got temperature check and covid symptom questionnaire on entry to (private) hospital, but it's not widespread.
> Just recently in the US I've only had two places doing temperature checks which is wild to me at this point
I've gotten a temperature check every time I've entered a commercial building for the last few months (in NYC), but temperature checks hew dangerously close to safety theater.
It's a small thing that can catch some low symptom cases in the absence of randomized testing. It's not the most effective thing but I don't think it's theater.
Temperature checks won't catch asymptomatic people, and a lot of covid cases are asymptomatic. I don't see how temperature checks ought to make anyone feel safer.
Yeah, the false positive and false negative rates are utterly atrocious - there's so many things that can cause raised body temperatures, a lot of people with Covid don't actually have fevers, and the thermometers used often aren't that accurate anyway.
The problem is that the US media have quite consistently only reported on the fact that they're useless when talking about them being implemented in the US. When China and the WHO claimed they were the basis for China's success in containing the virus, pretty much everyone - including publications like the New York Times - uncritically regurgitated that claim. Same with places like (if I remember rightly) Taiwan using it for airport screening. Anyone who got their beliefs from the mainstream media would be left convinced that America was failing because it hadn't adopted these successful measures from places like China.
what the hell did we think we were doing between August and November?
Starting the new school year, for one thing. For many of us that was critical to letting us keep working (and mass home-schooling and online teaching for young kids was not working).
Fair point, and you're right something had to give on that score. Classroom pods for young kids seem to work fairly well overall, it just ups the risk for visiting the grandparents.
The university side didn't seem to work out as well - possibly partly because uni staff are (understandably) less willing to work crunch hours to meet duty of care than primary school staff.
I think it's quite simple, there is good evidence that younger children (U14s) get covid less than adults, and spread it less when they do have it. So schools - especially primary schools are not the issue.
Reopening universities was - students do get it, and they all live together in shared accommodation so as soon as one got it lots of them did.
During the summer, when they talked about opening schools and claimed that young children weren’t major vectors for the virus, I was very skeptical and assumed it was mostly just an excuse -- but it does actually seem to have worked out! If primary school children were spreading the virus en masse, the current spike would be vastly bigger.
(It’s very unfortunate in the US that school opening has been so strongly politicized.)
Opening the universities is another matter entirely. That definitely shouldn’t have been done. I was going to say “in hindsight” but in fact that was pretty obvious right away.
Researchers suspect that one reason schools have not become COVID-19 hot spots is that children — especially those under the age of 12–14 — are less susceptible to infection than adults, according to a meta-analysis4 of prevalence studies. And once they are infected, young children, including those aged 0–5 years, are less likely to pass the virus on to others, says Haas. In an analysis5 of German schools, Haas’s team found that infections were less common in children aged 6–10 years than in older children and adults working at the schools. “The potential to transmit increases” with age, and adolescents are just as likely to transmit the virus as adults, he says. Teenagers and teachers should be the focus of mitigation measures, such as wearing masks or a return to online lessons when community transmission is high, says Haas."
> Starting the new school year, for one thing. For many of us that was critical to letting us keep working
Is this not why the situation persists? Lockdown hard then go back to pretty-much-normal seems vastly preferable. I say this from NZ.
The hit has been hard, but it seems that partial lockdowns and half measures actually lead to worse outcomes. The death toll is certainly on another scale when you don’t lock down.
NZ peaked at 150 cases/day, the UK didn’t start its first lockdown till 5000 cases/day. And that’s 5000 tested cases.
It was too late (even though Italy was bad and a good canary, UK politicians did nothing). Even if the country remains in permanent lockdown the virus will still spread now for months/years.
At massive economic cost. It has only been bearable due to the other states remaining open and proping up the Victorian economy via Federal Government payments.
Just at the state level debt is expected to more than triple by FY23/24 to $155b.
Ongoing semi-lockdowns, presumably until the majority of the population can be vaccinated, plus the affect of the infection on individuals along with their medical costs and absence from work has a cost too.
Money is just a means to an ends. It acts as a means of exchange, unit of account, and store of value.
What we really want are goods and services to consume. If people aren't going to work and producing goods and providing services then there will be less to go around making us all poorer.
Locking down does have a large economic cost, but the alternative is a large number of preventable deaths. I know which course of action I prefer to be taken.
Lockdowns are expensive when you do them late. The point is to do them as early as possible or better do proper contact tracing, mask usage, travel restrictions early. E.g. Taiwan put on full travel restrictions super fast and now operate like a normal country with minimal economic damage. Dragging your feet on COVID19 is what gets expensive.
I don't think the NZ strategy was ever viable for Europe and the US. They have very integrated economies that rely on massive amounts of travel and freight movement, at the same time they have very fractured political systems.
I mentioned this in a comment above but the U.K. and New Zealand are on Different scales when it comes internationalism. The U.K. ranks 4th worldwide for international travellers per capita, and New Zealand 38th. Looking at the numbers for international trade as a percentage of GDP, NZ quite below the global average, whereas the UK way above it. NZ has the advantage of size and geography too. It’s largest city is 1/10th size of London and it’s overall far, far less densely populated - the UK has pop density of 279/km2 vs 19/km2 for NZ. So while what they have been able to achieve is admirable, if there was one country that should be able to do it, it was New Zealand. Tiny, wealthy and isolated. Expecting other countries to be able to do the same doesn’t make sense.
Have you a source on your travel statistic? I’d been trying to find something like that but the sources have been terrible. In isolation I’m not sure of the relevance of the comparison between NZ and UK regarding travel frequency. New Zealand’s largest economic sector was tourism.
Pretty much every tourist flew in, and tourists are in close proximity to each other for 4+ hours. It doesn’t matter how often New Zealanders fly internationally if tourists come in infected. The UK has international flights that last a 15-20 minutes. This could give you covid for sure, but it may avoid infecting the whole plane.
A total of about 3.8 million tourists arrived in NZ in 2019, a number equivalent to about 75% of NZs population. The UK had about 38 million tourists in 2018 (most recent numbers available) and that equates to about 56% of the UKs population. NZ had a lot of tourists relative to its population.
Even now we are getting people fly in with covid every day, usually several cases and this is happening without there being international tourism anymore.
The UK doesn’t even require self isolation in all cases and having tried asking people to self isolate in NZ, we know exactly how it doesn’t work. Managed isolation is hard enough to get right.
Overall, what happened in NZ was impossible in the UK due to a lack of will, not anything else. NZ was willing to sacrifice it’s largest industry. How would you describe the approach used in the UK? It doesn’t appear to have a particular focus or goal.
The degree to which the UK is connected to the world is just on a different scale to New Zealand. That’s before you even consider the geography, population density, and wealth distribution sides of the argument. It was always going to be more difficult to control it in the UK. I don’t think lack of will is a valid excuse either. What country doesn’t want to get back to normal as quickly as possible? Why is it that only this tiny island in the Pacific has managed to do it? Is every single other country is simply that incompetent? It just doesn’t make sense. There has to be other factors involved.
If you order that list by ‘per capita’ NZ is way above the UK, 13th versus 24th. I think you have misread it and got the absolute number of travellers.
> The degree to which the UK is connected to the world is just on a different scale to New Zealand.
In absolute numbers, yes, per capita, no. With covid the thing that matters is people coming into contact. The ratio tourists/population matters. NZ has a lot of travel and relative to it’s population, a lot more than the UK. And NZs population travel a lot more.
> I don’t believe the tourism argument holds up in the slightest either.
How so? Tourists bring in covid.
If you look at things relative to the population, NZ has a lot of people moving a lot of the time.
NZ may be a small, far away islands (it’s bigger than the UK geographically), but the approach NZ used wasn’t invented here and is not novel. It was copied from others that had success. Interestingly, a lot of good policy came from South Korea. South Korea copied it from the NHS.
Others have had good results too, NZ is not alone at any stretch and did not pioneer it’s policies.
I’m sure there are other factors and many of them. However the UK leaders have not done well and have contributed hugely to the problems. The ignoring of advice from experts is incredible - why set up systems if you don’t want them? They continue to ignore the most basic advice and get exactly the outcome one would expect, covid.
You're right, I grabbed the absolute numbers by mistake. I'm not sure it dilutes the point as much as you are suggesting though. Absolute numbers do matter - as the difference is still huge (~10x). It a far harder problem to contain 10,000 infections than 1000 even in a country with resources because of the nature of exponential growth. Things are going to take off faster and more aggressively with a higher seed number, so even with proportionally the same resources, you have less time to react.
I actually never at any point said that I thought the UK was doing things well (I'm not from the UK). My point is that I don't think NZ's success was down especially to brilliant leadership so much as a combination of factors that make it a uniquely hard place for a disease like COVID to enter and spread.
In per capita terms yes, but in absolute terms not so much.
Trade in goods is also mostly via very long sea journeys which off course act as a sort of quarantine period. In terms of air travel Auckland is the only hub airport and the number of transit passengers is quite small.
I disagree. The UK’s economy is far more international than New Zealand’s. The U.K. ranks 4th worldwide for international travellers per capita, and New Zealand 38th. Shutting down air travel to the financial centre of the world would have been an incredibly risky move at the time. It may have been the right move in hindsight, but at the time it was far easier for the tiny island on the edge of the world to even consider doing it.
I don’t mean in march necessarily. But the UK never implemented testing at the border or isolation for travellers in any rigorous way.
They could have done this sometime over the summer. Going zero covid has huge economic benefits. And with testing you could let business travellers in with a modified isolation.
It was only worth doing in March. Because there were so few cases NZ got down to zero in about 5 weeks. Once the cases numbers build up the time and economic cost to get to zero is unfeasible.
> The U.K. ranks 4th worldwide for international travellers per capita, and New Zealand 38th.
If the below is the source, you’re citing an absolute, not per capita stat. NZ ranks significantly above the UK for travel per capita, and the UK population do not travel that much.
The UK is connected to continental Europe via the Channel Tunnel. We rely on an endless stream of trucks coming across from the continent and driving directly to destinations throughout the UK with their original drivers to supply us with important things like food, and they often then go on to do delivery trips within the country. (One of the big reasons that Brexit is supposed to be such a disaster is that it'll disrupt all this. With the scale at which this happens, even a small delay to each truck is apparently enough to cause massive disruption.)
Remember, this is a very good way of spreading Covid-19 to new areas - it's almost certainly how it got into Beijing, which was the best and most aggressively protected city in all of China at the time.
And yet the Chinese managed to control t. More people, higher density and little in the way of warning.
It’s one hell of a failure that the UK has had. Squandered preparation time and wasted opportunity with massive economic and health/death toll costs.
Elimination strategy works, and other strategies don't work. This isn't a novel insight, it's how infectious diseases programmes work regardless, Guinea worm: Elimination strategy. Rinderpest: Elimination strategy. Polio: Elimination strategy. Smallpox: Elimination strategy. It was never a question of whether it was "viable" except in the sense of whether political will existed to act. In the US and to a lesser extent Europe, that will did not exist.
The UK absolutely could have chosen to not have tens of thousands of people die for no purpose, but its political leadership were focused, as ever, on what's in it for them. How much can we exploit this to line our own pockets, how many old mates can be rewarded? Sure, people are dying, but isn't this a perfect chance to loot the corpses?
The UK could have started its first lockdown much earlier, and imposed quarantine on all arrivals. Then lifted the lockdown in areas with no spread, while keeping the quarantine. It's not like it was a mystery what was happening, once we'd seen what happened in Wuhan. China had the hardest job, dealing with a newly discovered infection, but has been among the least affected countries.
Half measures seem to have worked here in Madrid during the second wave.
There is a general curfew at midnight and health districts of the metropolitan area have been selectively locked down, but everything else has remained open: restaurants, gyms, non-essential businesses, etc.
Cases per 100k are not low but they have been declining for weeks now, with most of the city largely open for business.
Are you aware that "lock down hard" isn't possible? Do you expect food to still turn up in the shops, garbage to be collected, maintenance to be done on your utilities, online purchases to still work?
The death toll is on the scale of normal seasonal flu outbreaks when you subtract the deaths caused by lockdowns (i.e. that occur during lockdowns but that don't mention COVID on the death certificate). New Zealand is screwed by the way: good luck with international travel from now on.
I’m in NZ. Our level 4 lockdown was strict and only essential services kept running.
Can you provide a source showing covid is less deadly that the flu?
I can travel internationally from NZ and can get back in if I want to, but I don’t want to leave NZ. Why are we screwed? Everything is normal here now.
I didn't say it was less deadly than the flu. I said it's comparable to a normal seasonal flu outbreak if you subtract deaths caused by lockdowns. Please don't change people's arguments in the act of re-phrasing them.
Source: look at excess death data for most European countries. Even in the UK which had a significant wave of non-COVID excess deaths during the first wave (a little under half of them didn't mention COVID on the death certificate), excess deaths from it was similar to the winter of 1999/2000. And in countries that have less incompetent management the waves of deaths are similar to flu waves.
There are many, many sources you can get the data from. Try EuroMoMo, the national statistical agencies etc. But here's just one example, long term Swedish mortality data:
Remember Sweden didn't lock down. Modelling predicted a bloodbath which never happened.
As for NZ, what kind of business or tourist travellers will go to New Zealand now they have to be temporarily imprisoned at their own absurdly high expense? Adding a more than $3000 charge per person to arrival, plus lost time? Your island is currently a pariah state that people will avoid visiting unless absolutely necessary, indefinitely.
I assume at some point these rules will be dropped for those who can show an immunity passport because it's the only way New Zealand doesn't just drop off the face of the planet, but vaccines aren't 100% effective and even the vaccinated can still carry the virus: they just get milder symptoms. So it's not at all clear how New Zealand plans to ever open back up.
