ivermectin
Article
ivermectin is a recurring concept in the Astral Codex Ten archive, appearing 18 times across 18 issues between September 06, 2021 and January 21, 2026. The archive places it in contexts such as “ivermectin is an antiparasitic drug that looked promising against COVID”; “ivermectin is causing a few hospitalizations”; “Any deep dive into ivermectin has to start here”. It most often appears alongside COVID, Alexandros Marinos, ivermectin.
Metadata
- Category: Concepts
- Mention count: 18
- Issue count: 18
- First seen: September 06, 2021
- Last seen: January 21, 2026
Appears In
- Too Good To Check: A Play In Three Acts
- Ivermectin: Much More Than You Wanted To Know
- Highlights From The Comments On Ivermectin
- Pascalian Medicine
- Open Thread 200
- Open Thread 201
- The FDA Has Punted Decisions About Luvox Prescription To The Deepest Recesses Of The Human Soul
- Bounded Distrust
- Predictions For 2022
- Open Thread 227
- Response To Alexandros Contra Me On Ivermectin
- Open Thread 262
- Contra Kavanagh On Fideism
- Trying Again On Fideism
- Declining Sperm Count: Much More Than You Wanted To Know
- The Other COVID Reckoning
- Your Review: The Astral Codex Ten Commentariat (“Why Do We Suck?”)
- Highlights From The Comments On Scott Adams
Related Pages
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- COVID (11 shared issues)
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- Alexandros Marinos (7 shared issues)
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- ivermectin (7 shared issues)
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- ACX (5 shared issues)
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- Scott (5 shared issues)
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- Donald Trump (4 shared issues)
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- Dr. Bitterman (4 shared issues)
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- fluvoxamine (4 shared issues)
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- Gideon Meyerowitz-Katz (4 shared issues)
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- hydroxychloroquine (4 shared issues)
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- ivmmeta (4 shared issues)
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- ivmmeta.com (4 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
In case you find this hard to follow: ivermectin is an antiparasitic drug that looked promising against COVID in early studies. Later it started looking less promising, and investigators found that a major supporting study was fraudulent. But by this point it had gotten popular among conspiracy theorists as a suppressed coronavirus cure that They Don’t Want You To Know. The media has tried to spread the word that the scientific consensus remains skeptical. In the process, they may have gone a little overboard and portrayed it as the world’s deadliest toxin that will definitely kill you and it will all somehow be Donald Trump’s fault. It turned into the latest culture war issue, and now there’s a whole discourse on (for example) how supposedly-sober fact-checkers keep calling it "a horse dewormer” (it is used to deworm horses, but it’s also FDA-approved for humans, but lots of the people using it are buying the horse version), and probably this is hypocritical in some way. Enter the article above. A doctor named Jason McElyea apparently told local broadcaster KFOR that Oklahoma hospitals are “overwhelmed” with ivermectin poisoning cases, so much so that “gunshot victims” are “left waiting”. Some of the world’s biggest news outlets heard the story and ran with it. The tweet mentions the Rolling Stone version, but the same story, with the same doctor’s testimony, got picked up by The Guardian, the BBC, Yahoo News, etc. Which brings us to the Sequoyah Hospital letter on the right. They released a statement saying that Dr. McElyea hasn’t worked there in two months, they haven’t had any ivermectin overdose cases, and they don’t know what he’s talking about. In the comments, author Virginia Hume sums up the situation nicely: I’ve recently been reading Scout Mindset (expect a review soon), which is kind of the rationalist movement in book form. It focuses on the difference between how we treat ideas that conform to our biases versus those that contradict them. If they conform, we ask “Are we allowed to accept this?” and wave them through, like a small town police chief dealing with a case involving the mayor’s son. If they contradict, we subject them to the harshest inquisition possible, like a small town police chief dealing with a guy named “Abdullah” with a sinister-looking beard. The media was already looking to discredit ivermectin. So the report of one doctor - without even a phone call to confirm - was good enough for Rolling Stone, The Guardian, BBC, etc. It was “too good to check”. II. Did you believe that? I did, briefly. Then I remembered the Law Of Rationalist Irony: the smugger you feel about having caught a bias in someone else, the more likely you are falling victim to that bias right now, in whatever way would be most embarrassing. So, quick check: am I doing this? I notice this story is exactly tailored to appeal to me and people like me. It discredits the media establishment, who I don’t like. It’s a great argument for why we need more rationality, something I’ve been trying to push. It lets me feel superior to everyone: I am properly skeptical of ivermectin, but also I haven’t become a contemptible propagandist who joins in mass media smear campaigns. And I didn’t even take a second to check if it was true! I’m relying entirely on the word of a Twitter bluecheck I’ve never heard of before, whose profile picture is some kind of dog (an Australian sheepdog? maybe some kind of weird collie?) Forget making a phone call to a hospital, I didn’t even read the original article! The story was “too good to check”! So I tried checking, and noticed that the third reply to the original tweet was this: In case you’re as confused as I am, NHS here = “Northeastern Health System”, an Oklahoma health care group. Britain is not involved. This…turns out to be completely true. The story never mentions Sequoyah Hospital! Dr. McElyea has worked at Sequoyah in the past, but he’s a traveling doctor and works lots of places. Plausibly Sequoyah just wanted to clarify that they weren’t like the hospitals in the story, they’re not turning away gunshot victims, and if you happen to be a gunshot victim you’re still welcome to go to Sequoyah and can expect timely care. Apparently I’m not the only person who doesn’t scroll down to the third tweet. The right-wing Washington Examiner has an article on how Rolling Stone’s Ivermectin Fiction Shows Why Republicans Don’t Trust Media. Fox has an article on Rolling Stone Forced To Issue Update After Viral Ivermectin Story Turns Out To Be False. One Redditor puts it more bluntly: “Dr. Jason McElyea, who has been claiming that emergency rooms have been turning away gunshot victims because of Ivermectin overdoses, is a liar.” None of these sources mentioned that the original article had never claimed Sequoyah Hospital was involved. Their story was - I guess - too good to check. III. Did you believe that? I mean, that’s also a pretty cool story, isn’t it? Right-wing news outlets accuse the so-called “liberal media” of bias, then get hoist on their own petard? Seems a bit too cute. Have you clicked through to any of the links yet? No? Not even after I admitted I’m probably biased here? Sequoyah Hospital might not be the particular hospital that the doctor in the story was thinking of. But isn’t it suspicious that other hospitals are so packed with ivermectin cases that they have to delay care to gunshot victims, yet Sequoyah says that it “has not treated any patients due to complications of treating ivermectin”? Seems weird for there to be that much difference. Okay, this time I promise I’m not trying to psych you out. Here’s what I’ve actually been able to figure out about this situation: Rolling Stone seems to think that the Sequoyah Hospital statement casts doubt on their account. They changed the title of their article to “One Hospital Denies Oklahoma Doctor’s Story…” and edited in a long prologue about the hospital’s statement in a way that suggests they feel bad about their reporting. They say that they have reached out to various relevant doctors and hospitals for comments but have not heard back from them - which I guess is good, because if your hospital is so busy that you don’t have time to treat gunshot victims, you really shouldn’t have time to give interviews to Rolling Stone.
Inline links: the, The Guardian, the BBC, Yahoo News, https://substackcdn.com/image/fetch/$s_!50Ju!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F6a65950a-1232-4977-ace5-71b13c4ab83f_726x156.png, Scout Mindset, https://substackcdn.com/image/fetch/$s_!cSE3!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe530cd25-fde9-4b98-b7d8-a1143ee0e026_722x187.png, Rolling Stone’s Ivermectin Fiction Shows Why Republicans Don’t Trust Media, Rolling Stone Forced To Issue Update After Viral Ivermectin Story Turns Out To Be False, puts it more bluntly
Rolling Stone seems to think that the Sequoyah Hospital statement casts doubt on their account. They changed the title of their article to “One Hospital Denies Oklahoma Doctor’s Story…” and edited in a long prologue about the hospital’s statement in a way that suggests they feel bad about their reporting. They say that they have reached out to various relevant doctors and hospitals for comments but have not heard back from them - which I guess is good, because if your hospital is so busy that you don’t have time to treat gunshot victims, you really shouldn’t have time to give interviews to Rolling Stone.
Inline links: One Hospital Denies Oklahoma Doctor’s Story
In an unrelated issue, the photo on top of their article was previously a bunch of Oklahoman-looking people standing in a long line outside a building. This had a caption, in small print, saying that it was of Oklahomans waiting for the COVID vaccine. Critics pointed out that in context, people would have interpreted it as being a picture of people waiting outside a hospital which had long lines because it was too full of ivermectin victims. Whether or not that criticism was fair, Rolling Stone has taken down that photo and replaced it with a photo of ivermectin pills.
But here’s my pitch: this is one of the most carefully-pored-over scientific issues of our time. Dozens of teams published studies saying ivermectin definitely worked. Then most scientists concluded it didn’t. What a great opportunity to exercise our study-analyzing muscles! To learn stuff about how science works which we can then apply to less well-traveled terrain! Sure, you read the articles saying that experts had concluded the studies were wrong. But did you really develop a gears-level understanding of what was going on? That’s what we have a chance to get here!
