Coronavirus: Why aren’t death rates rising with case numbers? A UK perspective
theconversation.com
theconversation.com
https://www.evms.edu/covid-19/covid_care_for_clinicians/#d.e...
■ Vitamin C 500 mg BID and Quercetin 250-500 mg BID
■ Zinc 75-100 mg/day
■ Melatonin (slow release): Begin with 0.3mg and increase as tolerated to 2 mg at night
■ Vitamin D3 1000-4000 u/day
■ Optional: Famotidine 20-40mg/day
It's also important to note treatment isn't the same thing as a cure. Treatment is any medical care for the illness (i.e. things that help keep you alive through it) not just things that make the illness go away (bit of a rectangle/square thing).
tl;dr of what I've heard on various episodes
- "Standard care" practices have changed
- Dexamethadone
- Lot more of the younger population being infected who have typically been known not to die of the virus (relative to older folks)
- More testing which increases the denominator of CFR
https://www.cnn.com/audio/podcasts/corona-virus?episodeguid=...
And this will continue for at least another month. All in all it's rather amazing how by trying to do everything right the Victorian government has managed to do everything wrong.
At least the current government gets to wag its finger at people for wanting such unreasonable things as jobs, leaving your house after work, or sleeping with your partner for the first time in 3 months.
Consider that lockdowns cannot stop the virus forever. They were only ever pitched, even by advocates, as a delaying strategy to reduce pressure on hospitals. Total numbers of infected were never meant to change, as logic dictates. However lockdowns and other restrictions, when as long as they have been, do create new deaths by e.g. delaying cancer checkups and treatments, by causing job losses and subsequent poverty related deaths, by stopping the elderly from seeing their family - deaths by loneliness are a real thing in elderly care!
If you're going to assert that lockdowns can actually reduce the death rate rather than increase it you will need to give arguments for why that's the case, especially over the long term.
Try living under curfew for a few months and see if you still think that keeping 10000 people in their 80s alive for another two years is worth it.
It's worth noting that nobody until very recently was claiming lockdowns could eliminate outbreaks. That whole notion was deemed absurd as recently as June. The problem is obvious - for as long as there is a pool of people, somewhere, spreading the disease, and a large pool of people who haven't developed immunity, and international travel, then the virus will get in. Meanwhile lockdowns have catastrophic consequences far in excess of their benefits (halting COVID is not very important given how mild it is).
There's a lot of pile-on about how they've done everything wrong without a lot of suggestion about what they should've done instead / should currently be doing instead.
For example, if Andrews and co cave to the federal and local pressure and re-open the state today, and everything explodes in two weeks, who takes the blame then? Still Andrews and co.
While it's been a huge outbreak by Australian expectations, it's still tiny when compared to the rest of the world.
If we had the 10, 15,000 cases per million that are more commonplace around the world, there'd still be a stuffed economy, lower employment, increased mental health issues, right? We'd just have another layer of mess with hospital overload and death that we don't have in a large amount at the moment.
In short: open everything and let the devil take the hindmost. The alternative is a yo-yo lock down until Bangladesh manages to deploy a vaccine to everyone infected before the virus mutates, something that will happen in 202-never.
[0] Even the horror stories from New York were because they didn't have the capacity to bury people fast enough, not that they ran out of hospital beds.
New Jersey - At capacity, Elective surgeries cancelled
Alabama - Elective Surgeries Cancelled, state of emergency declared
California - set up tents outside, patients in hallways
Pennsylvania - Surge tents
https://english.elpais.com/society/2020-04-07/spains-intensi...
It discusses one of the hardest hit hospitals. However the absolute numbers were small and they never turned people away.
This sort of bed conversion is known to happen even in normal years, so it doesn't mean much by itself. Dramatic language can be misleading. Unfortunately it is standard for health officials to describe hospitals as "overloaded" or "at breaking point" simply due to seasonal flu outbreaks, as in these articles from 2017:
https://www.thelocal.fr/20170111/french-hospitals-stretched-...
https://www.euronews.com/2017/01/12/struggling-to-care-hospi...
Not a direct acquaintance, but a friend of my sister was two days siting in the hall of the Gregorio Marañon until they could transfer him to IFEMA. Almost no supply of food during these two days, and he was lucky to have a seat, many people lying on the floor.