That's not unrealistic though, I don't envy anyone in the world having to balance the economy and their excess deaths - in the US especially economic downturns can directly translate to deaths and suffering of their own.
That is based on the premise that less restrictions are better for an economy. That isn't necessarily the case though. If people are scared to go out it doesn't matter if places are legally allowed to open or not. Also sustained moderate restrictions might be worse than a short term period of harsh restrictions. Better to bring cases down a low level, build consumer confidence, then use your R budget.
You can't work at getting a balance unless someone does a detailed cost/benefit analysis. I've seen no such thing. In Britain supposedly highly educated people in government and the civil service have been acting it seems, on whim and dodgy statistics which have been utterly refuted by respected independent academics. I suspect that many thinking people in the UK would concur with the view that sections of their government would be hard put to it to run a drinks party in a brewery.
There was a paper that came out of Germany earlier this year that said the optimum replication rate in terms of keeping the economy going was 0.63. This idea that there is a trade off between health and business is false.
But the error bars on that R value are big enough that you should be very cautious. Both due to statistical noise and potential systematic error. If you see a range of 0.9-1.1, should you act like it's around 1? It might be prudent to inflate the figure by some amount.
Though pjc50’s comment looks pretty convincing given gov.uk could have used the same money to make it easier for businesses to restructure to offer delivery...
The chance of dying from the seasonal flu or getting permanent health damage is significantly less.
Counted like COVID19 there are only about 15 000 who die from Seasonal Flu in the US. Compare that to the 250 000 or so dead despite massive efforts to contain COVID19.
Every single attempt to count flu deaths "like Covid-19" that I've come across compares apples to oranges in a way that downplays the number of flu deaths. There are some really critical gotchas that make apparently like-for-like comparisons misleading.
For a start, Covid-19 testing is much more widespread than flu testing. The UK has been testing everyone hospitalized for any reason for Covid, which they don't do for flu, and I think other Western countries are broadly similar. The flu tests are also less sensitive. Not only that, but because flu tends to kill more via secondary bacterial pneumonia, apparently patients don't necessarily have enough influenza virus left to test positive by the time they're hospitalized, whereas Covid causes pneumonia directly. Also, there's strong statistical evidence that flu causes heart attacks which aren't recorded as influenza deaths on things like death certificates.
The headline CDC, etc stats take all this into account to estimate the number of people who died as a result of flu, in the sense that they'd have lived if they weren't infected. The "counted like Covid-19" stats generally don't count these as flu deaths, whilst comparing with stats that count almost anyone who died after being infected with Covid-19 as a Covid-19 death regardless of whether it was directly caused by Covid in this sense. They really don't compare like with like.
From the regime which oversaw the deaths of thousands of people in 'care homes' by moving Covid-19 infected hospital patients into care homes, reducing testing in care homes as the plague exploded in March, advising against mask use for care home staff, and that "if an employee becomes unwell and believe they have been exposed to COVID-19 [...] normal practice should continue".[0]
Yes, the same regime that notoriously made the UK a sick joke around the world after openly announcing its preferred strategy of infecting as much of the population as possible with a deadly plague.
"the highest risk activity" seems somewhat hyperbolic. Eating at restaurants when tables are appropriately spaced and masks are worn when not actually eating is not extremely dangerous.
Another feature of the scheme was that they made people crowd together on just three days of the week. It was absolutely packed in some places and almost empty for the rest of the week.
This is a hugely different from just "restaurants", for many reasons:
- restaurants have wait staff, so the guests are much more stationary, whereas in bars every round requires a walking trip to the bar for at least one person per group.
- restaurants have tables, and the guests are usually seated, whereas bars have much more people standing around and close together.
- as a result, the people walking around in restaurants can be controlled and trained, since they are employees. In bars, the people walking around are guests.
- restaurants are a quiet atmosphere, and people at the same tables can usually have an easy conversation. In most bars, there's music blaring at loud volume so people must lean in towards each other for every sentence.
I don't see how you go from "bars and restaurants have far and away been the driver" to "restaurants are one of the highest risk places" with a straight face. Can you point to studies showing how these differences don't make a diffference?
Bars are at the very top of the list, but restaurants are also risky. You won’t find studies, to my knowledge no one has done any.
Restaurants are not usually a quiet atmosphere, at least in north america. This loud volume gets people talking more loudly. Animated talking is common in restaurants: people go to socialize, not to quietly.
Bars are worse, but lack of masks in restaurants make them much riskier than masked activities. What places would you estimate are riskier than restaurants?
I’ll grant that bars are #1, but restaurants havw got to be #5 or so. (I’m assuming also that high risk things like choirs are shut down. If not then that changes assumptions a bit)
I can understand schools opening, but the devastating double peak when universities opened (Freshers week and then the 2nd/3rd years the week after) was totally avoidable.
There is minor peak at the end of August, but that is in my opinion actually holiday makers returning from infection ravaged Spain, as otherwise it would have been a month long peak.
Three peaks which line up perfectly with three national level mixing events? That happened in all regions round the country?
Bullshit.
If you want to play with simulations that clearly do not reflect real life, go ahead, but to me the Real World data is presently showing opening unis killed 10,000s people.
And it makes sense too. Eat out to help out you stayed in your local area. The time periods were short, often outside, and many of the people mixing were already exposed to each other.
Opening universities meant 100,000s of people moved around the country, met in big groups during induction, lots of mixing of new geographic regions. The time periods were long, often inside, and all the people mixing had never been exposed to each other.
Yes, an absolute disaster and they're going to blame it on Xmas instead of the actual cause, sending the students home. And then, they're going to let them go back again 2nd week of January :'(.
And not a single newspaper is reporting about it. The media should be shouting from the rooftops day after day that the 2nd wave was caused entirely by universities reopening and yet instead they regurgitate these releases from ONS blindly.
We could have reopened schools and accepted the small increase in actual cases, kept unis online only. But by reopening schools and universities, with the two events so close to each other they compounded and caused the 2nd wave.
As a small ray of hope, I know people who work in both the unis here in Notts and they're taking it very seriously and doing mass testing before they send them home, as well as staggering them being sent back. Hopefully other unis are too.
I've heard that one of the reasons Notts infection rate shot up so high compared to nationwide is because Nottingham University were aggressively contact testing with their own labs and found many more asymptomatic cases than the national government's shambolic track and trace system is presently achieving.
That's interesting - your final paragraph implies that there's a perverse incentive for local authorities to discourage testing to avoid being locked down..
Thats really interesting, but I dont see how staggering helps. Seems better to use entry/exit quarantine. Like, online learning during the first week and last week of the semester.
Staggering helps a bit as it will mean some people who were asymptomatic become symptomatic before they go home, and they can't realistically police a quarantine of something like 60,000 - 80,000 students, of which something like 70% live off campus.
I'm not sure of the exact figures, I think Nottingham Uni has like 45k students and Nottingham Trent has about 25k.
The other thing is that the official "Nottingham City" boundary is actually quite small and has only 320k residents and I'd happily bet at least £50 that the official government figures don't include the students as residents which is why Nottingham has such a high "cases per 100,000" because the true population count is something like 25% higher than the the "official" one, artificially inflating the proportional cases count.
I think the UK government realised its mistake, and is trying to unwind it as safely as possible.
"From 3 December to 9 December, which will be known as the ‘student travel window’, students will be allowed to travel home on staggered departure dates set by universities, who will work with other institutions in the region to manage pressure on transport infrastructure.
The student travel window will mean students can travel having just completed the four-week period of national restrictions, reducing the risk of transmission to family and friends at home.
Universities should move learning online by 9 December so students can continue their education while also having the option to return home to study from there."
"Fresher's flu" is the name given to the phenomenon of nearly everyone at uni getting a cold when returning for the new academic semester; everyone congregating from across the country/planet brings their own strain and gives it to everyone else.
We know that this happens every year, so we knew that it would happen this year too.
The main problem in the "Western approach" to the pandemy has been the logic: The effect has not been rigorously proven ⇒ The effect does not exist.
All your inputs are uncertain information to varying degrees, yet you still have to decide something. And the correct strategy is not to sit put and decide nothing.
> The effect has not been rigorously proven ⇒ The effect does not exist.
There's a great article on the BBC news homepage fighting this effect now about Vitamin D.
The TL;DR is the government says "Vitamin D cannot be said to help coronavirus infections, but we strongly recommend everyone take vitamin D supplements, and it's so important we'll even give them out for free"
Schools and universities open in fall, respiratory diseases usually come back in fall. Doesn't mean they are related. This virus looks fairly seasonal.
Indeed, I feel compliance where I am is fairly low, already. Yes, people largely follow the rules, but they are looking for every loophole they can find, and they are completely ignoring basic things like physical distancing and limiting the number of people they interact with.
It's worth remembering that the original lockdown models always factored in a certain amount of non compliance, and afterwards the model makers expressed suprise that real levels of non compliance were significantly lower than expected.
Non compliance concerns are often a social group function or a side effect of anxiety. it's normal for humans to identify enemies and other groups to make them feel better.
A spectral enemy that one can blame for the bad things.
I wouldn't be surprised if the UKs behavioural modification experts know and use this too.
It would have worked if one acted earlier. Then lockdown would have lasted shorter and more moderate restrictions could have been put in place which people could more easily follow.
Ofoten The problem is authorities come with too draconian restrictions too late rather than coming with milder restrictions earlier.
You’re right, and it’s frustrating that this discussion is often framed as a binary choice between lockdown and back to normal.
IMO what we really need to be doing is looking at making lasting changes to society to keep things working safely. We’re seeing a little of that, but not nearly enough.
> Wasn’t R<1 the magic number for ending the first lockdown?
NO!!!
Sorry this is infuriating. What’s the point of getting to R<1 if you then immediately end lockdown and have it shoot right back us? It’s a necessary step, but just abstep in the process. You need to stay in lockdown long enough to get case counts low enough to be able to fully trace.
Something I learned after moving from the UK to Germany, is that my German friends think Otto von Bismarck invented modern public health in 1883 and the NHS was based on their model.
My German language and history is not good enough for a rigorous comparison.
Bismarck did create the first public health system back then and the model is called the Bismarck Model. The NHS is nothing like that though and is based on what's called the Beveridge Model after the man who proposed it:
Headline begs the question - what the hell did we think we were doing between August and November?
Numbers were low which makes R very hard to calculate. When numbers are low, it doesn't matter much if there is some growth. And, finally, we were under tiered area restrictions depending on local rates (though I felt the chosen restrictions were a bit odd). Finally, in some parts of the country, a full lockdown didn't really make sense even when it was ordered (though arguably, this is lockdown-lite compared to the spring).
Keeping R<1 is the mandatory criteria for not having your health system collapse. So the goal of lockdowns is to make R<1 and to keep it that way.
As soon as R>1 you need the next lockdown, so when it's working and R is going down, it kind of makes sense to wait for R<0.8 and not just R<0.999 before you end the lockdown, or else you'll have to restart the next one very soon.
It will, as an R higher than 1 means that there will be no maximum in the new infections at all (while any health system obviously does have a maximum capacity that is significantly lower than the size of the population).
R going lower than one means, there will be a maximum in the future. Of course, only when numbers are currently increasing.
R is basically the second derivation of the case count (+1). So a lower R first means that the increase in new infections decreases, until the new infections decrease.
Even R>1 has a maximum in future new infections because R gradually declines over time as more people have had the disease and have some form of protection.
You need to understand that people are still being ventilated on sub-optimal machines outside a proper ITU; a lot of care has been cancelled; and many hospitals are currently on the cusp of declaring major incidents and closing access (including A&E) to any new patients.
I genuinely don't understand what the public thinks of when people in healthcare talk about system collapse. What level of dysfunction and preventable death is needed for the public to accept that the system has collapsed?
People use the word 'collapse' to predict problems in healthcare, but then we never see it happen, as health systems don't 'collapse' - medical professionals just work in increasingly degraded conditions. It's not like they're a routed army who all flee at signs of losing the battle.
> People use the word 'collapse' to predict problems in healthcare, but then we never see it happen, as health systems don't 'collapse' - medical professionals just work in increasingly degraded conditions.
I don't get it. We do see problems in healthcare. The excess mortality we're seeing at the moment is a combination of deaths directly caused by covid, but also deaths caused by reduced access to healthcare. When we change long-established norms (eg 1:1 nurse:patient ratios) this is system collapse.
Here's how I think of "collapse": you suffer some serious injury or illness, you call for an ambulance and told that none are available. You get a friend to drive you to the nearest A&E department to be told to come back tomorrow as there's no room left. You drive to another to be told the same.
This is all entirely possible in 2020 to 1000s of people, and I still wonder why people think lockdowns are a bad idea.
Doctors had to make a decision about which patients to let die, because there wasn't enough space for everyone who needed medical help. That's called triage and pretty horrible. In my opinion, that is a collapse of the system in the sense that it can no longer fulfill its duties on an acceptable level.
After the first lock down the government allowed everyone to go on holiday abroad. In theory people had to quarantine on their return, but compliance was very low and spread during the flight back was inevitable.
R is a useful value for statisticians. For policy makers it’s just mumbo jumbo that means exactly the same as the infections graph: if it’s going up, R is above 1, if it’s going down R is below 1. It’s not magic.
This is false, the R value cannot tell you about the future or wether graphs are ‘likely to go down’. They tell you wether the graph is going down, which you can tell from the graph. It just quantifies this.