Any deep dive into ivermectin has to start here:
This is from ivmmeta.com, part of a sprawling empire of big professional-looking sites promoting unorthodox coronavirus treatments. I have no idea who runs it - they’ve very reasonably kept their identity secret - but my hat is off to them. Each of these study names links to a discussion page which extracts key outcomes and offers links to html and pdf versions of the full text. These same people have another 35 ivermectin studies with different inclusion criteria, subanalyses by every variable under the sun, responses and counterresponses to everyone who disagrees with them about every study, and they’ve done this for twenty-nine other controversial COVID treatments. Putting aside the question of accuracy and grading only on presentation and scale, this is the most impressive act of science communication I have ever seen. The WHO and CDC get billions of dollars in funding and neither of them has been able to communicate their perspective anywhere near as effectively. Even an atheist can appreciate a cathedral, and even an ivermectin skeptic should be able to appreciate this website. What stands out most in this image (their studies on early treatment only; there are more on other things) is all the green boxes on the left side of the table. A green box means that the ivermectin group did better than placebo (a red box means the opposite). This isn’t adjusted for statistical significance - indeed, many of these studies don’t reach it. The point of a meta-analysis is that things that aren’t statistically significant on their own can become so after you pool them with other things. If you see one green box, it could mean the ivermectin group just got a little luckier than the placebo group. When you see 26 boxes compared to only 4 red ones, you know that nobody gets that lucky. Acknowledging that this is interesting, let’s detract from it a little. First, this presentation can exaggerate the effect size (represented by how far the green boxes are to the left of the gray line in the middle representing no effect). It focuses on the most dire outcome in every study - death if anybody died, hospitalization if anyone was hospitalized, etc. Most studies are small, and most COVID cases do fine, so most of these only have one or two people die or get hospitalized. So the score is often something like “ivermectin, 0 deaths; placebo, 1 death”, which is an infinitely large relative risk, and then the site rounds it down to some very high finite number. This methodology naturally produces very big apparent effects, and the rare studies where ivermectin does worse than placebo are equally exaggerated (one says that ivermectin patients are 600% more likely to end up hospitalized). But this doesn’t change the basic fact that ivermectin beats placebo in 26/30 of these studies. Second, this presents a pretty different picture than you would get reading the studies themselves. Most of these studies are looking at outcomes like viral load, how long until the patient tests negative, how long until the patient’s symptoms go away, etc. Many of these results are statistically insignificant or of low effect size. I went through these studies and tried to get some more information for my own reference: Click to expand. # is how many people were in the smallest relevant group (eg if there were 20 people in placebo and 10 in ivermectin, it was 10). Dose is ivermectin dose x number of days. Tested w/ is what drugs were given alongside ivermectin; compare is what drugs were in the “placebo” group (I excluded some very common things like paracetamol). %-PCR7 is what percent of patients had a negative PCR test (indicating recovery) after 7 days (though if 7 wasn’t available, I accepted anything from 6-12); the (I) and (P) are ivermectin and placebo groups. R is the ratio - green if statistically significant, red otherwise. DaysPCR is how many days it took to get a negative PCR test. Days to -sym are how many days it took symptoms to resolve. -outc is some serious negative outcome in the study, either clinical worsening, hospitalization, or death. I was inconsistent which one I chose, trying to pick whichever I thought struck a balance between high sample size and severity. Since this was almost never significant, I made it blue if it favored ivermectin and orange if it favored placebo (which it never did; there is no orange). Lowest p is the lowest p-value in the study for one of the headline results. 1o+ is whether the primary outcome was positive or not. I made this very quickly and unprincipledly and I am sure there are a lot of errors; please forgive me. Of studies that included any of the endpoints I recorded, ivermectin had a statistically significant effect on the endpoint 13 times, and failed to reach significance 8 times. Of studies that named a specific primary endpoint, 9 found ivermectin affected it significantly, and 12 found it didn’t. But that’s still pretty good. And “doesn’t affect to a statistically significant degree” doesn’t mean it doesn’t work. It might just mean your study is too small for a real and important effect to achieve statistical significance. That’s why people do meta-analyses to combine studies. And the ivmmeta people say they did that and it was really impressive. All of this is still basically what things would look like if ivermectin worked. But of course we can’t give every study one vote. We’ve got to actually look at these and see which ones are good and which ones are bad. So, God help us, let’s go over all thirty of the ivermectin studies in this top panel of ivmmeta.com. (if you get bored of this, scroll down to the section called “The Analysis”) The Studies Elgazzar et al: This one isn’t on the table above, but we can’t start talking about the others until we get it out of the way. 600 Egyptian patients were randomized into six groups, including three that got ivermectin. The ivermectin groups did substantially better: for example, 2 vs. 20 deaths in ivermectin group 3 vs. non-ivermectin group 4. There were various other equally impressive outcomes. Unfortunately, it’s all false. Some epidemiologists and reporters were able to obtain the raw data (it was password-protected, but the password was “1234”), and it was pretty bizarre. Some patients appeared to have died before the trial started; others were arranged in groups of four such that it seemed like the authors had just copy-pasted the same four patients again and again. Probably either the study never happened, or at least the data were heavily edited afterwards. You can read more here. A lot of the apparent benefit of ivermectin in meta-analyses disappeared after taking out this paper (though remember, this isn’t even on the table at the top of the post, so it doesn’t directly affect that). Since the Elgazzar debacle, a group of researchers including Gideon Meyerowitz-Katz, Kyle Sheldrake, James Heathers, Nick Brown, Jack Lawrence, etc, have been trying to double-check as many other ivermectin studies as possible. At least three others - Samaha, Carvallo, and Niaee - have similar problems and have been retracted. Those studies were all removed before I screenshotted the table above, and they’re not on there. But everybody is pretty paranoid right now and looking for fraud a lot harder than they might be in normal situations. Moving on: Chowdury et al: Bangladeshi RCT. 60 patients in Group A got low-dose ivermectin plus the antibiotic doxycycline, 56 in Group B got hydroxychloroquine (another weird COVID treatment which most scientists think doesn’t work) plus the antibiotic azithromycin. No declared primary outcome. Ivermectin group got to negative PCR a little faster than the other (5.9 vs. 7 days) but it wasn’t statistically significant (p = 0.2). A couple of other non-statistically-significant things happened too. 2 controls were hospitalized, 0 ivermectin patients were. This is a boring study that got boring results, so nobody has felt the need to assassinate it, but if they did, it would probably focus on both groups getting various medications besides ivermectin. None of these other medications are believed to work, so I don’t really care about this, but you could tell a story where actually doxycycline works great at addressing associated bacterial pneumonias, or where HCQ causes lots of side effects and that makes the ivermectin group look good in comparison, or whatever. Espitia-Hernandez et al: Mexican trial which is probably not an RCT - all it says is that “patients were voluntarily allocated”. 28 ended up taking a cocktail of low-dose ivermectin, vitamin D, and azithromycin; 7 were controls. On day ten, everyone (!) in the experimental group was PCR negative; everyone (!) in the control group was still positive. Also, symptoms in the experimental group lasted an average of three days; in the control group, more like 10. These results make ivermectin look amazingly super-good, probably better than any other drug for any other disease, except maybe stuff like vitamins for treatment of vitamin deficiency. Any issues? We don’t know how patients were allocated, but they discuss patient characteristics and they don’t look different enough to produce this big an effect size. The experimental group got a lot of things other than ivermectin, but I would be equally surprised if vitamin D or azithromycin cured COVID this effectively. It deviated from its preregistration in basically every way possible, but you shouldn’t be able to get “every experimental patient tested negative when zero control patients did” by garden-of-forking-paths alone! But this has to be false, right? Even the other pro-ivermectin studies don’t show effects nearly this big. In all other studies combined, ivermectin patients took an average of 8 days to recover; in Espitia-Hernandez, they took 3. Also, it’s pretty weird that the entire control group had positive PCRs on day 10 - in most other studies, a majority of people had negative PCRs by day 7 or so, regardless of whether they were control or placebo. Everything about this is so shoddy that I can easily believe something went wrong here. I don’t have a great understanding of this one but I don’t trust it at all. Luckily it is small and non-randomized so it will be easy to ignore going forward. I’m not saying this is related, but I’m not saying it *isn’t* related either. Carvallo et al: This one has all the disadvantages of Espitia-Hernandez, plus it’s completely unreadable. It’s hard to figure out how many patients there were, whether it was an RCT or not, etc. It looks like maybe there were 42 experimentals and 14 controls, and the controls were about 10x more likely to die than the experimentals. Seems pretty bad. On the other hand, another Carvallo paper was retracted because of fraud: apparently the hospital where the study supposedly took place said it never happened there. I can’t tell if this is a different version of that study, a pilot study for that study, or a different study by the same guy. Anyway, it’s too confusing to interpret, shows implausible results, and is by a known fraudster, so I feel okay about ignoring this one. Mahmud et al: RCT from Bangladesh. 200 patients received ivermectin plus doxycycline, 200 received placebo. Everything was written up very nicely in real English, by people who were clearly not on 34 lbs of meth at the time. They designated a primary outcome, “number of days required for clinical recovery”, and found a statistically significant difference at p < 0.001: Okay, fine, they misspelled “recovery” once. But they spelled it right the other time! That puts it in the top 50% for ivermectin papers! The fraud-hunters have examined this paper closely and are unable to find any signs of fraud. @PubPeer on the Mahmud trial of ivermectin in covid patients.\n\nI have now reviewed the individual patient data master sheet.\n\nI did not find any irregularities and the summary data matches the published data.\n\n","username":"K_Sheldrick","name":"Kyle Sheldrick","profile_image_url":"","date":"Sat Jul 17 11:06:25 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":2,"like_count":12,"impression_count":0,"expanded_url":{"url":"https://pubpeer.com/publications/E1D65711EF28D14517731BEACB89C8#2","title":"PubPeer - Ivermectin in combination with doxycycline for treating COVI...","description":"There are comments on PubPeer for publication: Ivermectin in combination with doxycycline for treating COVID-19 symptoms: a randomized trial (2021)","domain":"pubpeer.com"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> I think this paper is legitimate and that its findings need to be seriously considered. Serious consideration doesn’t always meant they’re true - sometimes if we have strong evidence otherwise we can dismiss things without understanding why. And there’s always the chance it was a fluke, right? Can something have a p-value less than 0.001 and still be a fluke? Szenta Fonseca et al: This is a chart review from Brazil. Researchers looked at various people who had been treated for COVID in an insurance company database, saw whether they got ivermectin or not, and saw whether the people who got it did better or worse. About a hundred people got it, and a few hundred others didn’t. The people who got it did not do any better than anyone else, and you’ll notice this is one of the rare red boxes on the table above. But we shouldn’t take this study seriously. Nobody took any effort to avoid selection bias, so it’s very possible that sicker people were given more medication (including ivermectin), which unfairly handicaps the ivermectin group. Also, it’s hard to tell from the paper who was on how much of what, and the discussion of ivermectin seems like kind of an afterthought after discussing lots of other meds in much more depth. This is another one I feel comfortable ignoring. Cadegiani et al: A crazy person decided to put his patients on every weird medication he could think of, and 585 subjects ended up on a combination of ivermectin, hydroxychloroquine, azithromycin, and nitazoxanide, with dutasteride and spironolactone "optionally offered" and vitamin D, vitamin C, zinc, apixaban, rivaraxoban, enoxaparin, and glucocorticoids "added according to clinical judgment". There was no control group, but the author helpfully designated some random patients in his area as a sort-of-control, and then synthetically generated a second control group based on “a precise estimative based on a thorough and structured review of articles indexed in PubMed and MEDLINE and statements by official government agencies and specific medical societies”. Patients in the experimental group were twice as likely to recover (p < 0.0001), had negative PCR after 14 vs. 21 days, and had 0 vs. 27 hospitalizations. Speaking of low p-values, some people did fraud-detection tests on another of Cadegiani’s COVID-19 studies and got values like p < 8.24E-11 in favor of it being fraudulent. And, uh, he’s also studied whether ultra-high-dose antiandrogens treated COVID, and found that they did, cutting mortality by 92% . But the trial is under suspicion, with a BMJ article calling it “[the worst] violations of medical ethics and human rights in Brazil’s history” and “an ethical cesspit of violations”. [update 2022: this section originally contained more accusations against Cadegiani. Alexandros Marinos does a deeper dive with information not available at the time I wrote this, and finds some of them were overstated or false by implication] Anyway, let’s not base anything important on the results of this study, mmkay? A defiant Flavio Cadegiani. Imagine a guy who looks like this telling you to take ultra-high-dose antiandrogens. Ahmed et al: And we’re back in Bangladesh. 