It is hard to know what to think at present. On the one hand, we have the expensively orchestrated flow of seemingly miraculously and marvelous news from the big pharmaceutical companies, eagerly pitching their vaccines through the press to the FDA. On the other hand, we’re setting new records for daily new case and daily death rates, and we’re told rates will get very much worse as the month progresses.
So what is it? The light at the end of the tunnel? Is it sunny daylight awaiting our emergence, or is it an oncoming express train?
No-one yet knows. But what we do know is the drug companies are not telling us the complete story about their vaccines or how successful they truly are.
We’ve seen claims of around 95% effectiveness, which certainly sounds brilliantly encouraging. But we’re never told the range of possible measures that it could be. For example, let’s think about something we understand – if you roll a dice 18 times and a six doesn’t come up on any of the 18 times, the chances of that happening is 3.76%. Say someone has perfected a special way of rolling a dice so a six never appears, and then rolls the dice 18 times with no six appearing. We could say we are 96.24% certain that his method works.
But what would have happened if he rolled the dice 18 times and one time a six appeared? All of a sudden, the odds of that have dropped (I think down to about 80%, but I’m not certain). What say the 19th time and a six appears – again, the overall odds shift to a less significant number – probably also around 80% (in theory, you’d expect three sixes to appear, going from zero to one is a big shift in the odds).
So while the statistic “96.24%” seems very exact and very persuasive, it needs to also tell us what would happen if a six did appear (which it could and might) and how much of an impact that would happen on the odds.
The drug companies are giving us the 96.24% statistic, but they’re not telling us about the range of possible outcomes within which that 96.24% number falls.
As a clear example of this, I saw Moderna say their vaccine is 100% effective in preventing severe virus cases. Any statistician, when confronted with a confident statement of “100% effective”, and a very small sample size, immediately knows, without needing to even look at the numbers, that they are being sold a dose of snake oil.
Moderna based their claim on a mere 196 cases of Covid-19 occurring among their study participants (so far…..). 185 were among test subjects who received the placebo, and the other 11 were among test subjects who received the actual vaccine.
The first thing you notice is that out of the tens of thousands of test subjects, we’re basing the vaccine effectiveness on only 196 cases appearing. All the numbers – 185 placebo cases and 11 vaccinated cases – are ridiculously low, as is the little-more-than-two-month measurement time. Wouldn’t you like to know how effective the vaccine is at three and four months, and longer, too?
Now let’s look at the 100% effective claim.
There were 30 “severe” cases (a somewhat subjective claim which also needs to be balanced not only against whether the severely affected people were vaccinated but also by their age and other factors too). All of them were in the 185 placebo subjects.
So, extremely simplistically, a first grader would say “30 cases in the placebo subjects, none in the vaccinated subjects, therefore 100% effective”.
But anyone else would say “One in every six of the placebo subjects had a severe case of the virus. But there were only 11 virus cases among the vaccinated subjects. We’d only expect 1 or 2 of them to have severe cases. Going from one or two expected cases down to zero observed cases, so far, is as likely to be chance as it is a proof of 100% effectiveness.”
In reality, having no severe cases in 11 cases would happen 14.3% of the time just by random chance. It is almost exactly the same as rolling a dice 11 times and having no sixes appear. We can only be 85.7% certain that the no cases is significant rather than random, and the normal standard for deeming if something is significant or random is three times higher – 95%/5% instead of 86%/14%.
Bottom line – AstraZenica’s claim of 100% effectiveness is nonsense, for several reasons. No self-respecting statistician would ever say that, without hastily adding a bunch of disclaimers and confidence interval data.
One more thing. None of these vaccine studies have been properly “double blinded” with the test subjects not knowing if they’d been given the vaccine or a placebo. Almost all the test subjects who received the real vaccine knew that, for the simple reason that they had two sets of moderately strong reactions to the injections, which the placebo-receiving test subjects did not experience.