This is exactly why the R value is not very useful. It is calculated over historical data so it has no predictive power whatsoever. However, it does falsely appear to have this power. Quote:
> There is always a slight time lag in the R number of a matter of weeks
I’m no statistician, but for me the most egregious failures on this have been constant use of ‘The’ R number and ‘The’ curve. The implication is that we have a single infallible measure that’s universally applicable, with no reference to exactly how R from different studies were weighted to come up with the announced figure, or how the sample populations of each study were skewed.
> There is always a slight time lag in the R number of a matter of weeks
ah ok: that's not what I understand from how governments are reporting it.
My understanding is that it's the (best estimate) of how virus cases are spreading today.
Since the graph of cases for today tells you how the virus has spread in the last two weeks, that's not the same information.
If you claim that R is only estimated from the historical number of cases, then R is not giving you information that you couldn't technically identify from this graph, I agree. However, R could be estimated using other information.
> what the hell did we think we were doing between August and November
I assume our political leaders made a decision with the following inputs:
0. As someone with a degree in classics, I don't have an intuitive understanding of how fast exponential growth can get out of control.
1. The death rate dropped from 9500/week in mid-April to 300/week in mid-July. And stayed below 300/week until the end of September.
2. Our scientific/medical advisors say we should keep things locked down - but it's their job to be cautious, they're medical advisors not economic advisors. I have to weigh up their advice against other interests.
3. Compared to at the start of the first lockdown, we now have more testing capacity and PPE. Face masks are now available for everyone not just medical staff, for example.
4. There are loads of industries saying if they can't re-open they'll need a government bail-out and we've already spent an eye-watering amount of money on the furlough scheme.
5. Some of these industries, like gyms and universities, point out that having them open is good for the nation. Keeping schools closed seems to be widening the performance gap between rich and poor children. People avoiding hospitals is leading to more cancers going untreated.
6. Countries like Sweden and America haven't locked down at all.
7. We're going to keep a lot of restrictions in place, with restaurants and theatres running at a fraction of their normal capacity, so it's not like we're going completely back to normal.
8. The prime minister's own chief advisor is breaking lockdown rules because he's bored of them, and punishing him isn't an option, so it'd be a lot less embarrassing if we could make what he did allowed retroactively.
Between these inputs, our leaders convinced themselves that lowering restrictions was the right thing to do in August.
For reference, this is the former head of research for Pfizer. The video (and him) have been banned off all the social media platforms due to “misinformation” (really a disagreement about the efficacy of the PCR protocol and how it has lead to a larger false positive rate).
Even with false positives the real case number is probably larger just because of the combination of asymptomatic cases and the lack of randomized community screening.
In the UK, one of the main things used to estimate the value of R is randomly sampling people from the population and testing them for Covid-19 regardless of symptoms.
It's worth bearing in mind that initially (and until only a few months ago iirc) tests were only available to certified essential workers - first NHS staff, then civil servants, etc. I actually paid £100 for a private test in May. I've had an NHS drive-thru one more recently.
I'm not sure of the absolute veracity of your 'regardless of symptoms' claim. As I understand it, the R number is calculated based on all the NHS tests done (and private, with some lag iirc). This even explicitly says "You cannot get a free NHS test unless you have symptoms, have been asked to by your local council, live in England and have been told to by your hospital, or are taking part in a government pilot project."
I believe they also run a programme of random tests regardless of symptoms. A friend of mine was selected for this and they periodically come to his house and take a sample.
Ah ok. Any idea how extensive the programme is and what weight it's given in relation to overall testing?
Obviously if this is the only / main input to the R number then my previous comment is crap and I retract it. Otherwise, I think I gave reasonable examples of how the sampling has been skewed, in good faith.
The false part is "tests were only available to certified essential workers".
That's true for people seeking tests, and workplaces etc.
But the statistical sampling was conducted separately by the Office of National Statistics (not the NHS) across the whole country in order to understand the pandemic, and it did have access to tests for this purpose.
While you’re right in absolute terms, I think you’re obscuring a valid point.
The ONS having tests doesn’t change the fact that for the vast majority of the population, being an essential worker was the only way to get a test.
The ONS tests are not the only input to the announced R number are they? Maybe I’m misunderstanding horribly, but it seems like you’re saying there’s absolutely no correlation whatsoever between availability of tests to the general public and the accuracy of the announced R number for the general public.
If I’m misunderstanding I do genuinely want to understand!
> it seems like you’re saying there’s absolutely no correlation whatsoever between availability of tests to the general public and the accuracy of the announced R number for the general public.
Depends what you mean by accuracy, whether that's bias or uncertainty. If you're talking about bias, then I agree with the above statement. My estimate of the mean bias in published R estimates is zero. (Possibly on a logarithmic scale :-)
But if you're talking about uncertainty and not bias, then in general more data is better provided its biases are known, but it's hard to say that focusing tests on a subset of the population reduces certainty. In a mathematical sense, to minimise uncertainty from sampling estimates if you have a fixed number of samples but a choice about which situations to assign them to, you want to focus more testing on the situations which provide the highest information content. That is not necessarily the same as spreading them evenly through the population in an unbiased manner.
I think what you may be misunderstanding, and therefore misrepresenting, is the idea that a combination of statistically sampled tests (ONS) plus biased targeted tests (NHS, key workers, Test & Trace etc) results in "skewed" or more misleading R estimates than just the statistically sampled tests (ONS) by themselves. I think that's unlikely.
I'm assuming the data is combined by competent professional statisticians.
Assuming they are competent, the likelihood of any biases due to NHS sampling that you or I might think of not having already been evaluated by the statisticians is negligible.
So, provided the bias can be estimated, combining data from multiple sources tends to reduce uncertainty rather than introducing bias in a particular direction.
That's why I say my personal "estimate of mean bias" is zero. Published R may by higher or lower than true R, and we can take it for granted it will be off by some amount and constantly (and retroactively) revised with new data, which is fair enough for estimations, but I have no basis on which to assume corrected results are more likely to have bias in one direction or the other.
A nice feature of having two or more kinds of sampling is that intentionally-randomly-sourced data (ONS) acts as an "anchor" on the interpretation of non-ONS data, allowing raw biases from various sources to be estimated and adjusted for, uncertainties to be estimated too, while at the same time trends (such as over time) remain trackable with the higher statistical power that comes from larger numbers of samples.
In other words, a bit of the best of both worlds. And since r and R are trend parameters, that's quite helpful.
Thanks, that's enlightening. I am definitely not a statistician, as you've no doubt guessed!
>I think what you may be misunderstanding, and therefore misrepresenting, is the idea that a combination of statistically sampled tests (ONS) plus biased targeted tests (NHS, key workers, Test & Trace etc) results in "skewed" or more misleading R estimates than just the statistically sampled tests (ONS) by themselves.
Not quite, and I apologise if I've communicated poorly. Totally agree that multiple sampling methods lead to more convincing results. I avoid optimising until I've profiled with both a sampling AND an instrumenting profiler, for example.
What I was trying (failing!) to get across is that I think that if the distribution of 'generally available' tests is sufficiently non-representative, then the statistically sampled test model potentially couldn't correct for it enough for the derived estimate to be reliable.
Obviously the responsible subgroup at SAGE will have tried to weight accordingly, and the people running the individual studies will as you say, be much more skilled at accounting for potential bias than I am. I'm absolutely not saying that I've stumbled on some insight that they missed!
Here's where I struggle - the pool of generally available tests at the time fall into two relatively narrow groups: patients exhibiting symptoms bad enough to require hospitalisation, and people at high risk of transmission. The random longitudinal studies don't have that problem of course and should be used to correct for the bias. I realise there are methods for quantifying bias and uncertainty, but isn't this more at risk of inaccuracy than simply having a higher N? N matters, surely? The higher confidence we have that any one set of data is representative, the higher confidence we can have in the final derived estimate.
I just can't see any angle from which having tested more people we wouldn't have improved our ability to estimate R.
> It's worth bearing in mind that initially (and until only a few months ago iirc) tests were only available to certified essential workers - first NHS staff, then civil servants, etc.
You’re not saying true things. Why are you spreading this disinformation despite everyone correcting you? They’ve been randomly sampling. R values are randomly sampled.
Ok, I really am arguing in good faith here. Not intending to spread disinformation. Would you mind spending the time to conclusively correct me?
So. Are you saying that the R number given by the government is derived from data only from random sampling, and that other test statistics do not feed into the estimate at all?
I’m not a statistician or epidemiologist and I find that very hard to believe. But I will honestly be happy to have learned something if you can teach me otherwise.
My understanding was that longitudinal studies using random sampling were used to check and correct the numbers derived from the actual test numbers for the real population. That meant the longitudinal studies would have been even more important early on when access to testing was poor, because the sample distribution was obviously skewed wrt the whole population.
Again, I really would appreciate a substantial rebuttal, link or otherwise.
It specifically says that they have been conducting ongoing random sampling of volunteers, outside of people being tested because they're possibly presenting symptoms.
> as of latest release of survey data on the 25 June 2020, 27,494 individuals out of 17139 households enrolled have agreed to continue to be tested
It does say they've been doing random sampling. They also say that randomly sampled longitudinal surveys are the best predictors. They also list (p32) all the other data sources that are used to estimate R in different studies - including case numbers from tests taken by symptomatic members of the general public.
Section 7.1 Case Numbers notes that Pillar 1 tests aren't a good predictor, Pillar 2 and 3 can be useful but (heavily paraphrasing here if you'll excuse me) the results need to be adjusted and hedged.
Section 8 of the rs paper specifically says that longitudinal studies should be used on a much wider scale than they are being, because of asymptomatic transmission. So in August, there was not enough random longitudinal testing, and an over-reliance on studies based on case numbers!
My controversial comment said that early on, access to testing would have skewed things, making R harder to confidently estimate (better wording this time?). I.E. Pillar 2 and 3 tests were not available to the non-essential members of the general public early on.
Is it fair to say that makomk's comment "one of the main things used to estimate the value of R is randomly sampling ... regardless of symptoms" is broadly true (now) - but that my comments about poor early access to testing skewing early R estimates is also broadly true? They're both supported by the paper you linked, imo.
Edit: To be clear, I was wrong about there being no access to testing without symptoms, as at least some random longitudinal testing was happening early on - just not enough, according to the paper you linked.
Is having the virus without symptoms really a case? The Coronavirus act says so. However, there's only tenuous evidence of asymptomatic and presymptiomatic transmission of the virus.
Kids tested with no symptoms had the same viral load in their nasal cavities as symptomatic cases so there's little reason to believe they were less effective spreaders than a person showing symptoms.
The crazy thing for that article is, it basically says there aren't any excess deaths, which is one of those conclusions where you ought to stop and think "Wait, surely that's a high level statistic I could cross-check?" and sure enough yes there are excess deaths statistics calculated, that's a normal thing countries do - and of course the US stats shot up due to COVID-19.
It's written by an economist, which maybe explains why they didn't check. You won't get far in economics if you insist on checking whether your work matches reality. Ask Arthur Laffer.
The graph on the second page is really low quality (I can't read the X-axis, the highlighted section is a different size, and the highlighted section has 2 additional series that don't show up in the key), so it's really hard to say for sure, but it's totally possible for both to be true: If most of the deaths so far were a "culling effect" of people likely to die later in the year, then the net by the end of the year could be "no difference".
Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year.
> Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year.
Life expectancy at birth, and life expectancy given a particular age are very different.
Most of those Covid deaths were above life expectancy are using life expectancy at birth figures, which is very misleading (as if you make it 82 you're almost certainly a fitter than average 82 year old).
The year 2020 isn't over as we write this, so of course your hypothesis is technically possible. In the final weeks of the year US death rates could fall through the floor compared to normal.
But that's not a hypothesis about the existing data, that's a guess about the future, and probably not a very good one.
This presentation masqueraded as an analysis of existing data, and the existing data shows a big rise in excess deaths. A competent analysis ought to at the very least point out this discrepancy and try to address it.
The alternatives are the author wasn't aware that excess deaths statistics are available or worse they were aware those statistics contradicted their thesis and decided to hope the audience didn't know.
Somebody else has linked one of the sites that charts US death figures. They are not subtle. In some countries you have to squint to see any impact from COVID-19, because the data is noisy and their population is small. (And maybe their reaction was effective, we can say this is the case for New Zealand but less clearly for say, Finland). But for the US it's an obvious anomaly, a prolonged excess over months.
So compared to 2018 and 2019, there is no change in deaths for those aged 45 and younger.
However there is an increase in death apparent for those aged above that, such that overall deaths when comparing up to Week 46 are 9.5% higher in 2020 than 2019. However, 2019 was a very weak flu season, with no excess death periods in England:
If you reduce 2020 deaths by the amount that didn't occur in 2019 due to the weak flu season but did occur in 2018, then 2020's deaths are only 6.8% higher than 2018. Consider also that in those two years the population of the UK aged 45 and above increased by 1.7%.
The question is - is COVID just shuffling fundamentally unhealthy people off their mortal coil a bit faster than would have occurred naturally? How many COVID deaths are really due to ongoing societal issues like Vitamin D deficiency, air pollution, poor diets and obesity? Or simply just old age?
Is shutting down and completely disrupting society for something which is about 5% worse than a regular flu season in terms of deaths really justified? Would we have noticed without the media attention?
The reason why they are banned is because what he is saying sounds plausible but is very, very likely wrong.
First of all, the number of tests isn't growing at the same rate as the number of cases, hospitalizations and deaths: https://imgur.com/2cVrGz7
You can notice the very low positive rate in mid August (150 000 tests and only 500 cases - even if all false positives, thats 0.3% FP rate)
But okay, lets assume that they did something to ramp up the false positive rate, If we look at the daily rate of growth (% increase) for cases, hospitalizations and deaths:
We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively!