72 hospital patients were randomized to one of three arms: ivermectin only, ivermectin + doxycycline, and placebo. Primary endpoint was time to negative PCR, which was 9.7 days for ivermectin only and 12.7 days for placebo (p = 0.03). Other endpoints including duration of hospitalization (9.6 days ivermectin vs. 9.7 days placebo, not significant). This looks pretty good for ivermectin and does not have any signs of fraud or methodological problems. If I wanted to pick at it anyway, I would point out that the ivermectin + doxycycline group didn’t really differ from placebo, and that if you average out both ivermectin groups (with and without doxycycline) it looks like the difference would not be significant. I had previously committed to considering only ivermectin alone in trials that had multiple ivermectin groups, so I’m not going to do this. I can’t find any evidence this trial was preregistered so I don’t know whether they waited to see what would come out positive and then made that their primary endpoint, but virological clearance is a pretty normal primary endpoint and this isn’t that suspicious. It’s impossible to find any useful commentary on this study because Elgazzar (the guy who ran the most famous fraudulent ivermectin study) had the first name Ahmed, everyone is talking about Elgazzar all the time, and this overwhelms Google whenever I try to search for Ahmed et al. For now I’ll just keep this as a mildly positive and mildly plausible virological clearance result, in the context of no effect on hospitalization length or most symptoms. Chaccour et al: 24 patients in Spain were randomized to receive either medium-dose ivermectin or placebo. The primary outcome was percent of patients with negative PCR at day 7; secondary outcomes were viral load and symptoms. The primary endpoint ended up being kind of a wash - everyone still PCR positive by day 7 so it was impossible to compare groups. Ivermectin trended toward lower viral load but never reached significance. Weirdly, ivermectin did seem to help symptoms, but only anosmia and cough towards the end (p = 0.03), which you would usually think of as lingering post-COVID problems. The paper says: Given these findings, consideration could be given to alternative mechanisms of action different from a direct antiviral effect. One alternative explanation might be a positive allosteric modulation of the nicotinic acetylcholine receptor caused by ivermectin and leading to a downregulation of the ACE-2 receptor and viral entry into the cells of the respiratory epithelium and olfactory bulb. Another mechanism through which ivermectin might influence the reversal of anosmia is by inhibiting the activation of pro-inflammatory pathways in the olfactory epithelium. Inflammation of the olfactory mucosa is thought to play a key role in the development of anosmia in SARS-CoV-2 infection This seems kind of hedge-y. If you’re wondering where things went from there, Dr. Chaccour is now a passionate anti-ivermectin activist: @Finneganporter in @BusinessInsider \n\nThe roots of #ivermectin mania: How South America incubated a fake-medicine craze that took the US by storm\n\n","username":"carlos_chaccour","name":"Dr. Carlos Chaccour ??????","profile_image_url":"","date":"Sun Nov 07 18:40:28 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":2,"like_count":9,"impression_count":0,"expanded_url":{"url":"https://www.businessinsider.in/international/news/the-roots-of-ivermectin-mania-how-south-america-incubated-a-fake-medicine-craze-that-took-the-us-by-storm/articleshow/87554081.cms","image":"https://bucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com/public/images/88d08e70-c9e2-46d4-a5df-96807b6c3a13_2000x1000.jpeg","title":"The roots of ivermectin mania: How South America incubated a fake-medicine craze that took the US by storm","description":"The popularity of unproven anti-parasitic drug ivermectin as a COVID-19 treatment is surging. Its use has roots in South America, where it was hyped by populist","domain":"businessinsider.in"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> So I guess he must think of this trial as basically negative, although realistically it’s 24 people and we shouldn’t put too much weight on it either way. Ghauri et al: Pakistan, 95 patients. Nonrandom; the study compared patients who happened to be given ivermectin (along with hydroxychloroquine and azithromycin) vs. patients who were just given the latter two drugs. There’s some evidence this produced systematic differences between the two groups - for example, patients in the control group were 3x more likely to have had diarrhea (this makes sense; diarrhea is a potential ivermectin side effect, so you probably wouldn’t give it to people already struggling with this problem). Also, the control group was twice as likely to be getting corticosteroids, maybe a marker for illness severity. Primary outcome was what percent of both groups had a fever: on day 7 it was 21% of ivermectin patients vs. 65% of controls, p < 0.001. No other outcomes were reported. I don’t hate this study, but I think the nonrandom assignment (and observed systematic differences) is a pretty fatal flaw. I can’t find anyone else talking about this one. At least no one seems to be saying anything bad. Babaloba et al: Be warned: if I have to refer to this one in real-life conversation, I will expand out the “et al” and call it “Babalola & Alakoloko”, because that’s really fun to say. This was a Nigerian RCT comparing 21 patients on low-dose ivermectin, 21 patients on high-dose ivermectin, and 20 patients on a combination of lopinavir and ritonavir, a combination antiviral which later studies found not to work for COVID and which might as well be considered a placebo. Primary outcome, as usual, was days until a negative PCR test. High dose ivermectin was 4.65 days, low dose was 6 days, control was 9.15, p = 0.035. Figure 2 is apparently a photograph of the computer screen where they did this calculation. Gideon Meyerowitz-Katz, part of the team that detects fraud in ivermectin papers, is not a fan of this one: He doesn’t say there what means, but elsewhere he tweets this figure: It’s always a bad sign when your study features in an image with “NUMEROUS IMPOSSIBLE NUMBERS” in red at the top. I think his point is that if you have 21 people, it’s impossible to have 50% of them have headache, because that would be 10.5. If 10 people have a headache, it would be 47.6%; if 11, 52%. So something is clearly wrong here. Seems like a relatively minor mistake, and Meyerowitz-Katz stops short of calling fraud, but it’s not a good look. I’m going to be slightly uncomfortable with this study without rejecting it entirely, and move on. Ravakirti et al: Here we’re in Eastern India - not exactly Bangladesh again, but a stone’s throw away from it. In this RCT patients were randomized into an ivermectin group (57) and a placebo group (58). Primary outcome was negative PCR on day 6, because doing it on day 7 like everyone else would be too easy. As with several other groups, this was a bad move; too few people had it to make a good comparison; it was 13% of intervention vs. 18% of placebo, p = 0.3. Secondary outcomes were also pretty boring, except for the most important: 4 people in the placebo group died, compared to 0 in ivermectin (p = 0.045). On the one hand, this is one outcome of many, reaching the barest significance threshold. Another fluke? Still, there are no real problems with this study, and nobody has anything to say against it. Let’s add this one to the scale as another very small and noisy piece of real evidence in ivermectin’s favor. Bukhari et al: Now we’re in Pakistan. 50 patients were randomized to low-dose ivermectin, another 50 got standard of care including vitamin D. There was no placebo, but primary outcome was number of days to reach negative PCR, which it seems hard for placebo to affect much, so I don’t care. 5 controls and 9 ivermectin patients left the hospital against medical advice and could not be followed up, which is bad but not necessarily study-ruining. They never measured their supposed primary outcome of “days to reach negative PCR” directly, but they did measure how many people had negative PCR on various days, and ivermectin had a clear advantage - for example, on day 7, it was 37/50 for IVR and only 20/50 for control. Even if we assume all the lost-to-followup patients had maximally bad-for-the-hypothesis results, that’s still a positive finding. Nobody else has much to say about this one, certainly no accusations that they’ve found anything suspicious. Keep. Mohan et al: India. RCT. 40 patients got low-dose ivermectin, 40 high-dose ivermectin, and 45 placebo. Primary outcomes were time to negative PCR, and viral load on day 5. In the results, they seem to have reinterpreted “time to negative PCR” as the subtly different “percent with negative PCR on some specific day”. High-dose ivermectin did best (47.5% negative on day 5) and placebo worst (31% negative), but it was insignificant (p = 0.3). There was no difference in viral load. All groups took about the same amount of time for symptoms to resolve. More placebo patients had failed to recover by the end of the study (6) than ivermectin patients (2), but this didn’t reach statistical significance (p = 0.4). Overall a well-done, boring, negative study, although ivermectin proponents will correctly point out that, like basically every other study we have looked at, the trend was in favor of ivermectin and this could potentially end up looking impressive in a meta-analysis. Biber et al: This is an RCT from Israel. 47 patients got ivermectin and 42 placebo. Primary endpoint was viral load on day 6. I am having trouble finding out what happened with this; as far as I can tell it was a negative result and they buried it in favor of more interesting things. In a "multivariable logistic regression model, the adjusted odds ratio of negative SARS-CoV-2 RT-PCR negative test" favored ivermectin over placebo (p = 0.03 for day 6, p = 0.01 for day 8), but this seems like the kind of thing you do when your primary outcome is boring and you’re angry. Gideon Meyerowitz-Katz is not a fan: He notes that the study excluded people with high viral load, but the preregistration didn’t say they would do that. Looking more closely, he finds they did that because, if you included these people, the study got no positive results. So probably they did the study, found no positive results, re-ran it with various subsets of patients until they did get a positive result, and then claimed to have “excluded” patients who weren’t in the subset that worked. I’m going to toss this one. Elalfy et al: What even is this? Where am I? As best I can tell, this is some kind of Egyptian trial. It might or might not be an RCT; it says stuff like “Patients were self-allocated to the treatment groups; the first 3 days of the week for the intervention arm while the other 3 days for symptomatic treatment”. Were they self-allocated in the sense that they got to choose? Doesn’t that mean it’s not random? Aren’t there seven days in a week? These are among the many questions that Elalfy et al do not answer for us. The control group (which they seem to think can also be called “the white group”) took zinc, paracetamol, and maybe azithromycin. The intervention group took zinc, nitazoxanide, ribavirin, and ivermectin. There were very large demographic differences between the groups of the sort which make the study unusable, which they mention and then ignore. From there, they follow this normal and totally comprehensible flowchart: There is no primary outcome assigned, but viral clearance rates on day seven were 58% in the yellow group compared to 0% in the white group, which I guess is a strong positive result. This table… …looks very impressive, in terms of the experimental group doing better than the control, except that they don’t specify whether it was before the trial or after it, and at least one online commentator thinks it might have been before, in which case it’s only impressive how thoroughly they failed to randomize their groups. Overall I don’t feel bad throwing this study out. I hope it one day succeeds in returning to its home planet. Lopez-Medina et al: Colombian RCT. 200 patients took ivermectin, another 200 took placebo. They originally worried the placebo might taste different than real ivermectin, then solved this by replacing it with a different placebo, which is a pretty high level of conscientiousness. Primary outcome was originally percent of patients whose symptoms worsened by two points, as rated on a complicated symptom scale when a researcher asked them over the phone. Halfway through the study, they realized nobody was worsening that much, so they changed the primary outcome to time until symptoms got better, as measured by the scale. In the ivermectin group, symptoms improved that much after 10 days; in the placebo group, after 12, p = 0.53. By the end of the study, symptoms had improved in 82% of ivermectin users and 79% of controls, also insignificant. 4 patients in the ivermectin group needed to be hospitalized compared to 6 in the placebo group, again insignificant. This study is bigger than most of the other RCTs, and more polished in terms of how many spelling errors, photographs of computer screens, etc, it contains. It was published in JAMA, one of the most prestigious US medical journals, as opposed to the crappy nth-tier journals most of the others have been in. When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. Ivermectin proponents make some good arguments against it. In order to get as big as it did, Lopez-Medina had to compromise on rigor. Its outcome is how people self-score their symptoms on a hokey scale in a phone interview, instead of viral load or PCR results or anything like that. Still, this is basically what we want, right? In the end, we want people to feel better and less sick, not to get good scores on PCR tests. Also, it changed its primary outcome halfway through; isn’t that bad? I think maybe not; the reason we want a preregistered primary outcome is so that you don’t change halfway through to whatever outcome shows the results you want. The researchers in this study did a good job explaining why they changed their outcome, the change makes sense, and their original outcome would also have shown ivermectin not working (albeit less accurately and effectively). I don’t know of any evidence that they knew (or suspected) final results when switching to this new outcome, and it seems like the most reasonable new outcome to switch to. Finally, their original placebo tasted different from ivermectin (though they switched halfway through). This is one of the few studies where I actually care about placebo, because people are self-rating their symptoms. But realistically most of these people don’t know what ivermectin is supposed to taste like. Also, they did a re-analysis and found there was no difference between the people who got the old placebo and the new one. I’m making a big deal of this because ivmmeta.com - the really impressive meta-analysis site I’ve been going off of - puts a special warning letter underneath their discussion of this study, urging us not to trust it. They don’t do this for any of the other ones we’ve addressed so far - not the one by the guy whose other studies were all frauds, not the one where 50% of 21 people had headaches, not the unrandomized one where the groups were completely different before the experiment started, not even the one by the guy accused of crimes against humanity. Only this one. This makes me a lot less charitable to ivmmeta than I would otherwise be; I think it’s hard to choose this particular warning letter strategy out of well-intentioned commitment to truth. They just really don’t like this big study that shows ivermectin doesn’t work. Also, the warning itself irritates me, and includes paragraphs like: RCTs have a fundamental bias against finding an effect for interventions that are widely available — patients that believe they need treatment are more likely to decline participation and take the intervention [Yeh], i.e., RCTs are more likely to enroll low-risk participants that do not need treatment to recover (this does not apply to the typical pharmaceutical trial of a new drug that is otherwise unavailable). This trial was run in a community where ivermectin was available OTC and very widely known and used. Nobody else worries about this, and there are a million biases that non-randomized studies have that would be super-relevant when discussing those, but somehow when they’re pro-ivermectin the site forgets to be this thorough. I think a better pro-ivermectin response to this study is to point out that all the trends support ivermectin. Symptoms took 10 days to resolve in the ivermectin group vs. 12 in placebo; 4 ivermectin patients were hospitalized vs. 6 placebo patients, etc. Just say that this was an unusually noisy trial because of the self-report methodology, and you’re confident that these small differences will add up to significance when you put them into a meta-analysis. Roy et al: We’re back in East India, and back to non-randomized trials. 