All things political. Coronavirus Edition. (15 Viewers)

A second tweet about how what some folks are pushing is misleading data by leaving out some critical information:

There’s not much about this whole craziness about the vaccine that truly upsets me as much as the demonization of Dr. Fauci. Based on lies and misinformation.

‘Fauci has been a doctor and public servant for more than 50 years. He’s been the country’s top expert on infectious diseases under seven U.S. presidents. George H.W. Bush once called him his personal hero. Under George W. Bush,Fauci became an architect of an AIDS-relief program that has, according to the U.S. government, saved 21 million lives around the world.

He knows how a virus works. He knows how Washington works. He thought he knew how people worked, too — even ones who called him a murderer, as AIDS activists did decades ago because they felt left for dead by a neglectful government. Back then the angry people were motivated by truth and science. Fauci had something to learn from them, and they had something to learn from him. The shared mission was pursuing facts and saving lives. Fear and uncertainty could be eased by data and collaboration. Combatants, however scared or passionate, shared a reality.

Now?

“There is no truth,” Fauci says, for effect. “There is no fact.” People believe hydroxychloroquine works because an Internet charlatan claims it does. People believe the 2020 election was stolen because a former president says so. People believe that Fauci killed millions of people for the good of his stock portfolio because it’s implied by TV pundits, Internet trolls and even elected leaders. Fauci is unnerved by “the almost incomprehensible culture of lies” that has spread among the populace, infected major organs of the government, manifested as ghastly threats against him and his family. His office staff, normally focused on communicating science to the public, has been conscripted into skirmishes over conspiracy theories and misinformation.’

Seriously what the hell is this? Even if you disagree with the mandates and rules, if you can't go to court because you test positive for coronavirus, you don't go out to eat . . . multiple times. If you know you have the flu and just go out and carry on with people, you're an butt crevasse. If you know you have an active coronavirus infection and do it, you're an even bigger butt crevasse.

The woman is dumber than a bag of hammers so it's no great surprise.

Okay, found this which might explain the article Farb saw. I think it’s fairly self-explanatory but if not there’s more posts about this subject.

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The base rate fallacy in this instance applies because it gives the impression that vaccinated people are being infected at the same rate as unvaccinated without taking in account the much larger pool of vaccinated people by comparison.

And then as a double whammy, the base rate bites again because of the low incidence testing paradox. Most likely half or more than half of the vaccinated people are testing with false positives, so even the impression that a almost equal in number of people testing positive is in error, further eroding the stories that Farb has been talking to us about, without showing a source.

This is a Wikipedia quote about the general base rate fallacy. The base rate fallacy is a formal fallacy, which means when it applies the information which was rate neglected is always wrong.

The base rate fallacy, also called base rate neglect[1] or base rate bias, is a type of fallacy. If presented with related base rate information (i.e., general information on prevalence) and specific information (i.e., information pertaining only to a specific case), people tend to ignore the base rate in favor of the individuating information, rather than correctly integrating the two.[2]

Base rate neglect is a specific form of the more general extension neglect.

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This is a quote from the same page giving information about the double whammy.

An example of the base rate fallacy is the false positive paradox. This paradox describes situations where there are more false positive test results than true positives. For example, if a facial recognition camera can identify wanted criminals 99% accurately, but analyzes 10,000 people a day, the high accuracy is outweighed by the number of tests, and the program's list of criminals will likely have far more false positives than true. The probability of a positive test result is determined not only by the accuracy of the test but also by the characteristics of the sampled population.[3] When the prevalence, the proportion of those who have a given condition, is lower than the test's false positive rate, even tests that have a very low chance of giving a false positive in an individual case will give more false than true positives overall.[4] The paradox surprises most people.[5]

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Here's where it specifically talks about the double whammy situation that is involved here:

It is especially counter-intuitive when interpreting a positive result in a test on a low-prevalence population after having dealt with positive results drawn from a high-prevalence population.[4] If the false positive rate of the test is higher than the proportion of the new population with the condition, then a test administrator whose experience has been drawn from testing in a high-prevalence population may conclude from experience that a positive test result usually indicates a positive subject, when in fact a false positive is far more likely to have occurred.