If you were accidentally getting false positives, you would either not expect hospitalizations and deaths to grow at the same rate as false positives do. Even if they did, you would expect them to grow at exactly the same time without any delays. If there is no causal relationship they should all grow at the same rate, at the same time as any other random subgroup of people
To get the delay to happen, you would have to somehow perfectly fine tune the false positives for hospitalizations and deaths as well. In which case you're better off just making numbers up.
But more importantly, there is a much simpler explanation, which we get if we super-impose google mobility trends % increase in amount spent staying at home, and we shift cases by 6 days (avg time to symptoms), hospitalizations by 11 and deaths by 22 days:
We can see that the rate of growth is almost perfectly inversely correlated with the % increase in staying at home (with perhaps some light seasonal / immunity / other measures effects included).
Additionally we have non-PCR data like the Zoe symptom tracker app largely corraborating more or less the same rate of growth as detected by PCR tests: https://covid.joinzoe.com/data#levels-over-time
But more generally, there is a fundamental problem with social media: it unfortunately acts a generator of large amounts of "perfect bullshit".
First, it gets thousands of people to generate various conspiracy theories and plausable looking ideas. Many of these will be interesting and have some real merit, but most of them wont. (By itself, this doesn't do much - we're people, we generate ideas and theories, many of them wrong - nothing special about this process).
Then, give people the retweet button, and have them act as a filter for the most convincing looking bullshit. This is where things go terribly wrong. Retweets are a powerful amplifier. What gets retweeted? Is it the most throughly researched content? Highly unlikely, most people aren't experts in the subject (heck, I don't even dare go into the mechanics of the theory, only the math and stats) but they will still retweet if they find it interesting, plausible and aligned with what they strongly believe or wish was true.
Side note: having some authority (Nobel prize, etc) also helps a lot with this process. Still, remember that social networks won't differentiate whether 1 scientist is actually having this idea or many, and worse, it won't necessarily inform you if many scientists are actually demonstrating how the idea is wrong (unless they make it equally interesting for a retweet)
Finally, trick people by giving them dopamine system rewards (notifications for retweets and likes). They inevitably end up surrounded by a group of supporters that praise and retweet what they say. This whole process makes it so much harder for people (even scientists) to go back on what they said if it turns out they were wrong.
So what do you end up with? You end up with a system that delivers the most perfect bullshit to the largest number of people. The scientists that tweet the same old boring conservative stuff (words like "likely" often appear) are largely voiceless.
I don't think any single person is necessarily at fault in this system. But I do think that the system is a total disaster, and we have to invent something better than this. These simplistic social network designs are failing humanity.
This is a good point - it is essentially a distributed multiple comparisons problem, further compounded by lots of dubious assessments of significance.
I’m sorry, don’t want to ban other (especially qualified) viewpoints just because they are “likely wrong”.
To his point and yours, how does this compare to normal flu? I don’t know, I don’t see that example in your data. The problem as this highly qualified individual states it, is that they’re looking for a diagnosis and are changing the number of times amplification of the dna occurs over time.
Am I sure of his claims, no.
But either way, I appreciate hearing both view points. Having minored in bioengineering in school I can understand both arguments and make the determination myself... provided I have the info.
I don't think bans are the answer, but see my other comment about how social networks end up generating the perfect bullshit and make it hard for scientists to go back on their theory and to realize whether they're wrong or not.
Bans don't solve the issue. We have to invent better social networks, where scientists can be free to theorize and be connected with their peers, without getting false awards (retweets, likes).
In general as humanity we also need to be more aware of the nature of social networks and how they don't always elevate the best content.
As for credentials, you have to realize that the mechanics of social networks are very good at finding and amplifying the few individuals with credentials that have something wrong (but interesting) to say. What you don't get to hear about are the dozens of reviews of that theory, also by experts, that show how its wrong. Because thats just not interesting for a retweet, and its kind of a downer, too.
I’m fully aware, I actually built something that quantifies what other experts think of your opinion.
It’s called InsiderOpinion (insideropinion.com).
That being said, the reality is that social media has over stepped as late. I’m literally being forced to “thedonald.win” or some other sh to find broadened perspectives.
Perhaps some insight as to why people have trouble believing scientists at the moment... they told everyone “masks and gloves don’t work” (to keep supply for essential workers) then told everyone “make your own masks” (btw studies going back to the early 1900s says masks will work if it’s droplet based) we also now have evidence masks don’t work. We knew this would be the case because back in January and February they confirmed it was airborne. Multiple studies since confirmed this. Basically the virus can survive in the air and our cloth masks aren’t good enough. Part of Biden’s transition team said that on Joe rogan’s podcast in March.
Then we had the whole “don’t go into crowds” followed by “oh protests are for a good cause, so it’s okay” and stuff like that.
The reality is that the public shouldn’t trust what they are being told. Literally everything has been a lie thus far.
* WHO recommended that sick people wear (surgical) masks since February at home to reduce the chances of spreading the virus in the household - if they can't fully isolate. (You can check this using archive.org - I don't have the link readily at hand, unfortunately)
* Yes, PPE was a concern but also it was thought that there is no spread without symptoms initially. Which was the main reason why masks were not recommended for the wider population:
* non-respirators don't really *protect* the wearer
* respirators like N95 do but PPE is in short suply
* if you have symptoms, wearing a mask helps, sure, but best to fully isolate as much as possible.
* Opinion largely changed due to incoming evidence of presymptomatic spread - and yes, some campaigning by various groups like masks4all.
I'm sure there were some people and groups that connected the PPE and "masks don't work and thats why they are not recommended" but it was certainly not a blatant lie - it was really thought they wouldn't help and isolation for the infected is much better. With presymptomatic (and therefore possibly asymptomatic) spread and the realization of millions infected everywhere, everyone wearing masks became a viable option.
Aerosols are a whole other topic I won't get into (and I don't really have the expertise for it either!) but suffice to say from my understanding its not really as simple as "works" / "doesn't work".
Yes there is a problem with science failing us here as well, as the bar for evidence is simply set too high and the processes are too slow to deal with a pandemic. This is true for medications too...
Also, here is a counterpoint that you may have not seen because its just not as interesting to retweet (I applaud Ian for the effort with the GIFs but while that helps, its not enough to offset the novelty/interestingness factor of the original theory):
Flu is really serious, which is why we have nationally co-ordinated campaigns of surveillance and monitoring, and then rapid vaccination development, and then programmes to immunise as many vulnerable people as possible.
So far, we think covid-19 is about 10 times worse than flu.
On an average year in the UK flu kills about 10,000 people. So far Covid has killed many more - at least 50,000.
But this is using an inclusive definition for "killed by flu" that will include many people, and it's using a restrictive definition for "killed by covid" that will undercount deaths.
If you have to cycle 40 times for example, that is like finding a needle in a haystack, i.e. not understood how relevant such high precision is in terms of weather someone is actively spreading, or had it a month ago, etc.
> But okay, lets assume that they did something to ramp up the false positive rate, If we look at the daily rate of growth (% increase) for cases, hospitalizations and deaths:
> We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively!
What locale is this graph from? Because it does not at all match.. let's say, the US, where there's now been 3 peaks and the number of daily cases doubled each peak, but the daily deaths was highest in the first peak. They are not growing at remotely the same rate over here, even with a 5 or 16 day delay.
> let's say, the US, where there's now been 3 peaks and the number of daily cases doubled each peak, but the daily deaths was highest in the first peak.
If one tries comparing the US data with the data from other developed countries, what can be seen is that only the third peak in the US has the "realistic" ratio of cases to deaths, that is, one which better corresponds to the ratio from the countries which were able to handle the outbreaks better, as in, being able to detect enough cases early enough, and for that appropriate test capability, adequate to the incidence, seems to be necessary. The approximate expected ratio, worldwide, seems currently (with obviously better testing infrastructure compared to Spring, and as long as the hospitals aren't too stressed) to be 1 case of death per 100 registered "cases", after a delay, and when using some averages across a moving window of data for both both cases and deaths, e.g. 7 day average.
In the first peak in the US it was as high as almost 1 death per 14 cases(!!) -- around 32K detected daily cases with 2.2K deaths were the peaks of the averages! In the second peak in the US it was 1 death per 60 cases. Both show that there weren't enough cases detected, compared to some other countries, and that more appropriate level of testing was achieved in the US only during the third wave. But if there are some systematic delays in reporting deaths during the third wave, it can still turn out that what we see at the moment will look worse, once the wave is over. Even that effect is known to exist in the reporting of one European country: Sweden, where the systematic reporting delay of deaths during the wave gives very wrong impression of the ratio as long as the wave is raising, compared to other countries: https://news.ycombinator.com/item?id=25122196 There are some signs that such an effect can be in play in the US as well.
Additionally, what one has to be aware of is that any statistics over a big population will at different points of time not always proportionally reflect the contribution of the events in different areas -- e.g. New York. That way, some big problems for the local population will appear "less bad" when averaged, which shouldn't be comforting.
This is the UK. The number is rate of growth, not number of cases
Its similar to Rt but its much easier to calculate. To get Rt, you need to estimate how many people are infected on average by one person at any point in time. This is usually done by simulating the process in various ways.
To get the daily rate of growth on the other hand, all you need to do is look at the actual numbers. Assuming you had 110 cases today and 100 cases yesterday, the current rate of growth is 10%. Since the rate calculated this way will be a bit erratic, I use some averaging and exponential smoothing to get the general trend.
The code to generate these graphs is available here: https://colab.research.google.com/drive/1QDZgdGkOzs6dP74-iED... - it uses the UK coronavirus API and google mobility trends reports directly from their respective URLs, so it should be easy to make a copy of the notebook, review/modify it and re-run it.
Why is the ratio of positive cases to hospitalizations different? I'd say this is mostly due to testing capacities being very different between now and March. In March in the UK for example it was impossible to get a test unless things are so bad that you need to get hospitalized. This is very different from now where anyone with symptoms (or just saying they have symptoms) can get tested.
Based on the graph, another reason for the different ratio between cases and deaths seems to be the period July to mid August. This was a period where the growth rate of cases didn't match the growth rate of hospitalizations and deaths at all. This likely means that parts of the population that wasn't that succeptable to severe outcomes were getting infected (which makes sense given that bars were opened up again at the beginning of July - although that is speculation)
We empircally know he is wrong because when schools went back there was a MASSSSSSIVE spike it requested tests (as school children got their start of season colds and worried parents got them tested in the first 2 weeks of school returning).
But there was not a MASSSSSIVE spike in Covid cases.
If Covid numbers were being driven by false positives then there HAD to be a massive spike in cases as testing numbers spiked. There was not. So false positives cannot be the reason.
Why would someone who deals in facts do such a thing? Surely the correct position would be to correct and remove.
Personally anyone who refers to his material is tarnished.
On a general point, there are many people now growing in fame (and monetising that) due to the pandemic. Are their interests aligned with a pandemic ending, what do they pivot to?
Considering the OP is calling into question why this person was booted from some social media, posting lies about public hospitals and their staff during a pandemic seems a fair reason.
Shame the posts on Twitter remain and a shame Twitter themselves have not taken action.
"A source just gave me the following information. A hospital in Wales, Nevill Hall in Abergavenny, has 250 beds. 200 beds are empty. The surgeons are bored & pass much time on the nearby golf course.
I think this might be one answer to why UK doctors are not investigating to find out why hospitals have no patients in them! Apparently all covid cases are currently being sent to this hospital.
This story tallies with the original evidence which drew me into this ghastly mess we’ve made of our country.
I’ve not mentioned this..."
You appear a clever chap, so you can verify that the statements are false. You can also locate where the author also states they are false, but does not delete them.
It might be a sixth form debating point, but you have also have previously posted "The problem is that it has become acceptable to treat ideas as dangerous. For example, if I want to deny the Holocaust, that is my right."
Brexit was sorted out ages ago. No deal. Johnson has wanted that from the start of his Preimership, doesn't need to deal and can try and blame the EU for when things go wrong.
The lack of thought people put into Northern Ireland during the referendum was outrageous. The Good Friday Agreement was nearly written in blood, and we're pissing on it because the Tories couldn't put out their own fire.
The worst part is that the people who actually voted for all this will be long dead before the impact becomes apparent.
You could quite easily argue that another vote was conducted in the form of the 2019 General Election, which the Tories - the only party of note who actually were in favour of Brexit - won by a landslide.
Brexit surely played a huge role, given Corbyn's near victory in 2017. If there was a flaw to Labour's 2019 Brexit "agnosticism" policy, it was that it was not pro-Brexit enough -- Starmer's former Brexit-hostility (such as his "6 tests for Brexit") is gone, and he will probably use the whip to vote for almost any negotiated deal. I only hope there is a deal.
I think it was literally more Corbyn screwed up massively. There was pretty much no Anti Brexit campaign. It was from as a far I could see between a guy who wanted Brexit to be over with and a guy who was wanting to play around with Brexit.
I suspect if Labour came out hard on anti Brexit they could have won even with Corbyn. The anti-EU feeling in the UK is nowhere near as bad as it was 4 years ago when they held the vote.
They probably don't want no-deal, but it's not in their interest to bother to try particularly hard to avoid it.
Regardless the country is not in a good place. I look forward to Kent being flattened and concreted over to form a giant truck stop.