56 patients were retrospectively examined; some had been given ivermectin + doxycycline, others hydroxychloroquine, other azithromycin, and others symptomatic treatment only. We don’t get any meaningful information about how this worked, but we are told that they did not differ in “clinical well-being reporting onset timing”. Whatever. Chahla et al: The first of many Argentine trials. 110 patients received medium-dose ivermectin; 144 were kept as a control (no placebo). This was “cluster randomized”, which means they randomize different health centers to either give the experimental drug or not. This is worse than regular randomization, because there could be differences between these health centers (eg one might have better doctors who otherwise give better treatment, one might be in the poor part of town and have sicker patients, etc). They checked to see if there were any differences between the groups, and it sure looks like there were (the experimental group had twice as many obese people as the controls), but as per them, these differences were not statistically significant. Note that if this did make a difference, it would presumably make ivermectin look worse, not better. The primary outcome was given as “increase discharge from outpatient care with COVID-19 mild disease”. This favored the treatment; only 2/110 patients in the ivermectin group failed to be discharged, compared to 20 patients in the control group. But, uh, these were at different medical centers. Can’t different medical centers just have different discharge policies? One discharges you as soon as you seem to be getting better, the other waits to really make sure? This is an utterly crap endpoint to do a cluster randomized controlled trial on. If you’re going to do cRCT, which is never a great idea, you should be using some extremely objective endpoint that doctors and clinic administrators can’t possibly affect, like viral load according to some third-party laboratory, using the same third-party laboratory for both clinics. This is such a bad idea that I can’t help worrying I’m missing or misunderstanding something. If not, this is dumb and bad and should be ignored. Mourya et al: We’re back in India. This is a nonrandomized study comparing 50 patients given ivermectin to 50 patients given hydroxychloroquine. No primary outcome was named, but they focus on PCR negativity. Only 6% of patients in the hydroxychloroquine group were negative, compared to 90% of patients in the ivermectin group! On what day did they do the test? Uh, kind of random, and they admit that “in [the hydroxychloroquine group], mean time difference from the date of initiation of treatment and second test was significantly longer (7.24±2.75 days) as compared to 5.22±1.21 days in [the ivermectin group] (p=0.021).” Since they assessed these groups at different times, we shouldn’t draw any conclusions from them getting different results. Except that as far as I can tell this should handicap ivermectin, making it especially impressive that it did better. But also, the ivermectin group was made mostly of people who had been asymptomatic at the beginning (70%), and the hydroxychloroquine group had almost no asymptomatic cases (8%) . They were giving the ivermectin to healthy people and the hydroxychloroquine to sick people! They admit deep in the discussion that this “may be a confounding factor”. So basically they got totally different groups of people, tested them at totally different times, and the two sets of test results differed. So what? So this is why normal people do RCTs instead of whatever the heck this is, that’s what. Loue et al: …this one isn’t going to be an RCT either. Loue tells a story about a cluster of COVID cases at the French nursing home where he works. He asked people if they wanted to try ivermectin; 10 did and 15 didn’t. 1 ivermectin patient died, compared to 5 non-ivermectin patients. The non-ivermectin group looked a bit sicker than the ivermectin group in the inevitable Table 1, though it’s hard to tell. One interesting possible confounder (not mentioned, but I’m imagining it) is that demented patients probably couldn’t consent to ivermectin and ended up in the control group. This is another case of “I’m not going to trust anything that isn’t an RCT”. Merino et al: Another (sigh) non-RCT. Mexico City tried a public health program where if you called a hotline and said you had COVID, they sent you an emergency kit with various useful supplies. One of those supplies was ivermectin tablets. 18,074 people got the kit (and presumably some appreciable fraction took the ivermectin, though there’s no way to prove that). Their control group is people from before they started giving out the kits, people from after they stopped giving out the kits, and people who didn’t want the kits. There are differences in who got COVID early in the epidemic vs. later, and in people who did opt for medical kits vs. didn’t. To correct these, the researchers tried to adjust for confounders, something which - as I keep trying to hammer home again and again - never works. They found that using the kit led to a 75% or so reduction in hospitalization, though they were unable to separate out the ivermectin from the other things in the kit (paracetamol and aspirin), or from the placebo effect of having a kit and feeling like you had already gotten some treatment (if I understand right, the decision to go to the hospital was left entirely to the patient). I think this study is a moderate point in favor of giving people kits in order to prevent hospital overcrowding, but I’m not willing to accept that it tells us much about ivermectin in particular. Faisal et al: This one was published in The Professional Medical Journal (mispelled as “Profesional Medical Journal” in its URL), so you know it’s going to be good! It describes itself as “a cross-sectional study”, but later says it “randomized patients into two groups”, which would make it an RCT - I think they might just be using the term “cross-sectional” different from the standard American usage. A hospital in Pakistan got 50 patients on ivermectin + azithromycin, and another 50 on azithromycin alone. Primary outcome was not mentioned, and the data were presented confusingly, but a typical result is that only 4% of the ivermectin group had symptoms lasting more than 10 days, whereas 16% of the control group did, p < 0.01. They do a really weird thing where they compare how long it took symptoms to resolve between IVM and control groups within each bin. That is, if I’m understanding correctly, they ask “of the people who took between 3-5 days for symptoms to resolve, did they resolve faster for IVM or control?”. This is an utterly bizarre analysis to perform, although it doesn’t affect the fact that their other results still seem to favor ivermectin. Maybe I’m confused about what’s going on here. I’ve mostly been letting people off easy on no placebo, but I as far as I can tell (not very far) this paper seems to be going off whether patients reported continuing to have symptoms to the hospital doing the study, and I think that is potentially susceptible to placebo effects. Additionally, there’s no preregistration, and even though they talk a lot about doing PCR tests they don’t present the results. This is by no means the worst study here but I still think it’s pretty low quality and I don’t trust it. Aref et al: This one is published in the International Journal Of Nanomedicine, even though I’m pretty sure that isn’t a real thing. In this case the “nanomedicine” is a new nasal spray version of ivermectin which is so confusing I cannot for the life of me figure out what dose they are giving these patients. This Egyptian study gives 57 patients intranasal ivermectin plus hydroxychloroquine, azithromycin, oseltamavir, and some vitamins; another 57 patients get all that stuff except the ivermectin. Primary outcome is not stated, but they look at various symptoms, all of which look better in the ivermectin group: 95% of ivermectin patients got negative PCRs at some time point, compared to 75% of controls, p = 0.004. I am pretty suspicious of this study, not least because it comes from Egypt which has an awful reputation for fake studies, and it returns extreme results that I wouldn’t expect even if ivermectin was actually a wonder drug. But I cannot find any particular thing wrong with it, nor did anyone else I looked at, so I will grudgingly let it stand. Krolewiecki et al: Another Argentine study. This one is a real RCT. 30 patients received ivermectin, 15 were the control group (no placebo, again). Primary outcome was difference in viral load on day 5. The trend favored ivermectin but it was not statistically significant, although they were able to make it statistically significant if they looked at a subset of higher-IVM-plasma-concentration patients. They did not find any difference in clinical outcomes. A pro-ivermectin person could point out that in the subgroup with the highest ivermectin concentrations, the drug seemed to work. A skeptic could point out that this is exactly the kind of subgroup slicing that you are not supposed to do without pre-registering it, which I don’t think this team did. I agree with the skeptic. Vallejos et al: Another Argentine study. It’s big (250 people in each arm). It’s an RCT. It tries to define a primary outcome (“Primary outcome: the trial ended when the last patient who was included achieved the end of study visit”), but that’s not what “primary outcome” means, and they don’t offer an alternative. Other outcomes: no difference in PCR on days 3 or 12. Hospitalization is nonsignificantly better in the ivermectin group (14 vs. 21, p = 0.2), but death is nonsigificantly better in the placebo group (3 vs. 4, p = 0.7). This isn’t even the kind of nonsignificant that might contribute to an exciting meta-analysis later. This is just a pure null result. I cannot find any problem with this study, and neither can anyone else I checked. This is the biggest RCT we’ve seen so far, so we should take it seriously. TOGETHER Trial: Speaking of big RCTs… This one hasn’t been published yet. There’s a video of a talk about it, but I am not going to watch it, because it is a video, so I am getting information secondhand from eg here. Apparently, it compares 677 people (!) randomized to ivermectin to 678 people randomized to placebo. 86 ivermectin patients ended up in the hospital compared to 95 placebo patients, p-value not significant. This was a really big professional trial done by bigshot researchers from a major Canadian university, and the medical establishment is taking it much more seriously than any of these others. When it comes out, it will probably get published in a top journal. When discussing Lopez-Medina, I wrote: When people say things like “sure, a lot of small studies show good results for ivermectin, but the bigger and more professional trials don’t”, this is one of the two big professional trials they’re talking about. This is the other one. Not coincidentally, it’s also the other trial that ivmmeta.com has a warning letter underneath telling you to disregard. Their main concern is that instead of truly randomizing patients to ivermectin vs. placebo, they did a time-dependent randomization that meant during some weeks more patients were getting one or the other. This is a problem because the trial takes place in Brazil, where different variants were more common at different times. Here’s their image: On the one hand, I have immense contempt for ivmmeta for letting all those other awful studies pass and then pulling out all the stops to try to nitpick this one. I have no idea if their proposed randomization failure really happened. And no doubt the reason they’re even able to investigate this is that this study is really careful and transparent - most of them don’t tell you anything about their randomization method. I would be shocked if other studies don’t have all these problems and worse. On the other hand, the point isn’t to be fair, it’s to be right. And this is a potential confounder. Not a huge one. But a potential one. I guess all we can do is try to bound the damage. Even if the confounding is 100% real and bad, there’s no way to make this study consistent with the crazy super-pro-ivermectin results of studies like Espitia-Hernandez and Aref. And even if we deny any confounding, we see the same slight pro-ivermectin trend - 86 hospitalizations vs. 95 - that we’ve seen in so many other studies. Nothing is going to make me believe that this isn’t in the top 33% of studies we’ve been looking at, so let’s add it as grist for the meta-analysis (though maybe not quite as much grist as its vast size indicates) and move on, angrily. Buonfrate et al: An Italian RCT. Patients were randomized into low-dose ivermectin (32), placebo (29), or high-dose ivermectin (32). Primary outcome was viral load on day 7. There was no significant difference (average of 2 in ivermectin groups, 2.2 in placebo group). They admit that they failed to reach the planned sample size, but did a calculation to show that even if they had, the trial could not have returned a positive result. Clinically, an average of 2 patients were hospitalized in each of the ivermectin arms, compared to 0 in the placebo arm - which bucks our previously-very-constant pro-ivermectin trend. Mayer et al: Not an RCT. Patients in an Argentine province were offered the opportunity to try ivermectin; 3266 said yes and become the experimental group, 17966 said no and became the control group. There were many obvious differences between the groups, but they all seemed to handicap ivermectin. There was a nonsignificant trend toward less hospitalization and significantly less mortality (1.5% vs. 2.1%, p = 0.03). While looking into this study, I learned the term “immortal time bias”. This means a period in between selection for the study and the beginning of study recording where patient outcomes are not counted. I think the problem here is that if you signed up for the system on Day X, and if you got sick before they could give you ivermectin, you were in the control group. See this Twitter thread, I have not confirmed everything he says. This only hardens my resolve to stay away from non-RCTs. Borody et al: Our last paper! …is it a paper? I can’t find it published anywhere. It mostly seems to be on news sites. Doesn’t look peer-reviewed. And it starts with “Note that views expressed in this opinion article are the writer’s personal views”. Whatever. 