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Here's an example of the paradox playing out in the situation that Farb has been talking about:

Example 1: Disease[edit]​

High-incidence population[edit]​

Imagine running an infectious disease test on a population A of 1000 persons, in which 40% are infected. The test has a false positive rate of 5% (0.05) and no false negative rate. The expected outcome of the 1000 tests on population A would be:

Infected and test indicates disease (true positive)1000 × 40/100 = 400 people would receive a true positiveUninfected and test indicates disease (false positive)1000 × 100 – 40/100 × 0.05 = 30 people would receive a false positiveThe remaining 570 tests are correctly negative.
So, in population A, a person receiving a positive test could be over 93% confident (400/30 + 400) that it correctly indicates infection.

Low-incidence population[edit]​

Now consider the same test applied to population B, in which only 2% is infected. The expected outcome of 1000 tests on population B would be:

Infected and test indicates disease (true positive)1000 × 2/100 = 20 people would receive a true positiveUninfected and test indicates disease (false positive)1000 × 100 – 2/100 × 0.05 = 49 people would receive a false positiveThe remaining 931 (= 1000 - (49 + 20)) tests are correctly negative.
In population B, only 20 of the 69 total people with a positive test result are actually infected. So, the probability of actually being infected after one is told that one is infected is only 29% (20/20 + 49) for a test that otherwise appears to be "95% accurate".

A tester with experience of group A might find it a paradox that in group B, a result that had usually correctly indicated infection is now usually a false positive. The confusion of the posterior probability of infection with the prior probability of receiving a false positive is a natural error after receiving a health-threatening test result.

MT15 said:

So your tweet doesn’t have a link, or really even any context at all as to the number of people that were tested to yield that level of cases.

Also, since testing is my thing, I’m going to get into the weeds a bit. If they are using PCR testing, and testing asymptomatic people, there’s a chance they are catching vaccinated people who have been exposed, thus having the virus in their nose, but are not strictly infected. The virus isn’t replicating in them and they will not actually come down with the disease.

PCR testing is very sensitive - the incubation period is designed to let any viral particles replicate in the test media. So almost any viral particles at all will be detected by the test. The pathologists and infectious disease docs have had conversations about this effect.

I heard one doc say he thought we needed new terminology because people are showing up with detectable viral particles without truly being infected. Most labs haven’t done thus type of PCR testing which is capable of detecting such small amounts of virus for other viral illnesses. So we don’t normally see these types of positive results.

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I went to click through to the tweet to see if it was part of a thread, and accidentally clicked through to that guy's feed, and wow, that guy is a clown.

That's not an argument - there isn't really anything there that's worth the time - just an observation.

Anyway, as far as Israel goes, I don't think the increase is a result of increased testing, because it appears the positivity rate is also really high. Those are most likely genuine cases, but the problem is that some people (not you @MT15 !) seem incapable of comprehending that two things can be true:

1) A vaccine can be effective.
2) A sufficiently transmissible virus can still maintain exponential growth in the presence of an effective vaccine and in the absence of sufficient other measures to limit spread.

We know the vaccine is effective, because we can compare outcomes between vaccinated and unvaccinated individuals, both in trials and through ongoing surveillance, and between households with systematic large-scale surveys such as that carried out by the ONS in the UK.

We also know that Omicron is incredibly transmissible. For a vaccine to prevent exponential growth of a virus by itself, it has to be sufficiently effective against infection and transmission and enough of the population has to have had that vaccine to bring the reproduction rate of that virus down to the point that it can no longer maintain growth. The more transmissible the virus, the higher that bar.

So for example, for measles, we have an incredibly effective vaccine (95%+), but we also need extremely high population coverage (~95%) to prevent outbreaks, because measles is a highly transmissible virus.