They found many bodies of people dead by COVID-19 at home. They found some bodies on the streets.
I don't get how can you pretend that many hospitals / regions were "overload".
It's a debatable question whether this shutdown of hospitals was due to the virus, or due to the over-reaction to it. Other places where the virus started later didn't do this to the same extent (although the UK did and is still doing so!), and they saw less serious problems.
As for "many bodies of people dead at home/on the streets", can you show me reports of people dropping dead of COVID on the streets? I never heard that, it seems it hasn't happened elsewhere and sounds suspect.
Remember that basically all reports about people dying "of" COVID are garbage. The average age of death when testing positive is over the average life expectancy in most places (maybe all, I haven't checked). Almost all such reports are of deaths that were naturally happening anyway due to age or other serious health conditions, and COVID was just co-present at time of death - maybe it pushed them over by a little bit, but probably only by months. Correlation/causation mixups are a huge problem with COVID datasets.
NZ went for elimination from the outset so when the virus came back in Auckland several weeks ago it was a no-brainer to immediately lock down again (although now they seem to have shifted to a suppression strategy, let's see how that goes for them...).
Sweden went for a flatten the curve(ish) strategy which meant that they did not automatically enact a lockdown when things started heating up in terms of case numbers/deaths because they were confident enough at the time that their health care system would cope.
Those are two very different strategies with different outcomes but they were consistent and thereby achieved their respective goals.
Victoria (and Australia as a whole) has gone from flatten the curve to suppression and now to elimination. If Victoria had chosen elimination after the first flare up back at the end of May, then that would have most probably been achieved by now.
It really does not make much sense to unnecessarily restrict the times when people can, e.g., go out and buy groceries. The wider the allowed hours, the less density of people there will be in those indoor places, which will help decrease the spreading of the virus.
Probably not much. But that's because you used the word "doing". If you had asked "what should Victoria have done instead?", then there is a long list.
To pick on one thing, I was amazed press were showing people in the locked down towers apparently depending on charities for essential supplies. To this day don't know if it was a beat up or real, but if real it boggles the mind. It implies the lock down was little more than a thought bubble with almost no effort put into planning.
Obviously, they did eventually react to the collapse of contract tracing, the explosion of cases, the outbreak in nursing homes and so on, and as a consequence everything seems to be as under control as it can be now. But it does seem to all be reactive, not proactive.
I do wonder how the situation arose. At one level it's obviously a reflection of competence of the bureaucracy, as this is where the pollies (who usually have very little expertise in their portfolio) get their advice. But those same pollies have been there for 10 years and so they should by now have made their stamp on the culture of the bureaucracy. Frankly when you compare it's performance with bureaucracies in all other states, it was very poor. For me (a Queenslander) the outstanding state was NSW the Ruby Princess cluster fuck notwithstanding.
Even the second wave isn't anywhere close to being as large as what Europe/NYC had but is largely confined to aged care homes.
Coronavirus quickly found its way into aged care facilities, causing a higher death rate. But as the virus progresses through the wider community the death rate declines.
Still doesn't make sense though. Pretty much everyone is inside all day either due to work or the weather being shite, and even if you do go outside you probably won't have much exposed skin due to the weather being shite, and even if you did the sun is low in the sky due to it being winter and...
Is that any clearer? :D
counter-intuitive as it may sound today, US might just end up the country that did really well. Most large countries are simply not measuring/admitting the real number of cases.
If we don't get vaccine then sure all countries might eventually end up the same, but Europe is largely back to normal living with kids back at school with almost no cases. In the US we still have lockdowns and no control at all.
So, would it be true if you looked at recorded deaths? After all, at the beginning of the pandemic they were expecting millions of deaths in the US.
With updated information, we can narrow the expectations between the most optimistic and pessimistic models, but recorded deaths will always be a lagging indicator. As of right now, the fivethirtyeight summary (https://projects.fivethirtyeight.com/covid-forecasts) has a spread in the US between 231,000 Americans dead by Oct. 17 (IHME) and 205,000 dead by Oct 17 (Los Alamos). What has changed since the disease started is the death curve has gone from exponential to linear (thank goodness), which is likely due to public health controls having an effect (we can guess this because the curve linearized around mid-April, which is about a month after California began treating the disease as an emergency and 2 weeks after New York followed suit). As it stands, it'd take over a decade to reach a million US deaths, assuming nothing changes (i.e. assuming people continue to avoid unnecessary contact and travel and protect their respiration); had the curve stayed exponential, it would have taken under a year.