600 Australians were treated with ivermectin, doxycycline, and zinc. The article compares this to an “equivalent control group” made of “contemporary infected subjects in Australia obtained from published Covid Tracking Data”; this is not how you control group, @#!% you. Then it gets excited about the fact that most patients had better symptoms at the end of the ten-day study period than the beginning (untreated COVID resolves in about ten days). Why are these people wasting my time with this? Let’s move on. The Analysis If we remove all fraudulent and methodologically unsound studies from the table above, we end up with this: Gideon Meyerowitz-Katz, who investigated many of the studies above for fraud, tried a similar exercise. I learned about his halfway through, couldn’t help seeing it briefly, but tried to avoid remembering it or using it when generating mine (also, I did take the result of his fraud investigations into account), so they should be considered not quite independent efforts. His looks like this: He nixed Chowdhury, Babaloba, Ghauri, Faisal, and Aref, but kept Szenta Fonseca, Biber (?), and Mayer. There was correlation of 0.45, which I guess is okay. I asked him about his decision-making, and he listed a combination of serious statistical errors and small red flags adding up. I was pretty uncomfortable with most of these studies myself, so I will err on the side of severity, and remove all studies that either I or Meyerowitz-Katz disliked. We end up with the following short list: We’ve gone from 29 studies to 11, getting rid of 18 along the way. For the record, we eliminated 2/19 for fraud, 1/19 for severe preregistration violations, 10 for methodological problems, and 6 because Meyerowitz-Katz was suspicious of them. …but honestly this table still looks pretty good for ivermectin, doesn’t it? Still lots of big green boxes. Meyerowitz-Katz accuses ivmmeta of cherry-picking what statistic to use for their forest plot. That is, if a study measures ten outcomes, they sometimes take the most pro-ivermectin outcome. Ivmmeta.com counters that they used a consistent and reasonable (if complicated) process for choosing their outcome of focus, that being: If studies report multiple kinds of effects then the most serious outcome is used in calculations for that study. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. I’m having trouble judging this, partly because Meyerowitz-Katz says ivmmeta has corrected some earlier mistakes, and partly because there really is some reasonable debate over how to judge studies with lots of complicated endpoints. By this point I had completely forgotten what ivmmeta did, so I independently coded all 11 remaining studies following something in between my best understanding of their procedure and what I considered common sense. The only exception was that when the most severe outcome was measured in something other than patients (ie average number of virus copies per patient), I defaulted to one that was measured in patients instead, to keep everything with the same denominator. My results mostly matched ivmmeta’s, with one or two exceptions that I think are within the scope of argument or related to my minor deviations from their protocol. Placebo vs. ivermectin groups sometimes differed in size, which I’ve adjusted for and rounded off. Probably I’m forgetting some reason I can’t just do simple summary statistics to this, but whatever. It is p = 0.15, not significant. This is maybe unfair, because there aren’t a lot of deaths in the sample, so by focusing on death rather than more common outcomes we’re pointlessly throwing away sample size. What happens if I unprincipledly pick whatever I think the most reasonable outcome to use from each study is? I’ve chosen “most reasonable” as a balance between “is the most severe” and “has a lot of data points”: Now it’s p = 0.04, seemingly significant, but I had to make some unprincipled decisions to get there. I don’t think I specifically replaced negative findings with positive ones, but I can’t prove that even to myself, let alone to you. [UPDATE 5/31/22: A reader writes in to tell me that the t-test I used above is overly simplistic. A Dersimonian-Laird test is more appropriate for meta-analysis, and would have given 0.03 and 0.005 on the first and second analysis, where I got 0.15 and 0.04. This significantly strengthens the apparent benefit of ivermectin from ‘debatable’ to ‘clear’. I discuss some reasons below why I am not convinced by this apparent benefit.] (how come I’m finding a bunch of things on the edge of significance, but the original ivmmeta site found a lot of extremely significant things? Because they combined ratios, such that “one death in placebo, zero in ivermectin” looked like a nigh-infinite benefit for ivermectin, whereas I’m combining raw numbers. Possibly my way is statistically illegitimate for some reason, but I’m just trying to get a rough estimate of how convinced to be) So we are stuck somewhere between “nonsignificant trend in favor” and “maybe-significant trend in favor, after throwing out some best practices”. This is normally where I would compare my results to those of other meta-analyses made by real professionals. But when I look at them, they all include studies later found to be fake, like Elgazzar, and unsurprisingly come up with wildly positive conclusions. There are about six in this category. One of them later revised their results to exclude Elgazzar and still found strong efficacy for ivermectin, but they still included Niaee and some other dubious studies. The only meta-analysis that doesn’t make these mistakes is Popp (a Cochrane review), which is from before Elgazzar was found to be fraudulent, but coincidentally excludes it for other reasons. It also excludes a lot of good studies like Mahmud and Ravakirti because they give patients other things like HCQ and azithromycin - I chose to include them, because I don’t think they either work or have especially bad side effects, so they’re basically placebo - but Cochrane is always harsh like this. They end up with a point estimate where ivermectin cuts mortality by 40% - but say the confidence intervals are too wide to draw any conclusion. I think this basically agrees with my analyses above - the trends really are in ivermectin’s favor, but once you eliminate all the questionable studies there are too few studies left to have enough statistical power to reach significance. Except that everyone is still focusing on deaths and hospitalizations just because they’re flashy. Mahmud et al, which everyone agrees is a great study, found that ivermectin decreased days until clinical recovery, p = 0.003? So what do you do? This is one of the toughest questions in medicine. It comes up again and again. You have some drug. You read some studies. Again and again, more people are surviving (or avoiding complications) when they get the drug. It’s a pattern strong enough to common-sensically notice. But there isn’t an undeniable, unbreachable fortress of evidence. The drug is really safe and doesn’t have a lot of side effects. So do you give it to your patients? Do you take it yourself? Here this question is especially tough, because, uh, if you say anything in favor of ivermectin you will be cast out of civilization and thrown into the circle of social hell reserved for Klan members and 1/6 insurrectionists. All the health officials in the world will shout “horse dewormer!” at you and compare you to Josef Mengele. But good doctors aren’t supposed to care about such things. Your only goal is to save your patient. Nothing else matters. I am telling you that Mahmud et al is a good study and it got p = 0.003 in favor of ivermectin. You can take the blue pill, and stay a decent respectable member of society. Or you can take the horse dewormer pill, and see where you end up. In a second, I’ll tell you my answer. But you won’t always have me to answer questions like this, and it might be morally edifying to observe your thought process in situations like this. So take a second, and meet me on the other side of the next section heading. … … … … … The Synthesis Hopefully you learned something interesting about yourself there. But my answer is: worms! As several doctors and researchers have pointed out (h/t especially Avi Bitterman and David Boulware), the most impressive studies come from places that are teeming with worms. Mahmud from Bangladesh, Ravakirti from East India, Lopez-Medina from Colombia, etc. Here’s the prevalence of roundworm infections by country (source). But alongside roundworms, there are threadworms, hookworms, blood flukes, liver flukes, nematodes, trematodes, all sorts of worms. Add them all up and somewhere between half and a quarter of people in the developing world have at least one parasitic worm in their body. Being full of worms may impact your ability to fight coronavirus. Gluchowska et al write: Helminth [ie worm] infections are among the most common infectious diseases. Bradbury et al. highlight the possible negative interactions between helminth infection and COVID-19 severity in helminth-endemic regions and note that alterations in the gut microbiome associated with helminth infection appear to have systemic immunomodulatory effects. It has also been proposed that helminth co-infection may increase the morbidity and mortality of COVID-19, because the immune system cannot efficiently respond to the virus; in addition, vaccines will be less effective for these patients, but treatment and prevention of helminth infections might reduce the negative effect of COVID-19. During millennia of parasite-host coevolution helminths evolved mechanisms suppressing the host immune responses, which may mitigate vaccine efficacy and increase severity of other infectious diseases. Treatment of worm infections might reduce the negative effect of COVID-19! And ivermectin is a deworming drug! You can see where this is going… The most relevant species of worm here is the roundworm Strongyloides stercoralis. Among the commonest treatments for COVID-19 is corticosteroids, a type of immunosuppresant drug. The types of immune responses it suppresses do more harm than good in coronavirus, so turning them off limits collateral damage and makes patients better on net. But these are also the types of immune responses that control Strongyloides. If you turn them off even very briefly, the worms multiply out of control, you get what’s called “Strongyloides hyperinfection”, and pretty often you die. According to the WHO: The current COVID-19 pandemic serves to highlight the risk of using systemic corticosteroids and, to a lesser extent, other immunosuppressive therapy, in populations with significant risk of underlying strongyloidiasis. Cases of strongyloidiasis hyperinfection in the setting of corticosteroid use as COVID-19 therapy have been described and draw attention to the necessity of addressing the risk of iatrogenic strongyloidiasis hyperinfection syndrome in infected individuals prior to corticosteroid administration. Although this has gained importance in the midst of a pandemic where corticosteroids are one of few therapies shown to improve mortality, its relevance is much broader given that corticosteroids and other immunosuppressive therapies have become increasingly common in treatment of chronic diseases (e.g. asthma or certain rheumatologic conditions). So you need to “address the risk” of strongyloides infection during COVID treatment in roundworm-endemic areas. And how might you address this, WHO? Treatment of chronic strongyloidiasis with ivermectin 200 µg/kg per day orally x 1-2 days is considered safe with potential contraindications including possible Loa loa infection (endemic in West and Central Africa), pregnancy, and weight <15kg. Given ivermectin’s safety profile, the United States has utilized presumptive treatment with ivermectin for strongyloidiasis in refugees resettling from endemic areas, and both Canada and the European Centre for Disease Prevention and Control have issued guidance on presumptive treatment to avoid hyperinfection in at risk populations. Screening and treatment, or where not available, addition of ivermectin to mass drug administration programs should be studied and considered. This is serious and common enough that, if you’re not going to screen for it, it might be worth “add[ing] ivermectin to mass drug administration programs” in affected areas! Dr. Avi Bitterman carries the hypothesis to the finish line: First two images are with all relevant studies; second two are a sensitivity analysis that removes some of the most dubious. The good ivermectin trials in areas with low Strongyloides prevalence, like Vallejos in Argentina, are mostly negative. The good ivermectin trials in areas with high Strongyloides prevalence, like Mahmud in Bangladesh, are mostly positive. Worms can’t explain the viral positivity outcomes (ie PCR), but Dr. Bitterman suggests that once you remove low quality trials and worm-related results, the rest looks like simple publication bias: This is still just a possibility. Maybe I’m over-focusing too hard on a couple positive results and this will all turn out to be nothing. Or who knows, maybe ivermectin does work against COVID a little - although it would have to be very little, fading to not at all in temperate worm-free countries. But this theory feels right to me. It feels right to me because it’s the most troll-ish possible solution. Everybody was wrong! The people who called it a miracle drug against COVID were wrong. The people who dismissed all the studies because they F@#king Love Science were wrong. Ivmmeta.com was wrong. Gideon Meyerowitz-Katz was…well, he was right, actually, I got the worm-related meta-analysis graphic above from his Twitter timeline. Still, an excellent troll. Also, the best part is that I ignorantly asked, in my description of Mahmud et al above: And it was! It was a fluke! A literal, physical, fluke! For my whole life, God has been placing terrible puns in my path to irritate me, and this would be the worst one ever! So it has to be true! The Scientific Takeaway About ten years ago, when the replication crisis started, we learned a certain set of tools for examining studies. Check for selection bias. Distrust “adjusting for confounders”. Check for p-hacking and forking paths. Make teams preregister their analyses. Do forest plots to find publication bias. Stop accepting p-values of 0.049. Wait for replications. Trust reviews and meta-analyses, instead of individual small studies. These were good tools. Having them was infinitely better than not having them. But even in 2014, I was writing about how many bad studies seemed to slip through the cracks even when we pushed this toolbox to its limits. We needed new tools. I think the methods that Meyerowitz-Katz, Sheldrake, Heathers, Brown, Lawrence and others brought to the limelight this year are some of the new tools we were waiting for. Part of this new toolset is to check for fraud. About 10 - 15% of the seemingly-good studies on ivermectin ended up extremely suspicious for fraud. Elgazzar, Carvallo, Niaee, Cadegiani, Samaha. There are ways to check for this even when you don’t have the raw data. Like: The Carlisle-Stouffer-Fisher method: Check some large group of comparisons, usually the Table 1 of an RCT where they compare the demographic characteristics of the control and experimental groups, for reasonable p-values. Real data will have p-values all over the map; one in every ten comparisons will have a p-value of 0.1 or less. Fakers seem bad at this and usually give everything a nice safe p-value like 0.8 or 0.9.