For Omicron, which is also a highly transmissible virus, while our current vaccines can be effective against transmission and infection, they're not effective enough to clear that bar by themselves, and population coverage is also not as good as some people seem to think it is. E.g. the aforementioned clown presented Israel as '90% of the adult population has received 2 vaccine doses, 80% have received 3 doses, and over 500,000 Israelis have received 4 doses—which the government is now pushing for all adults.' Sounds great? In reality, just 67% of their population has had 2 doses, and 56% an additional dose. Israel's vaccination programme started off strong, but they hit a lot of vaccine refusal, so they actually only have similar coverage to the USA (64%). Also, pretending children don't exist is a weird - and wrong - way to approach vaccination population coverage.

So we have an effective vaccine, but it's not effective enough against infection and transmission in the presence of a highly transmissible variant like Omicron to prevent growth, and we don't typically have the population coverage we'd need either.

So we'd need additional measures to prevent exponential growth. Otherwise we'll see continuing waves.

But the vaccine effectiveness against severe illness is higher, and against death higher still.

And it's that which has led the governments of some countries to go, "Meh, good enough," cut public health measures to varying degrees (such as reducing isolation requirements, lifting mask mandates, and limiting isolation of contacts, for example, letting children from infected households attend school), and essentially let it rip. Israel, and the UK (71% vaccinated with at least 2 doses), are a couple of examples of that.

They're relying on vaccination being sufficient to limit the strain on healthcare through hospitalisation, to limit deaths, and, well, they're basically just hoping there's no significant impact in terms of longer term healthcare implications, from things like long Covid. Personally, I think this is a bad idea.

The outcomes vary, as you'd expect given still differing public health measures, population behaviour, and vaccine coverage, but they're broadly what we'd expect: very high surges in cases, high but not as high surges in hospitalisation, and lower increases in deaths. But those are still significant increases; they're a lower proportion of cases, thanks to vaccine efficiency and coverage, but a lower proportion of a very large number can still be a very significant number.

And that's what's happening in Israel.

Rob, what did you think about the opinion that we either have reached or are about to reach endemic status? Personally, I was thinking once we have the antiviral pills readily available and as many people vaccinated as will do it, we can probably go forward treating this as similar to influenza. So not much more needs to be done - vaccinate 6 month-5 yo, have oral treatment for those who do catch it and are at high risk. Yearly or semi-yearly boosters for all who want them.

I need to have some hope that we are getting close to putting this behind us! Lol.

I’ve lost patience with those who refuse to be vaccinated. They have made their choice.

MT15 said:

Rob, what did you think about the opinion that we either have reached or are about to reach endemic status? Personally, I was thinking once we have the antiviral pills readily available and as many people vaccinated as will do it, we can probably go forward treating this as similar to influenza. So not much more needs to be done - vaccinate 6 month-5 yo, have oral treatment for those who do catch it and are at high risk. Yearly or semi-yearly boosters for all who want them.

I need to have some hope that we are getting close to putting this behind us! Lol.

I’ve lost patience with those who refuse to be vaccinated. They have made their choice.

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Good question. First, I don't think we're in a situation where firm predictions can be made, and I'm consequently skeptical about a lot of the predictions, particularly when some of the people making them have repeatedly done so and repeatedly been wrong.

That said, I don't think we're looking confidently at an endemic status at this point. But I'm seeing a lot of confusion about what 'endemic' means, some conflating it with mildness, and some with a virus just being always present, regardless of whether it fluctuates. Correctly, endemic refers to a steady presence, i.e. that on average each person infected will pass it on to one person. In the UK we're just three weeks removed from our largest peak (so far, the drop stopped following schools reopening and relaxing measures, so it may be starting to go back up again...) so it seems a bit premature to suggest we're about to go into a steady state.

Additionally, endemic diseases can definitely be deadly. Like malaria.

I saw a good article about this in Nature by Aris Katzourakis, a Professor of Evolution and Genomics at Oxford, a couple of days ago: https://www.nature.com/articles/d41586-022-00155-x

From what I can see, Covid seems likely to remain an epidemic disease for at least some time to come. Omicron, thankfully, seems substantially less likely to put people in the ICU, but it's so transmissible it's still a problem, and we still have a lot of uncertainty about it (vaccine and previous infection protection over time, the risk of reinfection, what its full range of possible damage is and the long-term implications of that, including the risk of long Covid both on initial infection and possible reinfection).