This in itself weakens the entire results of the testing. It doesn’t invalidate them, but it means that “best practices” have unavoidably not been observed.
There’s also another fascinating and fearsome point, hinted at in this article. Quite apart from the main thrust of the story, about how the antibody protection from a previous Covid infection (and possibly from a vaccine) might be short-lived rather than long-lasting, there’s another point that has not yet been fully aired in the media.
He said: “We need a vaccine that can be used multiple times, a recombinant vaccine will not suit. “Once injected with an adenoviral vector-based vaccine, we won’t be able to repeat it because the immunity against the adenoviral carrier will keep interfering.”
Are these modern brand-new types of vaccines limited in terms of how often they can be given to us? This is a matter little discussed, but mentioned in passing and then quickly ignored. For example, when explaining how the AstraZenica vaccine was accidentally discovered to work better if test subjects were first given a half dose and then in their second dose given a full dose, it was mentioned this seemed to work better because that way our bodies weren’t as strongly responding to and fighting against the vaccine itself the second time around.
This is an issue we need to see a lot more exploration on and explanation about. What level of tragedy would it be if we all rushed off to get one of these new types of vaccines, and then discovered that it was short lived and because we’d already had it once, we couldn’t have it again?
I’ve plenty of objections to our rushed testing of these vaccines, and while there are definitely concerns about not leaving enough time for negative side-effects to appear, an equal or bigger concern is we’re not waiting long enough to see how long-lasting the vaccine protection may be. Yes, I know we can do antibody testing to see what level of antibodies remain in vaccinated people’s blood, but keep in mind we’re still not exactly sure how/what antibody process it is that is most important and effective at fighting the Covid virus. Which antibody levels do we monitor? And what are the necessary minimum levels to give a person a high degree of protection?
So many unknowns…..
There were a couple of US state swaps in both the cases and deaths columns.
There were some minor swaps in the minor country list. In the major country list, the Czech Republic barely pushed past Belgium into first place, and Italy reappeared after a long absence from the list.
France reappeared in ninth position in the death rate list.
On Sunday I’ll be able to match the statistics for Sunday with those shown last Sunday.
US Best and Worst States
|Last time||Now||Last time||Now|
|1 Best||VT (6,571)||VT (7,439)||VT (107)||VT (120)|
|5||OR||OR (18,800)||OR||OR (231)|
|51 Worst||ND (100,217)||ND (106,428)||NJ (1,928)||NJ (1,953)|
Top Case Rates Minor Countries (cases per million)
|Rank||One Week Ago||Today|
|6||French Polynesia||San Marino|
|10||French Guiana||Panama (39,421)|
Top Case Rates Major Countries (cases per million)
|Rank||One Week Ago||Today|
|1||Belgium||Czech Republic (50,167)|
Top Death Rate Major Countries (deaths per million)
|Rank||One Week Ago||Today|
I Am Not a Doctor, But….
Britain has “won the race” to be the first major western country to officially approve a vaccine. Slightly surprisingly, they approved the Pfizer rather than the “home grown” AstraZeneca/Oxford vaccine, but we expect they’ll probably be approving the AstraZeneca vaccine very soon, too.
But is this really a point of pride to be the first country to rush through a vaccine approval? Perhaps not. On the other hand, I’m not sure we can be proud that the FDA doesn’t even meet to consider their first vaccine approval request until 10 December.
Talking about speed and timings, there has long been a totally perplexing mystery. There are credible reports that the virus was active in the US in mid-December last year, and in Italy way back in September 2019.
I’m not disputing these claims at all. But I’m puzzled to the point of risking my head exploding as to their implications. If the virus was active over a year ago, why did the numbers not explode exponentially back then? We’ve seen how the virus can grow, even with masks and social distancing and bars/restaurants shut, and all the other protections in place. How is it the virus did nothing, while we were totally unprotected, for three months in the US and almost six months in Italy?