Thank god we're having a government funded festival of Brexit. £120E6 fuck you to everyone who'll actually have to live in the country they've shat on in the coming decades
Interest rate payments are lower now than they were pre-pandemic, even though total debt has spiraled. CoE is not signaling for a return to austerity, and hopefully nobody will in future. WW2 debt was paid off even while creating the NHS, etc.
> Interest rate payments are lower now than they were pre-pandemic
For now. But some major ingredients of inflation are on the way: currency devaluation and more expensive imports, both due to a no deal/shit deal for Brexit. And if inflation goes up, interest rates will increase to try to control it (or even more government spending which will rack up even more debt).
> CoE is not signaling for a return to austerity
How else will we repay the enormous debt? They won't call it austerity just like they're now using the euphemism "Australia-style deal" instead of "no deal", but austerity is coming alright (that along with tax hikes).
What incentive is driving this trend is democracies? In UK, America, Japan, pretty much every other western/European democracy the government debt is ever growing and money printing is only growing and growing.
> What incentive is driving this trend is democracies?
I guess you're getting at election politics? Spend money that's borrowed so you don't need to increase taxes, point at all the good things you've done.
Some people think this is kicking the can down the road, but again, if the bomb doesn't explode in my hands it's fine.
This is incorrect. The EU as a whole shows sovereign debt to GDP falling fairly smoothly since 2014 (though it will rise this year). The UK and Japan have had static or slightly falling debt since around then too (though the UK's will _skyrocket_ over the next couple of years). The US is rising a little.
Given the market for sovereign debt right now, there's no strong incentive to pay it off aggressively as long as it's not rising too sharply.
Looking at https://coronavirus.data.gov.uk/
and you can see that current daily infections (tested and confirmed) is way higher than any time in September as are deaths. So whilst the R number and how it is calculated may be down, I'll not place my caution upon such `good` news.
After all this R of below 1 is based upon a reduction in those testing positive and 3 weeks of a country lock-down and you would expect that number to reduce, otherwise your whole reason for a lock down would be proven to of been futile. So that's good, lock downs do work - science shown that here(again).
Looking at the same site, I see "People tested positive" is down by 25% in the last 7 days, and the number tested has been stable in the same time interval, so the ratio is also down by 25%.
I don't see any other figure called "current daily infections"; do you mean something other than "people tested positive"?
The reduction in the last 7 days is considerable and suggests lockdown is working surprisingly well (considering it is hardly noticeable in some places, even though other places are more severely closed).
Prior to that it was indeed higher than any time in September, and deaths still are, hopefully just due to time lag.
If it's just time lag and 25% reduction per 7 days is already in the pipeline, that is very promising.
It does not hijack it. OP simply contains bbc.co.uk link, which gets redirected to bbc.com, so when you press "back" you get back to the bbc.co.uk link and immediately get redirected back to bbc.com. By pressing the button twice fast enough you will get back to HN.
BBC should be doing a 302 (or 301 if you assume people never change countries) redirect. Then the there would be no back button problems. Currently they're serving a page via a 200, then doing a Javascript redirect.
I suppose it's just less likely to be misunderstood among people who 8 months ago had never heard of the concept of "R" (or "the R number", or "c" probably) - especially in a language that people hearing "R" in a sentence will probably hear it as "are" or "our" before "R".
I'm much more annoyed by use of "coronavirus" to describe this specific virus.
The same is currently happening in Romania [1] (the country that I live in), even though we don't have the crazy and draconian restrictions imposed on countries like the UK. Not to mention that I've read yesterday the British PM saying that those restrictions will most likely last until late winter - early next spring, as "the beast" must be defeated/tamed or similar such non-sense. This isn't even technocratic leadership (which I'm not a big fan of), it's cargo-cult leadership.
Most probably the school being out (since I think early October), indoor restaurants and coffee-shops are closed (but this being Romania there are many “original” workarounds for that) and there are a couple of cities under similar lockdown as in Britain (you’re not allowed to go outside unless for work/essential shopping/small recreation) but not a lot of people respect even those (because it’s not heavily enforced).
Shops are still open in Romania and I can meet my friends indoor at their (or my) places with no restrictions (the “crazy” part from my first comment was addressing mostly this part), but if the English are happy with this intrusion in their private life then who am I to judge?
Given the population density of the UK is three times that of Romania it’s not really a surprise that you can get your R number below one with less strict measures than we have in the UK.
Yeah, it's probably the easiest option to rotate it 90 or 45 degrees. Any other solutions I can think of would require significantly more development overhead. Not sure such a minor thing is worth too too much effort
It's less the label smushing and more the fact that the bubbles overlap that annoys me. This makes it hard to see what's going on on mobile on arguably the most important chart on the site.
Plausible.io tells me that for today for the spike from this comment, 70% of users were on mobile. I might try the rotation thing. Thanks for the feedback!
Are you using just reported positive cases to infer the value of R on this website? Or are you using estimates from local authorities? Or are you doing your own epidemiological modelling to go from raw positive cases to R values?
In the UK, epidemiological modelling is done by various government bodies and universities, and it is this that is being reported in OP:
tl;dr is that we use a single datasource (not managed by us but by many dedicated others) and use case counts to estimate number of currently infectious and from that we estimate R. The running time of our R estimation calculations for all regions is around 1.5 hours on a $10/month Digital Ocean droplet.
Sometimes strange looking results on our site picked up by guests can be fed back to the maintainers of the datasource resulting in a correction of the data.
On our website, R value estimation is done by my father, a retired computer science professor with a long history of mathematical modelling experience. This is hacker news right? :)
Is it possible to get aggregate numbers? Say for the Nordics and for Scandinavia, or other such regions of tightly knit countries or regions? Most "Scandis" like to compare with the other Scandinavian countries, and with select European countries that are similar, such as the Netherlands and Belgium.
Not at the moment unfortunately. The display breaks down by the hierarchical organisation of the data source.
It might be possible to build up a list of regions as you navigate through the site, and then show only those in the bubble chart so that you can compare them. Interesting idea.
We wouldn't be able to aggregate infectious or R estimates for one or more regions together as the computation for those is done during deploy and then that processed data is uploaded along with the static site (it doesn't connect to a database to fetch data on the fly).
279 comments
[ 4.6 ms ] story [ 239 ms ] threadWasn’t R<1 the magic number for ending the first lockdown?
FWIW I’ve always been suspicious of the way R is used by the government and media. It’s always going to be a best guess averaged over an area, but with asymptomatic transmission and initially poor access to testing, seems like it should be treated with caution. Not dismissed, but not the main driver, I guess.
Their main beef over the pandemic has been when ministers and the government have been lying fairly explicitly about testing targets (counting posted tests as completed tests).
I find BBC as a whole hasn't been as critical, but they certainly seem to be at least making an effort to explain and contextualise. They aren't parroting government statistics as much as they could be doing.
Straight out of the Trump playbook of course... Every critical question and exposure of wrong doing is actually just biased media.
The headline assumes its conclusion in a premise? Perhaps you meant the headline raises the question?
But 'begs the question' is avoiding the issue. Not (necessarily) assuming the conclusion.
“Vice President, actually.”
https://dictionary.cambridge.org/dictionary/english/beg-the-...
R was good enough in London, back then. That's all they were worried about.
I got temperature check and covid symptom questionnaire on entry to (private) hospital, but it's not widespread.
I've gotten a temperature check every time I've entered a commercial building for the last few months (in NYC), but temperature checks hew dangerously close to safety theater.
To add to the anecdata, in Massachusetts I've only had my temperature checked at a doctor's office but I've also visited very few places.
https://abc13.com/temperature-checks-covid-coronavirus-sympt...
The problem is that the US media have quite consistently only reported on the fact that they're useless when talking about them being implemented in the US. When China and the WHO claimed they were the basis for China's success in containing the virus, pretty much everyone - including publications like the New York Times - uncritically regurgitated that claim. Same with places like (if I remember rightly) Taiwan using it for airport screening. Anyone who got their beliefs from the mainstream media would be left convinced that America was failing because it hadn't adopted these successful measures from places like China.
Starting the new school year, for one thing. For many of us that was critical to letting us keep working (and mass home-schooling and online teaching for young kids was not working).
The university side didn't seem to work out as well - possibly partly because uni staff are (understandably) less willing to work crunch hours to meet duty of care than primary school staff.
Reopening universities was - students do get it, and they all live together in shared accommodation so as soon as one got it lots of them did.
During the summer, when they talked about opening schools and claimed that young children weren’t major vectors for the virus, I was very skeptical and assumed it was mostly just an excuse -- but it does actually seem to have worked out! If primary school children were spreading the virus en masse, the current spike would be vastly bigger.
(It’s very unfortunate in the US that school opening has been so strongly politicized.)
Opening the universities is another matter entirely. That definitely shouldn’t have been done. I was going to say “in hindsight” but in fact that was pretty obvious right away.
"Young children transmit less
Researchers suspect that one reason schools have not become COVID-19 hot spots is that children — especially those under the age of 12–14 — are less susceptible to infection than adults, according to a meta-analysis4 of prevalence studies. And once they are infected, young children, including those aged 0–5 years, are less likely to pass the virus on to others, says Haas. In an analysis5 of German schools, Haas’s team found that infections were less common in children aged 6–10 years than in older children and adults working at the schools. “The potential to transmit increases” with age, and adolescents are just as likely to transmit the virus as adults, he says. Teenagers and teachers should be the focus of mitigation measures, such as wearing masks or a return to online lessons when community transmission is high, says Haas."
Is this not why the situation persists? Lockdown hard then go back to pretty-much-normal seems vastly preferable. I say this from NZ. The hit has been hard, but it seems that partial lockdowns and half measures actually lead to worse outcomes. The death toll is certainly on another scale when you don’t lock down.
https://www.google.com/amp/s/amp.rnz.co.nz/article/ba935329-...
It was too late (even though Italy was bad and a good canary, UK politicians did nothing). Even if the country remains in permanent lockdown the virus will still spread now for months/years.
Just at the state level debt is expected to more than triple by FY23/24 to $155b.
https://www.reuters.com/article/uk-health-coronavirus-britai...
What we really want are goods and services to consume. If people aren't going to work and producing goods and providing services then there will be less to go around making us all poorer.
It's a tiny island nation that is in no way economically independent from its trading partners.
And yet, they've figured out how to stop both community spread, and travel-related spread.
Pretty much every tourist flew in, and tourists are in close proximity to each other for 4+ hours. It doesn’t matter how often New Zealanders fly internationally if tourists come in infected. The UK has international flights that last a 15-20 minutes. This could give you covid for sure, but it may avoid infecting the whole plane.
A total of about 3.8 million tourists arrived in NZ in 2019, a number equivalent to about 75% of NZs population. The UK had about 38 million tourists in 2018 (most recent numbers available) and that equates to about 56% of the UKs population. NZ had a lot of tourists relative to its population.
https://en.m.wikipedia.org/wiki/Tourism_in_New_Zealand
https://en.m.wikipedia.org/wiki/Tourism_in_the_United_Kingdo...
Even now we are getting people fly in with covid every day, usually several cases and this is happening without there being international tourism anymore.
The UK doesn’t even require self isolation in all cases and having tried asking people to self isolate in NZ, we know exactly how it doesn’t work. Managed isolation is hard enough to get right.
https://www.gov.uk/uk-border-control
Overall, what happened in NZ was impossible in the UK due to a lack of will, not anything else. NZ was willing to sacrifice it’s largest industry. How would you describe the approach used in the UK? It doesn’t appear to have a particular focus or goal.
I don’t believe the tourism argument holds up in the slightest either. The UK has the fourth largest number of yearly inbound tourists visitors in the world. New Zealand is 69th. Source: https://www.indexmundi.com/facts/indicators/ST.INT.ARVL/rank...
The degree to which the UK is connected to the world is just on a different scale to New Zealand. That’s before you even consider the geography, population density, and wealth distribution sides of the argument. It was always going to be more difficult to control it in the UK. I don’t think lack of will is a valid excuse either. What country doesn’t want to get back to normal as quickly as possible? Why is it that only this tiny island in the Pacific has managed to do it? Is every single other country is simply that incompetent? It just doesn’t make sense. There has to be other factors involved.
> Sure, source https://www.citypopulation.de/en/world/bymap/AirTrafficPasse...
If you order that list by ‘per capita’ NZ is way above the UK, 13th versus 24th. I think you have misread it and got the absolute number of travellers.
> The degree to which the UK is connected to the world is just on a different scale to New Zealand.
In absolute numbers, yes, per capita, no. With covid the thing that matters is people coming into contact. The ratio tourists/population matters. NZ has a lot of travel and relative to it’s population, a lot more than the UK. And NZs population travel a lot more.
> I don’t believe the tourism argument holds up in the slightest either.
How so? Tourists bring in covid.
If you look at things relative to the population, NZ has a lot of people moving a lot of the time.
NZ may be a small, far away islands (it’s bigger than the UK geographically), but the approach NZ used wasn’t invented here and is not novel. It was copied from others that had success. Interestingly, a lot of good policy came from South Korea. South Korea copied it from the NHS. Others have had good results too, NZ is not alone at any stretch and did not pioneer it’s policies.
I’m sure there are other factors and many of them. However the UK leaders have not done well and have contributed hugely to the problems. The ignoring of advice from experts is incredible - why set up systems if you don’t want them? They continue to ignore the most basic advice and get exactly the outcome one would expect, covid.
I actually never at any point said that I thought the UK was doing things well (I'm not from the UK). My point is that I don't think NZ's success was down especially to brilliant leadership so much as a combination of factors that make it a uniquely hard place for a disease like COVID to enter and spread.