So, I don't think we can say it's about to reach endemic status, and I think it's premature to call Omicron mild. Milder, yes, but we just don't know enough about its impact in the medium to long term to call it mild. It feels longer, but we only saw Omicron less than three months ago!

And as I see it, the fundamental problem is that we're essentially aggressively rolling the dice on viral evolution. We've had multiple variants, there's no reason to think Omicron is the last significant one, we're allowing vast numbers of cases increasing the likely rate of further variants, and it is a gamble whether further variants will mutate to our benefit, or to our cost.

I appreciate that's pretty gloomy, but on the plus side, we do have effective vaccines, we're in a position to further improve, refine, and roll out vaccines faster than ever, and our ability to treat the disease should continue to improve as we learn more.

I just wish we could do that and take appropriate public health measures, like improving global vaccination rates, improving ventilation and filtration especially in venues like schools and workplaces, and keeping measures like high-quality mask wearing as appropriate (like on public transport during a wave).

MT15 said:

There is starting to be data about this, Farb. Natural immunity to Delta offers very little protection against Omicron. Sorry, I know that isn’t what you want to hear.

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Can you share that information. Does it proved the CDC was wrong on this:
https://www.lifesitenews.com/news/n...ral-immunity-stronger-than-covid-vaccination/

A new study released Wednesday by the U.S. Centers for Disease Control and Prevention (CDC) acknowledges what numerous independent studies have found over the past year: Natural immunity from prior COVID-19 infection provides stronger protection against the virus than the COVID vaccines.

The data from California and New York cases spanning May to November 2021 found that, while the vaccinated had lower rates of first-time infection by a factor of 6.2 in California and 4.5 in New York than the unvaccinated who had never before had COVID, the unvaccinated with natural immunity had infection rates 29 times lower in California and 4.7 times lower in New York. Those who had both vaccination and prior infection had lower rates still.

The report also showed that in California, the naturally-immune were less likely to be hospitalized (0.003%) than the vaccinated (0.007%). New York did not provide hospitalization data.

will probably not surprise anyone


NPR looked at deaths per 100,000 people in roughly 3,000 counties across the U.S. from May 2021, the point at which vaccinations widely became available. People living in counties that went 60% or higher for Trump in November 2020 had 2.73 times the death rates of those that went for Biden. Counties with an even higher share of the vote for Trump saw higher COVID-19 mortality rates.

In October, the reddest tenth of the country saw death rates that were six times higher than the bluest tenth, according to Charles Gaba, an independent health care analyst who's been tracking partisanship trends during the pandemic and helped to review NPR's methodology. Those numbers have dropped slightly in recent weeks, Gaba says: "It's back down to around 5.5 times higher."

Farb said:

Can you share that information. Does it proved the CDC was wrong on this:
https://www.lifesitenews.com/news/n...ral-immunity-stronger-than-covid-vaccination/

A new study released Wednesday by the U.S. Centers for Disease Control and Prevention (CDC) acknowledges what numerous independent studies have found over the past year: Natural immunity from prior COVID-19 infection provides stronger protection against the virus than the COVID vaccines.

The data from California and New York cases spanning May to November 2021 found that, while the vaccinated had lower rates of first-time infection by a factor of 6.2 in California and 4.5 in New York than the unvaccinated who had never before had COVID, the unvaccinated with natural immunity had infection rates 29 times lower in California and 4.7 times lower in New York. Those who had both vaccination and prior infection had lower rates still.

The report also showed that in California, the naturally-immune were less likely to be hospitalized (0.003%) than the vaccinated (0.007%). New York did not provide hospitalization data.

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I will look at the original data. You are reading an article about the data and I see a few things that are red flags for being possibly misleading. Also, due to the dates of the studies cited, you are most likely not looking at Omicron data.

@Farb - did you understand the base rate bias tweet I posted and explanation from Sam? That would be the answer as to why hospitalization data could be misleading in a highly vaccinated location.