The disease is 99+% survivable with optimal medical care during the worst phase of it and significantly less survivable without it.
All the excess hospital beds built at the height of the hysteria went unused.
Italy got saturated, and the outcome was tragic.
https://www.advisory.com/daily-briefing/2020/03/19/italian-h...
Most countries have twice as many cases now than at their peak in Spring and the trend is accelerating. As for most of Latin America, they are just not reporting the numbers because they are too poor to test.
Sky high death rate? Not even close. The worst hit countries, deaths per population are the European ones. Again, that is not a reflection on the societies, just perhaps their age distribution and other factors.
That the US is doing really badly is just propaganda fueled by the imminent election. Again, it is normal, election propaganda is anything but fair.
US is actually doing well overall.
To put it in context, "twice as many cases than in spring" can still be per capita 10 times smaller number than in USA.
> US is actually doing well overall.
Yeah, if the number of deaths doubles, USA can be number one! Wait, that is actually not a good thing...
If having 1 in 1730 people die is such a huge success, I suppose having 1 in 1690 die is okay, too.
(To avoid misunderstanding, no, I don't think any of these numbers is okay. Many developed countries have an order of magnitude better results.)
How does it happen on a molecular level that PCR delivers a false positive? Are the primers sometimes broken (matching not exactly what they're supposed to match)?
I'm not sure it really is. Take it with a grain of salt for now. I feel like there's a missing piece of the puzzle here.
A false positive rate that high doesn't pass the sniff test.
[1]https://ourworldindata.org/coronavirus-testing [2]https://www.nytimes.com/2020/05/26/world/asia/coronavirus-wu...
Different tests are used in different jurisdictions and at different times.
"The high specificities (usually 100%) reported in PCR-based tests for SARS-CoV-2 infection do not represent the real-world use of these tests, where contamination and human error produce significant rates of false positives."
New York reports positivity rate below 1% for a while now, so false positive rate cannot be 2.3%.
[1] https://www.fda.gov/medical-devices/coronavirus-disease-2019...
Combine that with [1] which makes a good argument that some high Ct levels may be too sensitive.
Just randomly looking, this test[2] approved in June uses the Ct of 40 which is criticised above.
[1] https://www.advisory.com/daily-briefing/2020/09/01/covid-tes...
The PCR test can produce high numbers of false positives. It depends on a variable called the "cycle threshold" (Ct), which is the number of times amplification is run.
Different tests have different Ct numbers, so some specific tests are overly sensitive. However there is no data on what test is used where, or when tests were changed.
https://www.advisory.com/daily-briefing/2020/09/01/covid-tes...
This article doesn't even deal with SARS-CoV-2, so until it gets peer reviewed and, more importantly, replicated, it should be treated as an extraordinary claim that requires extraordinary evidence.
Don't they have access to this data? How's that a speculation and not a plot?
One thing the article briefly mentioned but didn't really dig into (IMO) is that the peak of 5,451 cases on April 5th is basically a meaningless number and that it is important to try to figure out what the real number should have been.
On April 5th, the UK was only doing 16,000 tests a day and had a nearly 40% positive rate for tests. Only very sick people were being tested. That implies that the 5,451 cases detected that day is a vast undercount of the actual number of new cases at that point. It is bad data science to keep reporting that peak case number in comparison with the current case numbers as if it means anything.
So how many new cases were there on April 5th? No one knows for sure, but various estimates based on community surveys guess that it was more like 100,000/cases per day. That would be a very different graph than what gets attached to every news story.
Compare that with now, where the UK is doing ~200k tests a day (over 10x!). We also have much better community survey data now and can estimate that there are about 3,200/cases a day right now. The daily testing is picking up the majority of those expected cases.
So if you actually compare numbers that are comparable (~100k cases/~1000 deaths with ~3k cases/~10 deaths), you get a much better idea of what is actually going on. Demographics are definitely working in our favor now, which keeps death rates lower. But it's not like we have "solved COVID treatment" and can cure everyone now because we know to use steroids. It's mostly that there just aren't nearly as many people getting it right now as there were at the peak. Even if tomorrow we detected 5,451 cases again, there's no reason to expect that the death rate should approach the peak because we are getting much closer at detecting all the sick people than before.