Trade in goods is also mostly via very long sea journeys which off course act as a sort of quarantine period. In terms of air travel Auckland is the only hub airport and the number of transit passengers is quite small.
Continental europe would have faced a harder time coordinating it.
They could have done this sometime over the summer. Going zero covid has huge economic benefits. And with testing you could let business travellers in with a modified isolation.
If the below is the source, you’re citing an absolute, not per capita stat. NZ ranks significantly above the UK for travel per capita, and the UK population do not travel that much.
https://www.citypopulation.de/en/world/bymap/AirTrafficPasse...
Remember, this is a very good way of spreading Covid-19 to new areas - it's almost certainly how it got into Beijing, which was the best and most aggressively protected city in all of China at the time.
NZ has nothing that comes close. Australia is about a 4hr flight away.
People in transit infect each other, and workers are exposed to more chances to get infected, but it's a more manageable situation than land borders.
The UK absolutely could have chosen to not have tens of thousands of people die for no purpose, but its political leadership were focused, as ever, on what's in it for them. How much can we exploit this to line our own pockets, how many old mates can be rewarded? Sure, people are dying, but isn't this a perfect chance to loot the corpses?
There is a general curfew at midnight and health districts of the metropolitan area have been selectively locked down, but everything else has remained open: restaurants, gyms, non-essential businesses, etc.
Cases per 100k are not low but they have been declining for weeks now, with most of the city largely open for business.
The death toll is on the scale of normal seasonal flu outbreaks when you subtract the deaths caused by lockdowns (i.e. that occur during lockdowns but that don't mention COVID on the death certificate). New Zealand is screwed by the way: good luck with international travel from now on.
Can you provide a source showing covid is less deadly that the flu?
I can travel internationally from NZ and can get back in if I want to, but I don’t want to leave NZ. Why are we screwed? Everything is normal here now.
Source: look at excess death data for most European countries. Even in the UK which had a significant wave of non-COVID excess deaths during the first wave (a little under half of them didn't mention COVID on the death certificate), excess deaths from it was similar to the winter of 1999/2000. And in countries that have less incompetent management the waves of deaths are similar to flu waves.
There are many, many sources you can get the data from. Try EuroMoMo, the national statistical agencies etc. But here's just one example, long term Swedish mortality data:
https://swprs.org/wp-content/uploads/2020/10/sweden-monthly-...
Remember Sweden didn't lock down. Modelling predicted a bloodbath which never happened.
As for NZ, what kind of business or tourist travellers will go to New Zealand now they have to be temporarily imprisoned at their own absurdly high expense? Adding a more than $3000 charge per person to arrival, plus lost time? Your island is currently a pariah state that people will avoid visiting unless absolutely necessary, indefinitely.
I assume at some point these rules will be dropped for those who can show an immunity passport because it's the only way New Zealand doesn't just drop off the face of the planet, but vaccines aren't 100% effective and even the vaccinated can still carry the virus: they just get milder symptoms. So it's not at all clear how New Zealand plans to ever open back up.
They paid us to eat at restaurants ... basically the highest risk activity.
> Eligible establishments are those in which food is sold for immediate on-premises consumption.
...
> The discount cannot be applied to the following items:
> ...
> * food or drink that is to be consumed off premises
https://www.gov.uk/government/publications/get-more-informat...
Trying to protect waiters/esses jobs, maybe?
Though pjc50’s comment looks pretty convincing given gov.uk could have used the same money to make it easier for businesses to restructure to offer delivery...
(Not comparing the two diseases, but wondering where grim Covid attitudes will persist)
Counted like COVID19 there are only about 15 000 who die from Seasonal Flu in the US. Compare that to the 250 000 or so dead despite massive efforts to contain COVID19.
For a start, Covid-19 testing is much more widespread than flu testing. The UK has been testing everyone hospitalized for any reason for Covid, which they don't do for flu, and I think other Western countries are broadly similar. The flu tests are also less sensitive. Not only that, but because flu tends to kill more via secondary bacterial pneumonia, apparently patients don't necessarily have enough influenza virus left to test positive by the time they're hospitalized, whereas Covid causes pneumonia directly. Also, there's strong statistical evidence that flu causes heart attacks which aren't recorded as influenza deaths on things like death certificates.
The headline CDC, etc stats take all this into account to estimate the number of people who died as a result of flu, in the sense that they'd have lived if they weren't infected. The "counted like Covid-19" stats generally don't count these as flu deaths, whilst comparing with stats that count almost anyone who died after being infected with Covid-19 as a Covid-19 death regardless of whether it was directly caused by Covid in this sense. They really don't compare like with like.
Yes, the same regime that notoriously made the UK a sick joke around the world after openly announcing its preferred strategy of infecting as much of the population as possible with a deadly plague.
[0] https://www.gov.uk/government/publications/guidance-for-soci...
We just had an outbreak in halifax and bars and restaurants have far and away been the driver.
https://fortune.com/2020/06/26/is-it-safe-restaurant-coronav...
This is a hugely different from just "restaurants", for many reasons:
- restaurants have wait staff, so the guests are much more stationary, whereas in bars every round requires a walking trip to the bar for at least one person per group.
- restaurants have tables, and the guests are usually seated, whereas bars have much more people standing around and close together.
- as a result, the people walking around in restaurants can be controlled and trained, since they are employees. In bars, the people walking around are guests.
- restaurants are a quiet atmosphere, and people at the same tables can usually have an easy conversation. In most bars, there's music blaring at loud volume so people must lean in towards each other for every sentence.
I don't see how you go from "bars and restaurants have far and away been the driver" to "restaurants are one of the highest risk places" with a straight face. Can you point to studies showing how these differences don't make a diffference?
Restaurants are not usually a quiet atmosphere, at least in north america. This loud volume gets people talking more loudly. Animated talking is common in restaurants: people go to socialize, not to quietly.
Bars are worse, but lack of masks in restaurants make them much riskier than masked activities. What places would you estimate are riskier than restaurants?
I’ll grant that bars are #1, but restaurants havw got to be #5 or so. (I’m assuming also that high risk things like choirs are shut down. If not then that changes assumptions a bit)
https://ny.eater.com/2018/6/6/17429648/steve-cuozzo-noisy-re...
[1] https://www.economist.com/graphic-detail/2020/11/28/why-euro... (paywalled, key graphic is this: https://i.imgur.com/JpmZtPk.jpeg )
R shot up only during two events. Schools opening and Universities opening, and you can see this clearly on this graph someone else linked:
https://reproduction.live/world/GB
I can understand schools opening, but the devastating double peak when universities opened (Freshers week and then the 2nd/3rd years the week after) was totally avoidable.
There is minor peak at the end of August, but that is in my opinion actually holiday makers returning from infection ravaged Spain, as otherwise it would have been a month long peak.
Because of the UK's testing policies around only testing symptomatic individuals, it's very difficult to answer questions like this effectively.
See here for example, where it suggests that restaurants are one of the highest risk activities: https://www.nature.com/articles/s41586-020-2923-3
Bullshit.
If you want to play with simulations that clearly do not reflect real life, go ahead, but to me the Real World data is presently showing opening unis killed 10,000s people.
And it makes sense too. Eat out to help out you stayed in your local area. The time periods were short, often outside, and many of the people mixing were already exposed to each other.
Opening universities meant 100,000s of people moved around the country, met in big groups during induction, lots of mixing of new geographic regions. The time periods were long, often inside, and all the people mixing had never been exposed to each other.
And not a single newspaper is reporting about it. The media should be shouting from the rooftops day after day that the 2nd wave was caused entirely by universities reopening and yet instead they regurgitate these releases from ONS blindly.
We could have reopened schools and accepted the small increase in actual cases, kept unis online only. But by reopening schools and universities, with the two events so close to each other they compounded and caused the 2nd wave.
As a small ray of hope, I know people who work in both the unis here in Notts and they're taking it very seriously and doing mass testing before they send them home, as well as staggering them being sent back. Hopefully other unis are too.
I've heard that one of the reasons Notts infection rate shot up so high compared to nationwide is because Nottingham University were aggressively contact testing with their own labs and found many more asymptomatic cases than the national government's shambolic track and trace system is presently achieving.
I'm not sure of the exact figures, I think Nottingham Uni has like 45k students and Nottingham Trent has about 25k.
The other thing is that the official "Nottingham City" boundary is actually quite small and has only 320k residents and I'd happily bet at least £50 that the official government figures don't include the students as residents which is why Nottingham has such a high "cases per 100,000" because the true population count is something like 25% higher than the the "official" one, artificially inflating the proportional cases count.
"From 3 December to 9 December, which will be known as the ‘student travel window’, students will be allowed to travel home on staggered departure dates set by universities, who will work with other institutions in the region to manage pressure on transport infrastructure.
The student travel window will mean students can travel having just completed the four-week period of national restrictions, reducing the risk of transmission to family and friends at home.
Universities should move learning online by 9 December so students can continue their education while also having the option to return home to study from there."
https://www.gov.uk/government/news/christmasguidance-set-out...
We know that this happens every year, so we knew that it would happen this year too.
I know because I'm in it.
And this is the most recent set of data : https://www.ons.gov.uk/peoplepopulationandcommunity/healthan...
The main problem in the "Western approach" to the pandemy has been the logic: The effect has not been rigorously proven ⇒ The effect does not exist.
All your inputs are uncertain information to varying degrees, yet you still have to decide something. And the correct strategy is not to sit put and decide nothing.
http://bostonreview.net/science-nature/trisha-greenhalgh-wil...
There's a great article on the BBC news homepage fighting this effect now about Vitamin D.
The TL;DR is the government says "Vitamin D cannot be said to help coronavirus infections, but we strongly recommend everyone take vitamin D supplements, and it's so important we'll even give them out for free"
isn't this alternatively of a case of holiday makers infecting each others in droves while vacationing in all the same places in Spain?
R was lower in Spain in July and August than in the UK.
20%+ of secondary school kids absent (isolating, ill, or being kept away), but they still stubbornly insist on keeping them open.
People were rebounding from not being able to visit their friends for 6 months.
Non compliance concerns are often a social group function or a side effect of anxiety. it's normal for humans to identify enemies and other groups to make them feel better.
A spectral enemy that one can blame for the bad things.
I wouldn't be surprised if the UKs behavioural modification experts know and use this too.
Ofoten The problem is authorities come with too draconian restrictions too late rather than coming with milder restrictions earlier.
IMO what we really need to be doing is looking at making lasting changes to society to keep things working safely. We’re seeing a little of that, but not nearly enough.
NO!!!
Sorry this is infuriating. What’s the point of getting to R<1 if you then immediately end lockdown and have it shoot right back us? It’s a necessary step, but just abstep in the process. You need to stay in lockdown long enough to get case counts low enough to be able to fully trace.
To be fair, they've made a mess of the whole pandemic, which is very disappointing given that public health was invented there.
My German language and history is not good enough for a rigorous comparison.
https://en.wikipedia.org/w/index.php?title=Otto_von_Bismarck...
It is perhaps a mark of public health's incredible success that both replies think I was talking about the NHS.
Also, Bismarck invented the modern industrial state long before anyone else had realized this stuff was important.
https://morningsignout.com/international-health-care-systems...
http://morningsignout.com/international-health-care-systems-...
Numbers were low which makes R very hard to calculate. When numbers are low, it doesn't matter much if there is some growth. And, finally, we were under tiered area restrictions depending on local rates (though I felt the chosen restrictions were a bit odd). Finally, in some parts of the country, a full lockdown didn't really make sense even when it was ordered (though arguably, this is lockdown-lite compared to the spring).
As soon as R>1 you need the next lockdown, so when it's working and R is going down, it kind of makes sense to wait for R<0.8 and not just R<0.999 before you end the lockdown, or else you'll have to restart the next one very soon.
R is basically the second derivation of the case count (+1). So a lower R first means that the increase in new infections decreases, until the new infections decrease.
You need to understand that people are still being ventilated on sub-optimal machines outside a proper ITU; a lot of care has been cancelled; and many hospitals are currently on the cusp of declaring major incidents and closing access (including A&E) to any new patients.
I genuinely don't understand what the public thinks of when people in healthcare talk about system collapse. What level of dysfunction and preventable death is needed for the public to accept that the system has collapsed?
One source: https://www.hsj.co.uk/acute-care/difficult-to-maintain-emerg...
I don't get it. We do see problems in healthcare. The excess mortality we're seeing at the moment is a combination of deaths directly caused by covid, but also deaths caused by reduced access to healthcare. When we change long-established norms (eg 1:1 nurse:patient ratios) this is system collapse.
The average person expects a single dramatic event, and that never happens.
This is all entirely possible in 2020 to 1000s of people, and I still wonder why people think lockdowns are a bad idea.
Not in the uk they didn't, no.
R tells you: the graph is likely to keep going up (or will peak and go down). Policy makers should care about this more.
This is exactly why the R value is not very useful. It is calculated over historical data so it has no predictive power whatsoever. However, it does falsely appear to have this power. Quote:
> There is always a slight time lag in the R number of a matter of weeks
ah ok: that's not what I understand from how governments are reporting it.
My understanding is that it's the (best estimate) of how virus cases are spreading today.
Since the graph of cases for today tells you how the virus has spread in the last two weeks, that's not the same information.
If you claim that R is only estimated from the historical number of cases, then R is not giving you information that you couldn't technically identify from this graph, I agree. However, R could be estimated using other information.
I assume our political leaders made a decision with the following inputs:
0. As someone with a degree in classics, I don't have an intuitive understanding of how fast exponential growth can get out of control.
1. The death rate dropped from 9500/week in mid-April to 300/week in mid-July. And stayed below 300/week until the end of September.