Inline links: ivmmeta.com, https://substackcdn.com/image/fetch/$s_!8y_b!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F4e9f8e07-6611-4797-b775-8c2e529ed69c_1453x511.png, Elgazzar et al:, here, Chowdury et al, Espitia-Hernandez et al:, deviated from its preregistration, https://substackcdn.com/image/fetch/$s_!nJOk!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fda0f378f-c7e9-446c-909b-b870b062fd39_589x444.png, Carvallo et al:, another Carvallo paper was retracted, Mahmud et al:, https://substackcdn.com/image/fetch/$s_!ST60!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F1ff4783b-1473-4413-9230-8b15a5549208_500x469.gif, Szenta Fonseca et al:, Cadegiani et al:, a BMJ article, a deeper dive, https://substackcdn.com/image/fetch/$s_!ARca!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7fe429e5-dba6-4b59-b46f-a2345b6acaf4_1080x720.jpeg, Ahmed et al:, Chaccour et al:, Ghauri et al:, Babaloba et al:, https://substackcdn.com/image/fetch/$s_!f598!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F0238280a-236e-47f5-9db6-7c35c07c5fc2_520x393.jpeg, https://substackcdn.com/image/fetch/$s_!SRpb!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb5271fbd-b82a-4e34-9787-8b3aa6e8d2f6_595x522.png, https://substackcdn.com/image/fetch/$s_!cKHm!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Ff9be5d50-858b-4c3a-bef7-a312df762eda_638x549.png, Ravakirti et al:, Bukhari et al:, Mohan et al:, Biber et al:, the preregistration, Elalfy et al:, https://substackcdn.com/image/fetch/$s_!B_IH!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F4d3559ee-a058-44cc-9b38-09b78a0f5035_1352x1070.png, https://substackcdn.com/image/fetch/$s_!9mI_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fbffceed7-c84a-45c1-abfe-1fb2706dc383_483x674.png, Lopez-Medina et al:, Roy et al:, Chahla et al:, Mourya et al:, Loue et al:, Table 1, Merino et al:, never works, Faisal et al:, Aref et al:, https://substackcdn.com/image/fetch/$s_!-FoK!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Ff6de79b6-091b-4c13-b7be-715c9bb194a7_986x810.jpeg, Krolewiecki et al:, Vallejos et al:, TOGETHER Trial:, here, https://substackcdn.com/image/fetch/$s_!7X0m!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F1f65fd44-58b9-4489-a934-02a5a7330499_706x768.png, Buonfrate et al:, Mayer et al:, immortal time bias, this Twitter thread, Borody et al:, https://substackcdn.com/image/fetch/$s_!Wpjs!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F2d8a451b-b1fc-44e5-ae67-b1506e491762_914x657.png, https://substackcdn.com/image/fetch/$s_!DOjA!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F17d5827a-38da-4a99-beb3-c3018df5c633_920x604.png, https://substackcdn.com/image/fetch/$s_!GX1n!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fc692fec8-a450-4579-b337-c72bec060970_912x298.png, https://substackcdn.com/image/fetch/$s_!YcH4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Ff36db98e-e653-44da-906c-20312b1689a3_468x205.png, https://substackcdn.com/image/fetch/$s_!jbcL!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fd189a844-daf2-4199-bb2e-830d4fc64415_468x206.png, later revised their results to exclude Elgazzar, Popp, https://substackcdn.com/image/fetch/$s_!2B6r!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F505c5ac4-3fe8-47a4-8505-dab80601b44d_416x198.png, Avi Bitterman, David Boulware, https://substackcdn.com/image/fetch/$s_!JWWh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fac9e4f34-f9cc-40f2-9d83-da4e7178fad7_772x330.png, source, Gluchowska et al, the WHO, carries, https://substackcdn.com/image/fetch/$s_!xExE!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5da21781-249c-4e59-b616-9f23d83cc044_2048x1184.jpeg, https://substackcdn.com/image/fetch/$s_!4SMr!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fdcd6e4b2-37f7-4602-93d5-2581c3b27a60_700x432.png, https://substackcdn.com/image/fetch/$s_!-6n2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7fd6e8f4-093e-4e02-bce7-363615146c9c_2228x1346.jpeg, https://substackcdn.com/image/fetch/$s_!CPZs!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb0425847-198a-4bd3-a63b-149f15d147ba_700x432.png, https://substackcdn.com/image/fetch/$s_!H3rK!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F9972491b-25b0-4c06-8aca-86fce102ae63_666x147.png, even in 2014, The Carlisle-Stouffer-Fisher method
Thanks to everyone who commented on my recent post Ivermectin: Much More Than You Wanted To Know.
Inline links: Ivermectin: Much More Than You Wanted To Know
Let’s start with the negative comments. Leading pro-ivermectin website ivmmeta.com understandably disagreed with my fisking of them. They have a section where they respond to critics (see responses to Gideon Meyerowitz-Katz, to the BBC, to the parasitic worm hypothesis, and to someone named AT who they won’t explain further). I was honored to also get a response here. They write:
Inline links: Gideon Meyerowitz-Katz, the BBC, the parasitic worm hypothesis, someone named AT who they won’t explain further
We note a few limitations and apparent biases in the SA/SSC ivermectin analysis.
When I reviewed Vitamin D, I said I was about 75% sure it didn’t work against COVID. When I reviewed ivermectin, I said I was about 90% sure.
Another way of looking at this is that I must think there’s a 25% chance Vitamin D works, and a 10% chance ivermectin does. Both substances are generally safe with few side effects. So (as many commenters brought up) there’s a Pascal’s Wager like argument that someone with COVID should take both. The downside is some mild inconvenience and cost (both drugs together probably cost $20 for a week-long course). The upside is a well-below-50% but still pretty substantial probability that they could save my life.
Inline links: Pascal’s Wager
I’m going to guess it’s not true, because I’ve become pretty critical of these people’s methodology since doing the ivermectin review. Also, curcumin is a PAIN (pan-assay interference compound, ie a substance with weird chemical properties that make every test seem positive, so if you do chemical tests to see whether it activates eg coronavirus-fighting immune cells, it will always say yes). This means people are always publishing exciting papers about it and alternative medicine people are always getting really enthusiastic about it and suggesting it as the cure for everything (eg depression).
Inline links: pan-assay interference compound, depression
4: Dr. Bitterman, one of the researchers who came up with the ivermectin-effects-are-from-worms hypothesis, is defending his idea from some of the concerns you guys brought up in the comments. For example, in response to a comment that hyperinfection syndrome is rare, he writes:
Inline links: you guys brought up in the comments, writes
5: Alexandros Marinos, whose pro-ivermectin views I argued against in the same comments post, has finally started a Substack and written up those views at length. Among his interesting findings are that keeping all of the studies mentioned on ivmmeta, removing the ones I think are bad, removing the ones ivmmeta itself thinks are bad, and removing the ones that leading anti-ivermectin researcher Gideon Meyerowitz-Katz thinks are bad - all give about the same relative risk result (by ivmmeta’s methodology), somewhere around 0.3 or 0.4 (Marinos thinks that my and ivmmeta’s exclusions are similar around 0.3, and GMK’s exclusions are different around 0.4, but this seems like splitting hairs to me, since all three are overwhelmingly positive by these standards). I think this is an interesting finding about how (at least when critiquing ivmmeta) it’s probably not worth arguing over which studies to include or not, so much as about the overall methodology for how we interpret the studies remaining.
In terms of the more polemical points, I might or might not write a longer response later. Right now the point I think is most important is that Marinos sort of grants that many of the substances with many positive studies probably don’t work - but says ivermectin is different because it has more studies and stronger effects than the others. I think the stronger effects are a bit exaggerated - the graphic that Marinos presents shows it’s pretty similar to melatonin, anti-androgens, and a bunch of other things - but I will grant that it has significantly more studies.
3: The discussion on ivermectin also continues: ivermectin supporters counterargue against what I said on my last open thread; Shakoist on Substack defends me.
Inline links: counterargue against what I said, Shakoist on Substack defends me
In the midst of all the hype about ivermectin and hydroxychloroquine, scientists put together the giant 4,000-person TOGETHER trial, intended to test all these exciting COVID early treatments. You know what happened next: ivermectin and hydroxychloroquine crashed and burned.
But a different drug, the SSRI antidepressant fluvoxamine, actually did really well! It decreased COVID hospitalizations by about 30% - not the perfect cure rate the rumors attributed to ivermectin, but a substantial decrease. Given the size and professionalism of this study, and another smaller one that also got positive results, I and many others take Luvox pretty seriously. At this point I’d give it 60-40 it works.
I conclude that the risk-benefit calculation probably favors using Luvox. And I’m not alone here. Johns Hopkins University’s COVID treatment guidelines recommend fluvoxamine for appropriate COVID patients. Some leading psychiatrists, especially the Washington University psychiatrists who helped discover the new indication, support fluvoxamine for appropriate COVID patients. Many of the epidemiologists and statisticians most instrumental in debunking the hype around ivermectin have spoken out in favor of fluvoxamine, saying this one is the real deal (1, 2). The National Institute of Health hasn’t quite come out in support, but they have taken the unusual step of not disrecommending fluvoxamine the same as they disrecommend every other oral early COVID treatment, saying that the evidence "provides the sort of flexibility for the treating clinician to go either way".
Last year I explained why I didn't believe ivermectin worked for COVID. In a subsequent discussion with Alexandros Marinos, I think we agreed on something like:
Inline links: didn't believe ivermectin worked
1. If you just look at the headline results of ivermectin studies, it works. 2. If you just do a purely mechanical analysis of the ivermectin studies, eg the usual meta-analytic methods, it works. 3. If you try to apply things like human scrutiny and priors and intuition to the literature, this is obviously really subjective, but according to the experts who ought to be the best at doing this kind of thing, it doesn't work. 4. But experts are sometimes biased. 5. F@#k.
In the end, I stuck with my believe that ivermectin probably didn’t work, and Alexandros stuck with his belief that it probably did. I stuck with the opinion that it’s possible to extract non-zero useful information from the pronouncements of experts by knowing the rules of the lying-to-people game. There are times when experts and the establishment lie, but it’s not all the time. FOX will sometimes present news in a biased or misleading way, but they won’t make up news events that never happen. Experts will sometimes prevent studies they don’t like from happening, but they’re much less likely to flatly assert a clear specific fact which isn’t true.
COVID 22. Fewer than 10K daily average official COVID cases in US in December 2022: 20% 23. Fewer than 50K daily average COVID cases worldwide in December 2022: 1% 24. >66% US population fully vaccinated (by current standards) against COVID: 70% 25. India's official case count is higher than US: 5% 26. Medical establishment reverses course and officially says any of Vitamin D, HCQ, or ivermectin is actually effective against COVID: 1% 27: FDA approves a COVID indication for fluvoxamine: 60% 28. Some new variant not currently known is greater than 25% of cases: 60% 29. Most people I see in the local grocery store 12/31/22 are wearing masks: 60% 30. Masks still required on domestic flights: 60% 31. CDC recommends that triple-vaxxed people get at least one more vax: 70% 32. China has fewer than 100,000 COVID cases this year (official estimate): 30%
2: In my ivermectin post, about a third of the way down, are two analyses of whether a raw meta-analysis makes it look like ivermectin works. I concluded that they showed marginal effect, but that this was probably due to other factors (eg antiparasitic properties). A reader points out that it was wrong to do this by t-test, and I should have used a DerSimonian-Laird test because it’s a meta-analysis, which would have shown a clear (not marginal) effect, so I updated the post and my Mistakes page. More recently, another reader has commented that a DerSimonian-Laird test is also inappropriate because the studies aren’t homogenous, and now I’m not sure which test is appropriate or what result it would give - but it definitely wasn’t the one I originally tried. I don’t think this significantly alters the overall conclusion of the post, which was that the apparent effect (whether marginal or clear) was better explained by other things.