That is totally impossible. Was it a totally different strain that subsequently mutated to become much more severe and much more readily passed on? If that is the case, surely the reports would note that the earlier samples were of a different strain, and that’s never been said.
We’ve now at a point of 3,000 people dying every day in the US – two every minute. Hospitals are stressed as bad as they were earlier in the year, etc etc etc. Why did none of this happen before?
The other question has to be – why am I the only one raising this major question?
Talking about Italy, here’s a fascinating story about how their mistakes and political considerations and stupidity and delays caused the virus to run away with them in Bergamo in March (and subsequently, all of Italy). But when you put this story alongside the claim that the virus was not only in Italy in September, but also seemingly widespread back then, why weren’t people dying everywhere prior to March?
Here’s a credible explanation for one reason why some people suffer extended ill affects after a virus infection. There are other reasons too.
Here’s an interesting idea on how hotels are now starting to boast about the efforts they have undertaken to ensure the air quality in their buildings is relatively virus free. It is certainly extremely important that air quality is optimized – much more so than needless cleaning of exposed surfaces. But we, as potential hotel guests, are then placed in the awkward position of having to accept at face value the claims of hotels in terms of what they have done.
These are the same hotels that consistently lie to me (and to you) about why their air conditioning isn’t working. I’m not at all inclined to believe a word they say.
Yet again WHO shows itself to be stunningly behind the curve. They’ve just now made the discovery that a face shield is not as effective as a face mask. The rest of us knew that instinctively, simply by looking at face shields. Why is WHO always so late to acknowledge the most obvious facts?
Timings And Numbers
My “go-to” site for new case growth rates is again missing some days of reporting. I do hope this isn’t a precursor to closing down entirely.
After seeing 13 states with shrinking new case rates on Sunday, that number held steady on Monday, then reduced to 12 states on Tuesday. We had no data on Wednesday, and today it was down to only ten cases with shrinking new case rates.
As you can see, Oregon remains an outlier.
I continue to feel that rt.live’s “line of best fit” is exaggerating Oregon’s case rate growth, with what seem to be two anomalous results and some missing data, and if I were drawing the curve I’d have it not nearly so exaggerated. Maybe a correction will kick in soon – we’ll see.
Here’s an interesting article that suggests the current US count of 283,00 deaths might be greatly underestimated. Based on total death numbers, the CDC suggests that as of a week or so back, total Covid deaths might actually be closer to 400,000.
Logic? What Logic?
Some people think they can declare themselves exempt from public health measures to control the virus spread, but the virus is implacable and ignores all their posturing.
So we’re not unhappy to see the bar owner who refused to obey NYC restrictions and announced his bar was an “autonomous zone” has now been arrested by the police. He is part of the reason we’ve had possibly 400,000 people die.
Until a few months ago, New Zealand published fascinating data every day showing how long in quarantine people were before being detected with a virus infection. I noticed, with alarm, that several times, people were reaching 12 or 13 days before being detected as having an infection, and worried if 14 days might be too short a quarantine time. Certainly, studies have shown that a small percentage of cases have a longer than 14 day incubation period, and it was seeming to me, based on the NZ data, that this small percentage might have been larger than believed.
The CDC announced earlier this week that it was shortening the quarantine period – down to seven days for people with a negative virus test, or ten days for untested people.
I’ve no objection to the conditional seven day quarantine based on multiple clear tests, but the change from fourteen to ten days for the “no test” period seems very ill-advised.
The CDC says there is a remaining 1% chance of the virus appearing after ten days. That number feels low to me. Of course, any sort of quarantine is not all that important at present – there’s more risk of getting the virus from your neighbor or co-worker than there probably is from someone coming into your community from outside, but if we’re going to get serious about stemming the flow of new cases into the country or regions within the country, even a 1% risk causes measurable harm.
Please stay happy and healthy; all going well, I’ll be back again on Sunday.