2. Our scientific/medical advisors say we should keep things locked down - but it's their job to be cautious, they're medical advisors not economic advisors. I have to weigh up their advice against other interests.
3. Compared to at the start of the first lockdown, we now have more testing capacity and PPE. Face masks are now available for everyone not just medical staff, for example.
4. There are loads of industries saying if they can't re-open they'll need a government bail-out and we've already spent an eye-watering amount of money on the furlough scheme.
5. Some of these industries, like gyms and universities, point out that having them open is good for the nation. Keeping schools closed seems to be widening the performance gap between rich and poor children. People avoiding hospitals is leading to more cancers going untreated.
6. Countries like Sweden and America haven't locked down at all.
7. We're going to keep a lot of restrictions in place, with restaurants and theatres running at a fraction of their normal capacity, so it's not like we're going completely back to normal.
8. The prime minister's own chief advisor is breaking lockdown rules because he's bored of them, and punishing him isn't an option, so it'd be a lot less embarrassing if we could make what he did allowed retroactively.
Between these inputs, our leaders convinced themselves that lowering restrictions was the right thing to do in August.
https://lbry.tv/Mike-Yeadon-Unlocked:0
For reference, this is the former head of research for Pfizer. The video (and him) have been banned off all the social media platforms due to “misinformation” (really a disagreement about the efficacy of the PCR protocol and how it has lead to a larger false positive rate).
I'm not sure of the absolute veracity of your 'regardless of symptoms' claim. As I understand it, the R number is calculated based on all the NHS tests done (and private, with some lag iirc). This even explicitly says "You cannot get a free NHS test unless you have symptoms, have been asked to by your local council, live in England and have been told to by your hospital, or are taking part in a government pilot project."
https://www.gov.uk/get-coronavirus-test
Obviously if this is the only / main input to the R number then my previous comment is crap and I retract it. Otherwise, I think I gave reasonable examples of how the sampling has been skewed, in good faith.
That's true for people seeking tests, and workplaces etc.
But the statistical sampling was conducted separately by the Office of National Statistics (not the NHS) across the whole country in order to understand the pandemic, and it did have access to tests for this purpose.
The ONS having tests doesn’t change the fact that for the vast majority of the population, being an essential worker was the only way to get a test.
The ONS tests are not the only input to the announced R number are they? Maybe I’m misunderstanding horribly, but it seems like you’re saying there’s absolutely no correlation whatsoever between availability of tests to the general public and the accuracy of the announced R number for the general public.
If I’m misunderstanding I do genuinely want to understand!
Depends what you mean by accuracy, whether that's bias or uncertainty. If you're talking about bias, then I agree with the above statement. My estimate of the mean bias in published R estimates is zero. (Possibly on a logarithmic scale :-)
But if you're talking about uncertainty and not bias, then in general more data is better provided its biases are known, but it's hard to say that focusing tests on a subset of the population reduces certainty. In a mathematical sense, to minimise uncertainty from sampling estimates if you have a fixed number of samples but a choice about which situations to assign them to, you want to focus more testing on the situations which provide the highest information content. That is not necessarily the same as spreading them evenly through the population in an unbiased manner.
I think what you may be misunderstanding, and therefore misrepresenting, is the idea that a combination of statistically sampled tests (ONS) plus biased targeted tests (NHS, key workers, Test & Trace etc) results in "skewed" or more misleading R estimates than just the statistically sampled tests (ONS) by themselves. I think that's unlikely.
I'm assuming the data is combined by competent professional statisticians.
Assuming they are competent, the likelihood of any biases due to NHS sampling that you or I might think of not having already been evaluated by the statisticians is negligible.
So, provided the bias can be estimated, combining data from multiple sources tends to reduce uncertainty rather than introducing bias in a particular direction.
That's why I say my personal "estimate of mean bias" is zero. Published R may by higher or lower than true R, and we can take it for granted it will be off by some amount and constantly (and retroactively) revised with new data, which is fair enough for estimations, but I have no basis on which to assume corrected results are more likely to have bias in one direction or the other.
A nice feature of having two or more kinds of sampling is that intentionally-randomly-sourced data (ONS) acts as an "anchor" on the interpretation of non-ONS data, allowing raw biases from various sources to be estimated and adjusted for, uncertainties to be estimated too, while at the same time trends (such as over time) remain trackable with the higher statistical power that comes from larger numbers of samples.
In other words, a bit of the best of both worlds. And since r and R are trend parameters, that's quite helpful.
>I think what you may be misunderstanding, and therefore misrepresenting, is the idea that a combination of statistically sampled tests (ONS) plus biased targeted tests (NHS, key workers, Test & Trace etc) results in "skewed" or more misleading R estimates than just the statistically sampled tests (ONS) by themselves.
Not quite, and I apologise if I've communicated poorly. Totally agree that multiple sampling methods lead to more convincing results. I avoid optimising until I've profiled with both a sampling AND an instrumenting profiler, for example.
What I was trying (failing!) to get across is that I think that if the distribution of 'generally available' tests is sufficiently non-representative, then the statistically sampled test model potentially couldn't correct for it enough for the derived estimate to be reliable.
Obviously the responsible subgroup at SAGE will have tried to weight accordingly, and the people running the individual studies will as you say, be much more skilled at accounting for potential bias than I am. I'm absolutely not saying that I've stumbled on some insight that they missed!
Here's where I struggle - the pool of generally available tests at the time fall into two relatively narrow groups: patients exhibiting symptoms bad enough to require hospitalisation, and people at high risk of transmission. The random longitudinal studies don't have that problem of course and should be used to correct for the bias. I realise there are methods for quantifying bias and uncertainty, but isn't this more at risk of inaccuracy than simply having a higher N? N matters, surely? The higher confidence we have that any one set of data is representative, the higher confidence we can have in the final derived estimate.
I just can't see any angle from which having tested more people we wouldn't have improved our ability to estimate R.
You’re not saying true things. Why are you spreading this disinformation despite everyone correcting you? They’ve been randomly sampling. R values are randomly sampled.
So. Are you saying that the R number given by the government is derived from data only from random sampling, and that other test statistics do not feed into the estimate at all?
I’m not a statistician or epidemiologist and I find that very hard to believe. But I will honestly be happy to have learned something if you can teach me otherwise.
My understanding was that longitudinal studies using random sampling were used to check and correct the numbers derived from the actual test numbers for the real population. That meant the longitudinal studies would have been even more important early on when access to testing was poor, because the sample distribution was obviously skewed wrt the whole population.
Again, I really would appreciate a substantial rebuttal, link or otherwise.
Thanks
https://royalsociety.org/-/media/policy/projects/set-c/set-c...
It specifically says that they have been conducting ongoing random sampling of volunteers, outside of people being tested because they're possibly presenting symptoms.
> as of latest release of survey data on the 25 June 2020, 27,494 individuals out of 17139 households enrolled have agreed to continue to be tested
It does say they've been doing random sampling. They also say that randomly sampled longitudinal surveys are the best predictors. They also list (p32) all the other data sources that are used to estimate R in different studies - including case numbers from tests taken by symptomatic members of the general public.
Section 7.1 Case Numbers notes that Pillar 1 tests aren't a good predictor, Pillar 2 and 3 can be useful but (heavily paraphrasing here if you'll excuse me) the results need to be adjusted and hedged.
This page says they take many studies as input to the official R, including studies that look at test figures in the general population - https://www.gov.uk/guidance/the-r-number-in-the-uk
Section 8 of the rs paper specifically says that longitudinal studies should be used on a much wider scale than they are being, because of asymptomatic transmission. So in August, there was not enough random longitudinal testing, and an over-reliance on studies based on case numbers!
My controversial comment said that early on, access to testing would have skewed things, making R harder to confidently estimate (better wording this time?). I.E. Pillar 2 and 3 tests were not available to the non-essential members of the general public early on.
Is it fair to say that makomk's comment "one of the main things used to estimate the value of R is randomly sampling ... regardless of symptoms" is broadly true (now) - but that my comments about poor early access to testing skewing early R estimates is also broadly true? They're both supported by the paper you linked, imo.
Edit: To be clear, I was wrong about there being no access to testing without symptoms, as at least some random longitudinal testing was happening early on - just not enough, according to the paper you linked.
Thanks for reading ;)
https://www.uchealth.org/today/the-truth-about-asymptomatic-...
Lack of it? But isn’t that exactly how R is estimated?
Hard to tell this page doesn't really give details on how large the longitudinal and survey is conducted.
https://www.gov.uk/guidance/the-r-number-in-the-uk#about-r-n...
Johns Hopkins Newsletter deletes article re excess Covid-19 deaths --
https://twitter.com/JHUNewsLetter/status/1332100155986882562
It's written by an economist, which maybe explains why they didn't check. You won't get far in economics if you insist on checking whether your work matches reality. Ask Arthur Laffer.
(wrap in a joke tag)
Given the average age of deaths by COVID-19 being above average life expectancy, this totally seems possible to me - lots of excess deaths early in the year, but the opposite later in the year, resulting in net "deaths as usual" over the whole year.
Life expectancy at birth, and life expectancy given a particular age are very different.
Most of those Covid deaths were above life expectancy are using life expectancy at birth figures, which is very misleading (as if you make it 82 you're almost certainly a fitter than average 82 year old).
But that's not a hypothesis about the existing data, that's a guess about the future, and probably not a very good one.
This presentation masqueraded as an analysis of existing data, and the existing data shows a big rise in excess deaths. A competent analysis ought to at the very least point out this discrepancy and try to address it.
The alternatives are the author wasn't aware that excess deaths statistics are available or worse they were aware those statistics contradicted their thesis and decided to hope the audience didn't know.
Somebody else has linked one of the sites that charts US death figures. They are not subtle. In some countries you have to squint to see any impact from COVID-19, because the data is noisy and their population is small. (And maybe their reaction was effective, we can say this is the case for New Zealand but less clearly for say, Finland). But for the US it's an obvious anomaly, a prolonged excess over months.
A weirdly large number of economists seem to have taken it upon themselves to do dubious COVID work lately.
https://www.ons.gov.uk/peoplepopulationandcommunity/birthsde...
So compared to 2018 and 2019, there is no change in deaths for those aged 45 and younger.
However there is an increase in death apparent for those aged above that, such that overall deaths when comparing up to Week 46 are 9.5% higher in 2020 than 2019. However, 2019 was a very weak flu season, with no excess death periods in England:
https://www.euromomo.eu/graphs-and-maps#z-scores-by-country
If you reduce 2020 deaths by the amount that didn't occur in 2019 due to the weak flu season but did occur in 2018, then 2020's deaths are only 6.8% higher than 2018. Consider also that in those two years the population of the UK aged 45 and above increased by 1.7%.
The question is - is COVID just shuffling fundamentally unhealthy people off their mortal coil a bit faster than would have occurred naturally? How many COVID deaths are really due to ongoing societal issues like Vitamin D deficiency, air pollution, poor diets and obesity? Or simply just old age?
Is shutting down and completely disrupting society for something which is about 5% worse than a regular flu season in terms of deaths really justified? Would we have noticed without the media attention?
First of all, the number of tests isn't growing at the same rate as the number of cases, hospitalizations and deaths: https://imgur.com/2cVrGz7
You can notice the very low positive rate in mid August (150 000 tests and only 500 cases - even if all false positives, thats 0.3% FP rate)
But okay, lets assume that they did something to ramp up the false positive rate, If we look at the daily rate of growth (% increase) for cases, hospitalizations and deaths:
https://imgur.com/bEix1Fo
We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively!
If you were accidentally getting false positives, you would either not expect hospitalizations and deaths to grow at the same rate as false positives do. Even if they did, you would expect them to grow at exactly the same time without any delays. If there is no causal relationship they should all grow at the same rate, at the same time as any other random subgroup of people
To get the delay to happen, you would have to somehow perfectly fine tune the false positives for hospitalizations and deaths as well. In which case you're better off just making numbers up.
But more importantly, there is a much simpler explanation, which we get if we super-impose google mobility trends % increase in amount spent staying at home, and we shift cases by 6 days (avg time to symptoms), hospitalizations by 11 and deaths by 22 days:
https://imgur.com/UKklUIP
We can see that the rate of growth is almost perfectly inversely correlated with the % increase in staying at home (with perhaps some light seasonal / immunity / other measures effects included).
Additionally we have non-PCR data like the Zoe symptom tracker app largely corraborating more or less the same rate of growth as detected by PCR tests: https://covid.joinzoe.com/data#levels-over-time
First, it gets thousands of people to generate various conspiracy theories and plausable looking ideas. Many of these will be interesting and have some real merit, but most of them wont. (By itself, this doesn't do much - we're people, we generate ideas and theories, many of them wrong - nothing special about this process).
Then, give people the retweet button, and have them act as a filter for the most convincing looking bullshit. This is where things go terribly wrong. Retweets are a powerful amplifier. What gets retweeted? Is it the most throughly researched content? Highly unlikely, most people aren't experts in the subject (heck, I don't even dare go into the mechanics of the theory, only the math and stats) but they will still retweet if they find it interesting, plausible and aligned with what they strongly believe or wish was true.
Side note: having some authority (Nobel prize, etc) also helps a lot with this process. Still, remember that social networks won't differentiate whether 1 scientist is actually having this idea or many, and worse, it won't necessarily inform you if many scientists are actually demonstrating how the idea is wrong (unless they make it equally interesting for a retweet)
Finally, trick people by giving them dopamine system rewards (notifications for retweets and likes). They inevitably end up surrounded by a group of supporters that praise and retweet what they say. This whole process makes it so much harder for people (even scientists) to go back on what they said if it turns out they were wrong.