In November 2021, I posted Ivermectin: Much More Than You Wanted To Know, where I tried to wade through the controversy on potential-COVID-drug ivermectin. Most studies of ivermectin to that point had found significant positive effects, sometimes very strong effects, but a few very big and well-regarded studies were negative, and the consensus of top academics and doctors was that it didn’t work. I wanted to figure out what was going on.
Inline links: Ivermectin: Much More Than You Wanted To Know
After looking at twenty-nine studies on a pro-ivermectin website’s list, I concluded that a few were fraudulent, many others seemed badly done, but there were still many strong studies that seemed to find that ivermectin worked. There were also many other strong studies that seemed to find that it didn’t. My usual heuristic is that when studies contradict, I trust bigger studies, more professionally done studies, and (as a tiebreaker) negative studies - so I leaned towards the studies finding no effect. Still, it was strange that so many got such impressive results.
I thought the most plausible explanation for the discrepancy was Dr. Avi Bitterman’s hypothesis (now written up here) that ivermectin worked for its official indication of treating parasitic worms. COVID is frequently treated with steroids, steroids prevent the immune system from fighting a common parasitic worm called Strongyloides, and sometimes people getting treated for COVID died of Strongyloides hyperinfection. Ivermectin could prevent these deaths, which would mean fewer deaths in the treatment group than the control group, which would look like ivermectin preventing deaths from COVID in high-parasite-load areas (like the tropics) but not low-parasite-load areas (like temperate zones). This explained some of the mortality results, with the other endpoints likely being because of publication bias.
Inline links: here
3: Comment of the week: Meropenem fills in more details about the Cadegiani case mentioned in my ivermectin article.
Inline links: fills in more details about the Cadegiani case
I’ve been looking into the world of YouTube streamers; if you want to make it big, you need to have a beef with some other online celebrity. Fine; I choose Chris Kavanagh, who tweeted about me recently: astralcodexten.substack.com/p/response-to-… ","username":"C_Kavanagh","name":"Chris Kavanagh","profile_image_url":"","date":"Tue Feb 14 07:46:17 +0000 2023","photos":[{"img_url":"https://pbs.substack.com/media/Fo6TtYEaYAIxYu5.png","link_url":"https://t.co/GZpY9gU9V3","alt_text":null},{"img_url":"https://pbs.substack.com/media/Fo6Uiv2aMAIj_P_.png","link_url":"https://t.co/GZpY9gU9V3","alt_text":null}],"quoted_tweet":{},"reply_count":0,"retweet_count":14,"like_count":100,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":false}" data-component-name="Twitter2ToDOM"> @C_Kavanagh I think it probably persuaded some people that mainstream experts wouldn't have reached to get vaccinated instead of taking ivermectin","username":"RachelBCam","name":"Rachel","profile_image_url":"","date":"Tue Feb 14 09:49:06 +0000 2023","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":2,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":false}" data-component-name="Twitter2ToDOM"> @RachelBCam And for that I’m glad. But my critique here is to some extent orientated towards the rationalist community and what it says it does vs. what I see. It isn’t ‘rational’ to ignore conspiracy ecosystems and how they distort things & argue. It actually gives bad heuristics.","username":"C_Kavanagh","name":"Chris Kavanagh","profile_image_url":"","date":"Tue Feb 14 15:47:19 +0000 2023","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":0,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":false}" data-component-name="Twitter2ToDOM"> @RachelBCam Imagine Scott’s blog with some more generous degrees of freedom exercised in his analysis, suddenly you have a more positive result & the impression the issue is a genuine controversy. Indeed, this is what people like Alexandros did in response.","username":"C_Kavanagh","name":"Chris Kavanagh","profile_image_url":"","date":"Tue Feb 14 15:50:05 +0000 2023","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":0,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> This is an admirably concise encapsulation of everything I despise, so I want to respond. But first, a personal story:
A picture my instructor took of me at one of the ruins. Nobody was under any obligation to handhold me out of my Atlantis beliefs. But the #1 Google rank for “site about how Atlantis isn’t real” is a scarce resource. Article space on skeptic blogs (podcasts were still years into the dystopian future at this point) was a scarce resource. And when people frittered these scarce resources away on a thousand identical pieces saying “lol you’re stupid and racist if you believe this, haven’t you heard that conspiracies are always wrong?” - and never on any explanation of the GIANT UNDERWATER PYRAMIDS - yes, I feel like I was wronged. Eventually I lifted myself up by my own bootstraps. I studied some of the relevant history myself (less impressive than it sounds, Wikipedia was just coming into existence around this time). I learned enough about geology to understand on a gut level how natural processes can sometimes produce rocks that are really really artificial-looking - yes, even as artificial-looking as the ones in the picture above. More important, I learned something like rationality. I learned how to make arguments like the one I use in The Pyramid And The Garden. I realized that, for all their skill at finding anomalies, the Atlantis books couldn’t agree on a coherent narrative of their own. Some placed Atlantis in the Atlantic, others in the Pacific, others in Antarctica; some used it to explain artifacts from long after others said that it fell. For a while if I squinted I could sort of kind of smush them into a single story, but that story had even more anomalies than normal historians’. Eventually I gave up and joined the mainstream. I’m not angry at Graham Hancock. I see no evidence he has ever been anything but a weird, well-meaning guy who likes pyramids a little too much. But I feel a burning anger against anti-conspiracy bloggers, anti-conspiracy podcasters, and everyone else who wrote “lol imagine how stupid you would have to be to believe in Atlantis” style articles. Either these people didn’t understand the arguments for and against Atlantis, or they did. If they didn’t, they were frauds, claiming expertise in a subject they knew nothing about. If they did, then at any moment they could have saved me from a five year wild-goose-chase - but chose not to, because it was more fun to insult me. II. Kavanagh makes fun of me for writing 25,000 words on ivermectin. I agree this might not have been the best use of my time, and I would accept this criticism from anyone except Kavanagh - who’s devoted his whole career to thinking about ivermectin and ideas closely aligned to it. There’s a Hindu legend (maybe apocryphal?) about an atheist philosopher who spends literally every second of every day denouncing God. When he dies, God welcomes him into the highest heaven, praising him as a great yogi - for he never let his consciousness stray from awareness of God even for one moment. If by some inexplicable theological anomaly Bret Weinstein turns out to be God, Chris Kavanagh is definitely going to the highest heaven. So Kavanagh’s complaint can’t be that I’m thinking about this question at all. He sort of hints at a complaint where it took me too long to figure out that ivermectin didn’t work - shouldn’t I have been able to do it without the long review? But I clearly said on my first post on the subject that I had long since decided it to my own satisfaction, and was just trying to clear up some of my remaining questions. What is his complaint? At the risk of putting words in his mouth, two parts of his comment stand out to me as having important arguments: I interpret this as - to even try to “evaluate the evidence” at all is a mistake, because it suggests there might be evidence on both sides. Instead, you should admit that some people are idiots who believe things there’s no evidence for, and move on. But the problem with “if studies had supported ivermectin as an effective treatment, it would have been adopted”, is that about thirty different studies did support it, and it was adopted in several countries, mostly in Latin America. The first few meta-analyses of ivermectin found that it worked! I’m not defending ivermectin here. I think there was a reasonable explanation of this: a combination of fraud, poor methodology, publication bias, and maybe Strongyloides infections. But until someone tells you the reasonable explanation, there’s no reasonable explanation! It’s like the giant underwater pyramids. If I go diving and see the giant underwater pyramids, and you just say “LOL, you are stupid, don’t you know conspiracy theories aren’t real?”, you’re not going to convince me! I wanted to give the reasonable explanation, in terms that people could understand. Before doing any research, I had some intuitive guesses about what the reasonable explanation would look like - something something methodological problems something something small studies. But this, itself, isn’t a reasonable explanation. It’s an IOU for a reasonable explanation. I agree that many people are unreasonable and don’t respond to reasonable explanations. I think sometimes this is genetic or something and can’t be helped, but other times it comes after a hundred different experiences where you want reasonable explanations and don’t get them and also people are jerks to you and you learn that the establishment can’t be trusted. Mahabharata: “Even after ten thousand explanations, the fool is no wiser, but the wise man requires only two thousand five hundred.” If I had had to suffer through a few more skeptics calling me racist because I wanted to know why there were giant underwater pyramids, I probably would have believed in Atlantis even harder, out of spite, and never talked myself out of it. And then when ivermectin came along, I would have thought “Scientists? Experts? They’re the guys who are so dumb they can’t even figure out Atlantis existed when there are giant underwater pyramids right in front of their eyes. Screw them, I’m listening to Bret Weinstein.” I side with the Christians. There may be people so far gone into the outer darkness that they can’t be saved, but you are forbidden from ever believing with certainty that any specific individual is in this category. Act as if everyone is one good deed away from falling to their knees and acknowledging the light of Jesus. Moving on: @RachelBCam Imagine Scott’s blog with some more generous degrees of freedom exercised in his analysis, suddenly you have a more positive result & the impression the issue is a genuine controversy. Indeed, this is what people like Alexandros did in response.","username":"C_Kavanagh","name":"Chris Kavanagh","profile_image_url":"","date":"Tue Feb 14 15:50:05 +0000 2023","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":0,"like_count":0,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> This is the part I have the most trouble interpreting charitably. I can’t stop reading it as “doing good science is a near occasion of sin for doing bad science”. It sounds kind of like fideism, the belief (more common in atheists’ imaginations than real religion) that somebody who reasons their way to belief in God is a sinner, because a real saint would have believed through blind faith, without having to reason. The best I can do is to think of this as a PR argument: it looks bad to be treating these kinds of questions as live issues. I generally don’t like PR arguments, but while we’re having them: doesn’t it kind of look bad for one side to be promoting fideism? The ivermectinist slogan is “do your own research”. Kavanagh’s apparent slogan is “don’t do research” - even if you get it right, having tried it at all makes you impure. If there’s some argument I know nothing about - pro- vs. anti- skub, perhaps - and all I’ve heard is that the pro-skub people say that you should look at evidence and decide rationally based on your best judgment, and the anti-skub people say you should never look at evidence and have to trust them - I’m already 90-something percent sure pro-skub are the good guys. My model of the PR here - of the overall milieu and psychological factors that turn people into conspiracists - is that they spot some giant underwater pyramids, compelling-seeming facts that appear to point toward conspiracy. These facts have alternative explanations, but these alternatives are less compelling and harder to explain. Realistically some people are going to get caught up in the conspiracy’s superior first-level compellingness and you can’t help them. But other people are on the fence and can be talked down. This is the job of the pro-mainstream-anti-conspiracy people. Instead of doing their job, these people: ignore them
Inline links: The Pyramid And The Garden, so far gone into the outer darkness that they can’t be saved, pro- vs. anti- skub
I discussed this in this other post on ivermectin, where I describe how a false pro-ivermectin claim provoked an equally false anti-ivermectin response provoked an equally false pro-ivermectin response and so on, both sides living entirely in their biases and imagination for several cycles. “Conspiracy ecosystems” don’t have some exotic reasoning style we can’t possibly understand. They have normal reasoning, and are just slightly worse at applying CONSTANT VIGILANCE than everyone else.
Inline links: this other post on ivermectin, CONSTANT VIGILANCE
I liked your posts on ivermectin, but I do think there is a genuine cost to posts like it, which Kavanagh seems to me to be at least hinting at.
When people criticize me, they act like I’m 100% taking the Intellect perspective. I admit I have some sympathies in that direction. Ivermectin is an especially clear case: for a while, most doctors and epidemiologists suspected that it worked, because there were impressive studies in favor. Then those impressive studies were gradually found to be flawed or fraudulent, better studies gradually came out showing that it didn’t work, and the experts gradually shifted to doubting it. At what point in this process - which second of which day - did it switch from plausible-but-false scientific theory to conspiracy theory? Obviously there’s no single moment (cf. philosophy of science’s long failure to solve the demarcation problem). So the difference between a good scientific theory and a conspiracy theory is definitely a spectrum.