Farb said:

Can you share that information. Does it proved the CDC was wrong on this:
https://www.lifesitenews.com/news/n...ral-immunity-stronger-than-covid-vaccination/

A new study released Wednesday by the U.S. Centers for Disease Control and Prevention (CDC) acknowledges what numerous independent studies have found over the past year: Natural immunity from prior COVID-19 infection provides stronger protection against the virus than the COVID vaccines.

The data from California and New York cases spanning May to November 2021 found that, while the vaccinated had lower rates of first-time infection by a factor of 6.2 in California and 4.5 in New York than the unvaccinated who had never before had COVID, the unvaccinated with natural immunity had infection rates 29 times lower in California and 4.7 times lower in New York. Those who had both vaccination and prior infection had lower rates still.

The report also showed that in California, the naturally-immune were less likely to be hospitalized (0.003%) than the vaccinated (0.007%). New York did not provide hospitalization data.

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Here is an article from late December in the UK. Omicron evades previous infection and two dose vaccine regimens. Which is why the CDC suddenly changed from only older and more at risk people need a booster to everyone needs a booster.

MT15 said:

I will look at the original data. You are reading an article about the data and I see a few things that are red flags for being possibly misleading. Also, due to the dates of the studies cited, you are most likely not looking at Omicron data.

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Here is the link to the original CDC data. https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e1.htm

As I suspected, the study was completed before Omicron began infecting people. The study concludes that the differences seen were probably due to waning immunity after the two shot regimen. Before Delta showed up, vaccinated people had lower case rates than previously infected individuals, but after Delta that reversed somewhat, with vaccinated people having more cases than previously infected people. But the difference was minimal, as the graph shows (I find it much easier to get the perspective in graph form). Their conclusion was that vaccination was by far the best option rather than actually getting Covid, simply due to the fact that you don’t have all the risks from getting the disease and the chances for Long Covid and other complications with the vaccine. Also, now that Omicron has made an appearance, it’s far safer to get a booster than to get Covid again to boost your antibodies.

Since it might be hard to read - the top heavy bold line is people who are unvaccinated with no previous infection. The heavy dashed line is vaccinated with no previous infection, the very light dashed line is unvaccinated with previous infection, and the last line is vaccinated with previous infection.

https://www.wsj.com/articles/the-hi...s-protests-fire-rehire-employment-11643214336

For most of last year, many of us called for the Centers for Disease Control and Prevention to release its data on reinfection rates, but the agency refused. Finally last week, the CDC released data from New York and California, which demonstrated natural immunity was 2.8 times as effective in preventing hospitalization and 3.3 to 4.7 times as effective in preventing Covid infection compared with vaccination.

Yet the CDC spun the report to fit its narrative, bannering the conclusion “vaccination remains the safest strategy.” It based this conclusion on the finding that hybrid immunity—the combination of prior infection and vaccination—was associated with a slightly lower risk of testing positive for Covid. But those with hybrid immunity had a similar low rate of hospitalization (3 per 10,000) to those with natural immunity alone. In other words, vaccinating people who had already had Covid didn’t significantly reduce the risk of hospitalization.

I found this interesting.

Farb said:

https://www.wsj.com/articles/the-hi...s-protests-fire-rehire-employment-11643214336

For most of last year, many of us called for the Centers for Disease Control and Prevention to release its data on reinfection rates, but the agency refused. Finally last week, the CDC released data from New York and California, which demonstrated natural immunity was 2.8 times as effective in preventing hospitalization and 3.3 to 4.7 times as effective in preventing Covid infection compared with vaccination.

Yet the CDC spun the report to fit its narrative, bannering the conclusion “vaccination remains the safest strategy.” It based this conclusion on the finding that hybrid immunity—the combination of prior infection and vaccination—was associated with a slightly lower risk of testing positive for Covid. But those with hybrid immunity had a similar low rate of hospitalization (3 per 10,000) to those with natural immunity alone. In other words, vaccinating people who had already had Covid didn’t significantly reduce the risk of hospitalization.

I found this interesting.