So what do you end up with? You end up with a system that delivers the most perfect bullshit to the largest number of people. The scientists that tweet the same old boring conservative stuff (words like "likely" often appear) are largely voiceless.
I don't think any single person is necessarily at fault in this system. But I do think that the system is a total disaster, and we have to invent something better than this. These simplistic social network designs are failing humanity.
At the same time mainstream media has become pure propaganda. Interesting times.
To his point and yours, how does this compare to normal flu? I don’t know, I don’t see that example in your data. The problem as this highly qualified individual states it, is that they’re looking for a diagnosis and are changing the number of times amplification of the dna occurs over time.
Am I sure of his claims, no.
But either way, I appreciate hearing both view points. Having minored in bioengineering in school I can understand both arguments and make the determination myself... provided I have the info.
Bans don't solve the issue. We have to invent better social networks, where scientists can be free to theorize and be connected with their peers, without getting false awards (retweets, likes).
In general as humanity we also need to be more aware of the nature of social networks and how they don't always elevate the best content.
As for credentials, you have to realize that the mechanics of social networks are very good at finding and amplifying the few individuals with credentials that have something wrong (but interesting) to say. What you don't get to hear about are the dozens of reviews of that theory, also by experts, that show how its wrong. Because thats just not interesting for a retweet, and its kind of a downer, too.
It’s called InsiderOpinion (insideropinion.com).
That being said, the reality is that social media has over stepped as late. I’m literally being forced to “thedonald.win” or some other sh to find broadened perspectives.
Perhaps some insight as to why people have trouble believing scientists at the moment... they told everyone “masks and gloves don’t work” (to keep supply for essential workers) then told everyone “make your own masks” (btw studies going back to the early 1900s says masks will work if it’s droplet based) we also now have evidence masks don’t work. We knew this would be the case because back in January and February they confirmed it was airborne. Multiple studies since confirmed this. Basically the virus can survive in the air and our cloth masks aren’t good enough. Part of Biden’s transition team said that on Joe rogan’s podcast in March.
Then we had the whole “don’t go into crowds” followed by “oh protests are for a good cause, so it’s okay” and stuff like that.
The reality is that the public shouldn’t trust what they are being told. Literally everything has been a lie thus far.
* WHO recommended that sick people wear (surgical) masks since February at home to reduce the chances of spreading the virus in the household - if they can't fully isolate. (You can check this using archive.org - I don't have the link readily at hand, unfortunately)
* Yes, PPE was a concern but also it was thought that there is no spread without symptoms initially. Which was the main reason why masks were not recommended for the wider population:
* Opinion largely changed due to incoming evidence of presymptomatic spread - and yes, some campaigning by various groups like masks4all.I'm sure there were some people and groups that connected the PPE and "masks don't work and thats why they are not recommended" but it was certainly not a blatant lie - it was really thought they wouldn't help and isolation for the infected is much better. With presymptomatic (and therefore possibly asymptomatic) spread and the realization of millions infected everywhere, everyone wearing masks became a viable option.
Aerosols are a whole other topic I won't get into (and I don't really have the expertise for it either!) but suffice to say from my understanding its not really as simple as "works" / "doesn't work".
Yes there is a problem with science failing us here as well, as the bar for evidence is simply set too high and the processes are too slow to deal with a pandemic. This is true for medications too...
https://twitter.com/MackayIM/status/1331440271716827137
Flu is really serious, which is why we have nationally co-ordinated campaigns of surveillance and monitoring, and then rapid vaccination development, and then programmes to immunise as many vulnerable people as possible.
So far, we think covid-19 is about 10 times worse than flu.
On an average year in the UK flu kills about 10,000 people. So far Covid has killed many more - at least 50,000.
But this is using an inclusive definition for "killed by flu" that will include many people, and it's using a restrictive definition for "killed by covid" that will undercount deaths.
To give an idea of how flu in the UK is counted you can look at this report: https://assets.publishing.service.gov.uk/government/uploads/...
What does this mean?
https://bitesizebio.com/24581/what-is-a-ct-value/
If you have to cycle 40 times for example, that is like finding a needle in a haystack, i.e. not understood how relevant such high precision is in terms of weather someone is actively spreading, or had it a month ago, etc.
> https://imgur.com/bEix1Fo
> We can see that there is a perfect exponential 7% rate of growth starting in September and slowly decaying after. But more than that, the rate of growth in hospitalizations and deaths also follows the same pattern almost perfectly but with a 5 day and 16 day delay, respectively!
What locale is this graph from? Because it does not at all match.. let's say, the US, where there's now been 3 peaks and the number of daily cases doubled each peak, but the daily deaths was highest in the first peak. They are not growing at remotely the same rate over here, even with a 5 or 16 day delay.
If one tries comparing the US data with the data from other developed countries, what can be seen is that only the third peak in the US has the "realistic" ratio of cases to deaths, that is, one which better corresponds to the ratio from the countries which were able to handle the outbreaks better, as in, being able to detect enough cases early enough, and for that appropriate test capability, adequate to the incidence, seems to be necessary. The approximate expected ratio, worldwide, seems currently (with obviously better testing infrastructure compared to Spring, and as long as the hospitals aren't too stressed) to be 1 case of death per 100 registered "cases", after a delay, and when using some averages across a moving window of data for both both cases and deaths, e.g. 7 day average.
In the first peak in the US it was as high as almost 1 death per 14 cases(!!) -- around 32K detected daily cases with 2.2K deaths were the peaks of the averages! In the second peak in the US it was 1 death per 60 cases. Both show that there weren't enough cases detected, compared to some other countries, and that more appropriate level of testing was achieved in the US only during the third wave. But if there are some systematic delays in reporting deaths during the third wave, it can still turn out that what we see at the moment will look worse, once the wave is over. Even that effect is known to exist in the reporting of one European country: Sweden, where the systematic reporting delay of deaths during the wave gives very wrong impression of the ratio as long as the wave is raising, compared to other countries: https://news.ycombinator.com/item?id=25122196 There are some signs that such an effect can be in play in the US as well.
Additionally, what one has to be aware of is that any statistics over a big population will at different points of time not always proportionally reflect the contribution of the events in different areas -- e.g. New York. That way, some big problems for the local population will appear "less bad" when averaged, which shouldn't be comforting.
Its similar to Rt but its much easier to calculate. To get Rt, you need to estimate how many people are infected on average by one person at any point in time. This is usually done by simulating the process in various ways.
To get the daily rate of growth on the other hand, all you need to do is look at the actual numbers. Assuming you had 110 cases today and 100 cases yesterday, the current rate of growth is 10%. Since the rate calculated this way will be a bit erratic, I use some averaging and exponential smoothing to get the general trend.
The code to generate these graphs is available here: https://colab.research.google.com/drive/1QDZgdGkOzs6dP74-iED... - it uses the UK coronavirus API and google mobility trends reports directly from their respective URLs, so it should be easy to make a copy of the notebook, review/modify it and re-run it.
Why is the ratio of positive cases to hospitalizations different? I'd say this is mostly due to testing capacities being very different between now and March. In March in the UK for example it was impossible to get a test unless things are so bad that you need to get hospitalized. This is very different from now where anyone with symptoms (or just saying they have symptoms) can get tested.
Based on the graph, another reason for the different ratio between cases and deaths seems to be the period July to mid August. This was a period where the growth rate of cases didn't match the growth rate of hospitalizations and deaths at all. This likely means that parts of the population that wasn't that succeptable to severe outcomes were getting infected (which makes sense given that bars were opened up again at the beginning of July - although that is speculation)
Wrong on a spectacular level.
We empircally know he is wrong because when schools went back there was a MASSSSSSIVE spike it requested tests (as school children got their start of season colds and worried parents got them tested in the first 2 weeks of school returning).
But there was not a MASSSSSIVE spike in Covid cases.
If Covid numbers were being driven by false positives then there HAD to be a massive spike in cases as testing numbers spiked. There was not. So false positives cannot be the reason.
Here's a pretty good explainer: https://twitter.com/andrew_croxford/status/13308829944716533...
And another: https://twitter.com/andrew_croxford/status/13317220787777290...
Why would someone who deals in facts do such a thing? Surely the correct position would be to correct and remove.
Personally anyone who refers to his material is tarnished.
On a general point, there are many people now growing in fame (and monetising that) due to the pandemic. Are their interests aligned with a pandemic ending, what do they pivot to?
Considering the OP is calling into question why this person was booted from some social media, posting lies about public hospitals and their staff during a pandemic seems a fair reason.
Shame the posts on Twitter remain and a shame Twitter themselves have not taken action.
"A source just gave me the following information. A hospital in Wales, Nevill Hall in Abergavenny, has 250 beds. 200 beds are empty. The surgeons are bored & pass much time on the nearby golf course. I think this might be one answer to why UK doctors are not investigating to find out why hospitals have no patients in them! Apparently all covid cases are currently being sent to this hospital. This story tallies with the original evidence which drew me into this ghastly mess we’ve made of our country. I’ve not mentioned this..."
What in it is a known lie?
It might be a sixth form debating point, but you have also have previously posted "The problem is that it has become acceptable to treat ideas as dangerous. For example, if I want to deny the Holocaust, that is my right."
That is where I bow out, with a link to show how such 'ideas' and 'rights' have real world impact during this pandemic https://twitter.com/dashaburns/status/1332798207911399424?s=...
Have a great day / life etc.
The worst part is that the people who actually voted for all this will be long dead before the impact becomes apparent.
https://www.google.com/amp/s/www.independent.co.uk/voices/fi...
https://www.independent.co.uk/voices/final-say-remain-leave-...
I suspect if Labour came out hard on anti Brexit they could have won even with Corbyn. The anti-EU feeling in the UK is nowhere near as bad as it was 4 years ago when they held the vote.
Regardless the country is not in a good place. I look forward to Kent being flattened and concreted over to form a giant truck stop.
Thank god we're having a government funded festival of Brexit. £120E6 fuck you to everyone who'll actually have to live in the country they've shat on in the coming decades
For now. But some major ingredients of inflation are on the way: currency devaluation and more expensive imports, both due to a no deal/shit deal for Brexit. And if inflation goes up, interest rates will increase to try to control it (or even more government spending which will rack up even more debt).
> CoE is not signaling for a return to austerity
How else will we repay the enormous debt? They won't call it austerity just like they're now using the euphemism "Australia-style deal" instead of "no deal", but austerity is coming alright (that along with tax hikes).
The Bank of England has created most of the money, there's really no-one to pay it back to.
Certainly you should pay back the debt owed to external agencies, but there's no need to pay back that owed to your Central Bank.
If that's too crazy, then refinancing all of the debt over 30 yrs is probably the best solution, as it provides time for the economy to recover.
Conversely, given that demand from the private sector has dropped, if you introduce austerity then it will take longer to pay the debt back.
I guess you're getting at election politics? Spend money that's borrowed so you don't need to increase taxes, point at all the good things you've done.
Some people think this is kicking the can down the road, but again, if the bomb doesn't explode in my hands it's fine.
Given the market for sovereign debt right now, there's no strong incentive to pay it off aggressively as long as it's not rising too sharply.
After all this R of below 1 is based upon a reduction in those testing positive and 3 weeks of a country lock-down and you would expect that number to reduce, otherwise your whole reason for a lock down would be proven to of been futile. So that's good, lock downs do work - science shown that here(again).
https://www.gov.uk/guidance/the-r-number-in-the-uk#other-key...
I don't see any other figure called "current daily infections"; do you mean something other than "people tested positive"?
The reduction in the last 7 days is considerable and suggests lockdown is working surprisingly well (considering it is hardly noticeable in some places, even though other places are more severely closed).
Prior to that it was indeed higher than any time in September, and deaths still are, hopefully just due to time lag.
If it's just time lag and 25% reduction per 7 days is already in the pipeline, that is very promising.
Or right-click it like a normal person does
(yes, that excludes Mac users, they aren't normal)
(sarcasm)
It's like calling the speed of light "the c number" rather than "c".
I'm much more annoyed by use of "coronavirus" to describe this specific virus.
[1] https://www.graphs.ro/covid_r_ma7.php
Obviously this is a complicated scenario. From what great body of research are you drawing your conclusions?
Have you considered population quantity or density in your comparison of the two nations?
There is also a search on the landing page: https://reproduction.live which I should probably put in the sidebar of the dashboard page as well.
Plausible.io tells me that for today for the spike from this comment, 70% of users were on mobile. I might try the rotation thing. Thanks for the feedback!
In the UK, epidemiological modelling is done by various government bodies and universities, and it is this that is being reported in OP:
https://www.gov.uk/guidance/the-r-number-in-the-uk
tl;dr is that we use a single datasource (not managed by us but by many dedicated others) and use case counts to estimate number of currently infectious and from that we estimate R. The running time of our R estimation calculations for all regions is around 1.5 hours on a $10/month Digital Ocean droplet.
Sometimes strange looking results on our site picked up by guests can be fed back to the maintainers of the datasource resulting in a correction of the data.
On our website, R value estimation is done by my father, a retired computer science professor with a long history of mathematical modelling experience. This is hacker news right? :)
It might be possible to build up a list of regions as you navigate through the site, and then show only those in the bubble chart so that you can compare them. Interesting idea.
We wouldn't be able to aggregate infectious or R estimates for one or more regions together as the computation for those is done during deploy and then that processed data is uploaded along with the static site (it doesn't connect to a database to fetch data on the fly).
Useful resource for excess deaths in Europe