The problem is that the test's sensitivity has been amped up to such a huge level that labs are reporting positive for people who have virtually no virus in their blood, or actually no viable virus at all, and certainly are not infectious let alone at risk.
Fortunately the British government in the last few weeks finally understood that RT-PCR tests do in fact have false positives, contrary to what was being regularly claimed back in April. They changed their guidance on September 6th. There's an analysis of this by a scientist here:
https://lockdownsceptics.org/when-is-covid-19-not-covid-19/
A useful quote is this one:
The number of cycles is not actually specified in the publication. Instead each laboratory must determine their own. A beautiful French study demonstrated the relationship between the number of cycles and the chance that a sample will be from an infectious case. Above 30 cycles and the chances of a test being from an infectious case are only 50/50. Above 34 cycles they are all positive. Another laboratory may find a different cut off. Indeed, a Canadian study found no cases requiring more than 24 cycles were infectious.
To put it in perspective, COVID testing labs have routinely been reporting positive at 40 cycles.
The first thing they do now in the hospital is steroids, they learned after NY.
In the UK they had the Oxford study
https://www.ox.ac.uk/news/2020-06-16-dexamethasone-reduces-d...
> The PCR test amplifies genetic matter from the virus in cycles; the fewer cycles required, the greater the amount of virus, or viral load, in the sample. The greater the viral load, the more likely the patient is to be contagious. This number of amplification cycles needed to find the virus, called the cycle threshold, is never included in the results sent to doctors and coronavirus patients, although it could tell them how infectious the patients are. In three sets of testing data that include cycle thresholds, compiled by officials in Massachusetts, New York and Nevada, up to 90 percent of people testing positive carried barely any virus, a review by The Times found.
> ... One solution would be to adjust the cycle threshold used now to decide that a patient is infected. Most tests set the limit at 40, a few at 37. This means that you are positive for the coronavirus if the test process required up to 40 cycles, or 37, to detect the virus. Tests with thresholds so high may detect not just live virus but also genetic fragments, leftovers from infection that pose no particular risk — akin to finding a hair in a room long after a person has left, Dr. Mina said. Any test with a cycle threshold above 35 is too sensitive, agreed Juliet Morrison, a virologist at the University of California, Riverside. “I’m shocked that people would think that 40 could represent a positive,” she said. A more reasonable cutoff would be 30 to 35, she added. Dr. Mina said he would set the figure at 30, or even less. Those changes would mean the amount of genetic material in a patient’s sample would have to be 100-fold to 1,000-fold that of the current standard for the test to return a positive result — at least, one worth acting on.
Every published "case" should include the PCR cycle threshold to enable statistical analysis.
Maybe the global cycle count for the machine could be adjusted, similar to what you are talking about, but that is different than reporting the cycle count of every positive test.
Without the Ct value, "cases" are not comparable on the basis of test positivity.
With transparency on the Ct value, we can determine which tests and configurations best support health.
P.S. "the machine does not allow it" could be an HN firmware challenge. If the fate of civilization depends on PCR test machines, do any of them have auditable open-source firmware?
There's a rumor that it has a high false positive rate as well. There was a New York Times article that summarized this a few days ago. Again, perplexing why this isn't mentioned and studied more.
Pregnancy tests should return a binary result. Pretty much every other test requires a quantity for context. Imagine a blood-alcohol test that can say yes, alcohol is present, but is unable to distinguish between ingesting a teaspoon of cough syrup vs. drinking a six-pack.
Okay fine, let's say Reuters is correct and Mullis never said whatever quote some randoms on Facebook are trying to say he said. Here's a research paper pointing out everything wrong with the PCR test:
http://theinfectiousmyth.com/book/CoronavirusPanic.pdf
Let me know what you think.
https://davidcrowe.ca/cnp-wireless.com/dcroweresumelib.php
Holy shit, of course that nutjob is also an AIDS truther:
https://www.davidcrowe.ca/SciHealthEnv/alive-aids-stats.html
And still was in 2014! (Ctrl + F “David Crowe” in the comments):
https://retractionwatch.com/2014/09/26/publisher-issues-stat...
Find better role models.