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Article is behind a paywall, but from what you've quoted there, it's misrepresenting the CDC study, rather than the CDC misrepresenting their own study.

It appears to disregard that the study did not find that vaccination isn't more effective than natural immunity. Because, first, in as much as the data can provide indicative comparisons between groups (and see below on that), it indicated that vaccination can be substantially more effective and was, before Delta: "Before Delta became the predominant variant in June, case rates were higher among persons who survived a previous infection than persons who were vaccinated alone." The author of that article has apparently taken the later data, disregarded the earlier data, and just assumed the later state must be the case forever, which is a particularly unsound conclusion to draw when looking at a range of data which has changed over time.

And, second, it appears to ignore the limitations of the study. In particular that "persons with undiagnosed infection are misclassified as having no previous COVID-19 diagnosis" and that there is "uncertainty in the population size of the unvaccinated group without a previous COVID-19 diagnosis", as well as that "this analysis did not ascertain receipt of additional or booster COVID-19 vaccine doses and was conducted before many persons were eligible or had received additional or booster vaccine doses, which have been shown to confer additional protection", that "this analysis did not include information on the severity of initial infection and does not account for the full range of morbidity and mortality represented by the groups with previous infections", and that "this analysis was conducted before the emergence of the Omicron variant, for which vaccine or infection-derived immunity might be diminished."

All of those, but particularly population size uncertainty and the misclassification of individuals due to unrecorded or undiagnosed infections, mean comparisons between those groups has to be considered cautiously. Additionally, for a robust comparison, demographic differences need to be accounted for (the vaccinated population skews older and more vulnerable). The data is indicative, rather than conclusive.

And the study does conclude that "vaccination remains the safest strategy for averting future SARS-CoV-2 infections, hospitalizations, long-term sequelae, and death." and that "Primary vaccination, additional doses, and booster doses are recommended for all eligible persons.", but it is false that was based on "finding that hybrid immunity—the combination of prior infection and vaccination—was associated with a slightly lower risk of testing positive for Covid". The study makes no such statement, and states only that protection from vaccination is safer than initial infection among unvaccinated persons, since "Initial infection among unvaccinated persons increases risk for serious illness, hospitalization, long-term sequelae, and death; by November 30, 2021, approximately 130,781 residents of California and New York had died from COVID-19."

The author of that article is presumably just assuming the CDC recommends vaccination for previous infected people on the basis of what it calls 'hybrid immunity' offering some slight benefit, but has ignored the limitations and findings of the study and just compared the raw numbers to make that conclusion, when the study actually indicates more substantial protection, and the author has also failed to consider multiple other, more compelling, reasoning, including boosting potential waning of infection-induced immunity through vaccination being safer than boosting through further infection, and that infection-induced immunity can vary depending on the individual and infection, whereas vaccine-induced immunity tends to be more consistent (given standardised dosing). That is, the group, 'people with a previous infection' might, overall, have good protection, but individuals in that group may have very little. Because infection-induced immunity varies a lot depending on the individual and the infection; some people will have next to no protection against reinfection.

It's still a case of "more data needed", since, as the study says, we don't know how Omicron shifted things, and we also have better data on the waning effect of vaccination than we do infection-induced immunity. But that author's representation of the study is demonstrably inaccurate and misleading.

Instead of reading an opinion piece, why not read the actual CDC study being discussed, which Rob and I both did, and see for yourself why the CDC concludes that vaccination is the safer route?

Couple of points: the study concludes that vaccination is much safer than actually going the natural immunity route because actually getting Covid has some significant health risks, up to and including death, which are much more severe than getting vaccinated. Rob found the same thing. Your opinion piece completely misstates their conclusion.

Second, when people tout statistics it makes sense to go take an actual look at the numbers. Especially when total numbers being discussed are small to begin with, touting that there was a 50% increase doesn’t mean it’s significant. For example, let‘s say that out of a population of 100, 2% with natural immunity got sick, and 3% got sick after vaccination. That’s a 33% difference, which sounds significant, but it really isn’t and might be within a sampling error.

So you are saying the vaccine alone is more effective than natural immunity alone?