Mullis talking about his experience: https://www.youtube.com/watch?v=vaMZ4NyNCwI
Questioning known corrupt organizations like the FDA, CDC and WHO makes me feel better, not worse about Mullis and Crowe. It's the scientists who blindly follow authority who really make me nervous. But that's just me. Sounds like you might be in the opposite camp.
I've looked through your link and saw Crowe in the comments section. He mentions there are two new hypotheses in 2014, hence why its still being discussed. They really have no answer for his questions besides "move on, the science is settled". But critically look at his points, maybe you can address them. BTW, anyone who ever tries to to tell you "the science is settled" is trying to shut down debate, as Crowe correctly recognizes.
Any comments on the actual paper itself that Crowe wrote? You don't need a background in virology to figure out that there's giant issues with the PCR test. If you read the paper at all you'd see that, but I'm guessing you didn't.
There is literally no benefit to engaging with these charlatans or their half baked ideas.
Have you ever run a PCR? It's not magic and none of the arguments by these bizarre COVID truthers hold any water when there are thousands of people using them in research every single day.
Mullis also has said that HIV does not cause AIDS. While I'd look at his argument, I wouldn't give his opinion all that much weight just because he invented PCR.
TL;DR: Some (many?) PCR tests are using too high a cycle threshold, which makes them too sensitive. Key quote:
Juliet Morrison, a virologist at the University of California-Riverside, said she believes any test with a cycle threshold over 35 is too sensitive. "I'm shocked that people would think that 40 could represent a positive," she said.
The following is my commentary, and not specifically in the article above:
There were many early tests that were giving false negatives. It looks to me like test manufactures over-compensated to make sure they never give false negatives. There is no data source that I can find that shows what test is used in what area, or what CT is used for what test.
Research scientists and clinical scientists are worlds apart, and have very different goals in life.
I wouldn't trust a cT coming out of any research lab either, but clinical labs are far far more controlled and have far better processes, and have intense validation that shows that their threshold is repeatable, accurate, and a true representation of their limit of detection.
No research lab does any of this, and they almost never have extremely basic contamination protections like separate rooms for pre- and post-amplification rooms.
I've watched research scientists try to stand up clinical labs during this pandemic, and it has been an education for them to bring their standards up to what is the baseline for clinical testing. Its not unlike giving a butcher a scalpel and expecting brain surgery: there are a lot of the same skills involved but also very different and extremely narrow it's of knowledge.
Can you explain to the layperson why it's "basically bullshit"? The NYT article I linked describes a real-world scenario where a fake outbreak (100% of cases were false positives) actually occurred (note: I am not claiming Covid-19 is fake).
Also, specific false positive rates aside, is it not likely we're now approaching a rate of "cases" which is hard to distinguish from false positive tests, which would help explain the drop in hospitalization / ICU / mortality?
> Many of the new molecular tests are quick but technically demanding, and each laboratory may do them in its own way. These tests, called “home brews,” are not commercially available, and there are no good estimates of their error rates.
The technology, as mentioned, was new at the time and not even commercially available. There have been 13 years of improvement since then.
Interesting weasel-words and cherry-picking. First, comparing a quarter of a year of Covid deaths against a whole year (or two?) of normal flu, and then subtly shifting between deaths from Covid and deaths during a flu wave (so not caused by the flu?).
For a more accurate comparison: "between 291,000 and 646,000 people worldwide die from seasonal influenza-related respiratory illnesses each year"[0] and 907,917 have died from Covid so far this year[1], despite all the extra measures taken to limit its spread and mortality rate.
[0] https://www.cdc.gov/media/releases/2017/p1213-flu-death-esti...
The excess deaths statistics [1] give lie to the tired claim that these were all people who "would have died anyway." 200,000+ more people have died this year in the US alone than normal, and it's very statistically-significant, particularly as the annual death rate is under 3 million.
1. https://www.sciencealert.com/2020-has-killed-up-to-200-000-e...
* https://twitter.com/lymanstoneky/status/1301975654771064834?...
* https://twitter.com/lymanstoneky/status/1301976643146317825?...
This suggests undiagnosed COVID is in fact the cause of most of the excess deaths.
> a whole year (or two?) of normal flu
Flu season is fall to spring, that range is (northern hemisphere) half a year. Both years are given because it started in 2017 and ended in 2018.