Inline links: demarcation problem
This is my favorite illusion. The top and bottom chess sets are the same color, and only look black vs. white because of contrast effects. This one is harmless, because it affects everyone equally, nobody cares about it too much, and you can easily check via Paint or Photoshop or something. The Infohazard perspective claims conspiracy theories are potentially this convincing, but in a much more pernicious way: they only hit some people (not necessarily the dumb ones!), and they subvert the checking process so that it appears to give pro-conspiracy results (see Trapped Priors). All factual claims can become the basis for emotional/social coalitions. I wrote here about how an extremely pointless question - whether Abu Bakr or Ali should have been political leader of the Arabian empire in 632 AD - produced the Sunni/Shia split, whose different sides went on to develop different political systems, aesthetics, and philosophies, and to hate each other even today. It’s easy for a scissor statement like “is the chess set black or white?” to become the basis for a social/political movement, which then evolves the anti-epistemology necessary to protect its own existence (I’m still in awe of the way ivermectin advocates have made “small studies are more trustworthy than big studies” sound like a completely reasonable and naturally-arrived-at position). I agree that everyone (including smart people) needs to be constantly vigilant of this possibility, and that any suggestion otherwise risks placing a stumbling block before the blind. II. Where I differ from Alexander is something like - quick analogy, there used to be a thing where some therapists would avoid asking patients if they were suicidal, because they didn’t want to “plant the idea” in their head. People would argue that you shouldn’t talk at length about the reasons for and against suicide, because that was highlighting it as an option, or dignifying it with a response. Most studies have since weighed in against this perspective. Depressed people aren’t idiots. They are aware that committing suicide is an option. You will never be able to suppress all knowledge of suicide’s existence, and “suddenly triggering the latent knowledge” isn’t a thing. Talking about it openly just means . . . it can be talked about it openly. We currently live in a world where: There are big studies in prestigious journals finding that ivermectin works
Women are using hormonal birth control, and men are either absorbing it through the water supply, or missing cues of fertility that would otherwise increase sperm production through to some galaxy-brained evo psych daisy chain. Conclusions And Predictions To grind my usual axe: this is the kind of complex issue that makes me wary of bias arguments and the “misinformation” framing. If it turns out this was real all along, people will point to the hundreds of studies demonstrating it and prestigious scientists pushing it. Doubters will be compared to global warming denialists, ignoring science in order to continue their fantasy of consequence-free pollution. And if it turns out this was totally fake, people will talk about how this was a classic panic of fragile masculinity (“our precious bodily fluids!”). They’ll place it alongside ivermectin in the annals of “don’t trust small noisy studies”. In retrospect, it will feel obvious that one side was right all along and the other was laden with junk science, biases, and all the classic red flags for conspiracy theories. We’ll be told we should have “trusted the experts” - either experts like Levine and Swann saying it’s real, or experts like Auger and Fisch saying it’s overblown. But right now, not knowing which side is right, we don’t have any of these easy outs. We have to actually reason under uncertainty! I’m not actually very good at this in this situation, and I’m pretty split about how concerned to be. Trying to turn this into concrete predictions, with a market for each: 1: In twenty years, the best evidence will suggest that sperm counts have been substantially declining across most of the world: 50% Auger and Fisch make great points about confounders and measurement difficulties. Nobody denies how noisy these data are. I think the case in their favor is that there are so many studies that you’d need a strong directional bias to explain the strong directional finding - plus the sheer magnitude of the effect, from counts of 100 million + in the Fifties to ~40 million today, is impressive. I wrote this post at the same time I wrote my response to Alexandros Marinos on ivermectin. If I applied the same hyper-skeptical eye to these studies that I apply to the ivermectin studies, they fail. But I admitted I was more cynical than usual about the ivermectin studies because of the many large RCTs that found no effect. Should I be more forgiving here? I’m not sure. 2: In twenty years, the best evidence will show very substantial (>one quarter) declines in fertility rate (relative to couples trying equally hard to conceive in the past) due to decreasing sperm count, in at least one country: 20% If sperm counts are declining as fast as Swann and Levine think, this should definitely happen. So why is my number for this prediction so much lower than for the one above? Partly because the decline could be sublinear. Partly because the decline could stop - either because we identify the cause and correct it, or for more mysterious reasons. But partly it’s just an unjustifiable penalty for something that it seems very hard to imagine happening. 3: Conditional on a consensus 20 years from now being that sperm count was declining, scientists will believe the most important factor is: Plastics: 25%
Inline links: bias arguments, the “misinformation” framing
Five years later, we can’t stop talking about COVID. Remember lockdowns? The conflicting guidelines about masks - don’t wear them! Wear them! Maybe wear them! School closures, remote learning, learning loss, something about teachers’ unions. That one Vox article on how worrying about COVID was anti-Chinese racism. The time Trump sort of half-suggested injecting disinfectants. Hydroxychloroquine, ivermectin, fluvoxamine, Paxlovid. Those jerks who tried to pressure you into getting vaccines, or those other jerks who wouldn’t get vaccines even though it put everyone else at risk. Anthony Fauci, Pierre Kory, Great Barrington, Tomas Pueyo, Alina Chan. Five years later, you can open up any news site and find continuing debate about all of these things.
This graph shows that around 9% of comments will contain at least one token indicating the comment is discussing a sensitive topic, with a range of about 6% to 14%, disregarding the very early years where small sample size made the data more variable. There wasn’t any one ‘sensitive’ token in particular which correlated exceptionally well with the rise and fall of this 6% to 14%, which implies to me that we have correctly identified a general factor of ‘willingness to discuss sensitive topics’ (or possibly that the peaks and troughs correspond to peaks and troughs in the external landscape – ie specific touchpoints and lulls in the Culture War – which would also be fine for the purpose we’re putting it to). This is an imperfect measure because it only tracks if someone is using a sensitive phrase and not whether they are using it in a heretical way (cf. ‘fifty Stalins’ here). However, I thought in the context of ACX posts the approach was probably reasonable – sensitive phrases are only likely to appear if they are being discussed a lot, and we know from the previous section that discussion depth is high both now and during the 2016 peak engagement period. It isn’t necessarily true that deep discussion implies spirited debate - some political discussions on reddit can go into the thousands of comments without anyone ever actually expressing a counter-orthodoxy view – but I think in the specific context of ACX it is reasonable, because we don’t generally have norms of expressing substanceless agreement. Hopefully, therefore, the changing ratio of socially or professionally sensitive phrases to phrases not included in my dictionary would tell us something about the willingness of the comment section to engage in potentially emotive discussions at any point in time. The relationship of occurrence of these tokens to engagement with the comment section is hard to draw clear conclusions from – although the peak does indeed look to be about 2016 or 2017 the data are noisy, and strongly affected by the choice of words to include in my dictionary. I picked the dictionary before I saw the data, but perhaps a different set of words would have given a different result, especially if I had a better way of identifying sensitive discussions around COVID (‘ivermectin’ was the only COVID-related word I could think of that became politicised in the same way ‘microaggression’ or ‘misgender’ did). Nevertheless, I would say this gives some weak support to the idea that 2016 was a turning point in SSC Commentariat free speech norms (and strong support to the idea that the start of ACX was a low point for discussion of sensitive topics) I include below a few specific sensitive phrases which I thought were interesting. Do note the different scales on each graph. Of particular interest to me is the ‘SJW’ graph, which has a really clear peak at exactly the high point of Commentariat engagement. I will return to this graph later in the review. Politeness
I haven’t watched his videos, but they have names like You Could Be MUCH More Persuasive, The Persuasion Playbook (“Learn practical techniques to harness the power of persuasion”), and Persuasion Techniques That Will Improve Your Business And Life. Adams absolutely did not limit his interest in Trump’s persuasion to the media, and praised Trump (for example) using persuasion techniques to take down other Republican candidates. You can find his discussion of how Adams “publicly predicted Ben Carson’s demise” after Trump acted out a mocking version of Carson’s description of getting stabbed in the belt buckle (according to Adams, a masterful example of “visual persuasion”). Leo continues: A good example would be spinning a whole tale about him as an ‘ivermectin true believer’, when he was open about his skepticism. if you knew his history with medically-assisted suicide, you’d know he didn’t plan on fighting the cancer and only did IVM because his fans begged him. I half-apologize for this one. I didn’t try to “spin a whole tale” about Adams as “an ivermectin true believer”. What I said was: » “In 2024, diagnosed with terminal cancer, Adams decided to treat it via ivermectin, according to a protocol recommended by fellow right-wing contrarian Dr. William Makis. This doesn’t seem to me like a story about a cynic milking right-wingers for the grift. It sounds like a true believer.” I stand by that paragraph. I don’t think someone who was milking right-wingers as a cynical grift would have gone so far as to trust their recommendations on what to take for his cancer. I think Adams became a sincere right-winger, and so was willing to listen to right-wing medical advice. But I agree that it was written sloppily and sort of suggests he was an ivermectin true believer. He wasn’t, and I apologize for that. I later realized I didn’t need to read tea leaves about this - he says, very explicitly, in one of his books, that yes, after getting attacked by too many left-wing trolls, he decided to commit to fully joining the right wing: » “If you want to see the world more clearly, avoid joining a tribe. But if you are going to war, leave your clear thinking behind and join a tribe. Trumped joined the Republican tribe to win the presidency. Now I was joining the Trump tribe. For a war against Hillbullies [ie pro-Hillary Clinton bullies]. I was all in.” After I made some of these arguments to Leo, he said: I do think that people who listened to thousands of hours of him speaking off-the-cuff might have a better understanding than someone attempting to gain the same by reading a few of his old blog posts. This is a fair criticism. I tried listening to a couple of his shows, and they had a different, friendlier tone than his books / interviews / tweets. Arguably Adams thought of formal written communication as a place to do manipulation, and verbal communication as a cozier spot where he could relate to people normally and explain all the manipulation he was doing. @Ashwin V writes: If you knew anything about Scott, you would know that he never considered anyone a "lesser human" as you've so confidently asserted. He was streaming and trying to pass on his wisdom on his death bed. This was a response to my claim that Adams “longed to be a manipulator of lesser humans”. Several people including Ashwin objected that Adams didn’t see anyone as lesser, nor think of manipulation as demeaning. For example, nutter_just: “Your error is in thinking you must be a lesser human to be manipulable. My impression was Scott believed everyone was like this even himself which is why he believed self affirmations worked. It’s you manipulating your dumb self.” Again, I’ll half-apologize. I regret my exact framing (“lesser humans”), which I think was unnecessarily inflammatory since it implies he was sort of thinking in those terms. But I think he was doing a bad thing which requires that on some philosophical level he has to be treating other people as his lessers in an unacceptable way, even if he wasn’t consciously thinking that they were. I think trying to manipulate people is inherently demeaning to the dignity of humankind. Nor is it exonerating to say “I also manipulate myself” (even if this is true). For analogy, suppose that Adams was a literal telepathic mind controller. If he used his powers on himself (mind controlling himself to work harder), that sounds like a good lifehack. But if he used his powers to turn everyone else into his zombie slaves, he would be offending the dignity of humankind, and “I also use my powers on myself!” would be no excuse. There are a thousand edge cases, complications, things that are sort of manipulation but not quite, and ways that some of those things might be permissible for the greater good. But none of them change the fact that in the simplest and most typical of cases, like the telepathic mind controller with his zombie slaves, manipulation is wrong. One might object that there are simple, typical cases on the other side too. When a job candidate shaves, dresses nicely, and gives a firm handshake, this is in some sense “manipulating” the interviewer, since it’s an attempt to influence his decision through some channel other than facts. I can’t draw a perfect bright line here between the good and the bad cases, but I would apply tests like “is this an attempt to more effectively convey true information?” (eg when I shave, it conveys that I’m capable of remembering to shave and care a lot about the interview), “is this something where failing to do the thing would also convey even more information?” (eg if I didn’t shave, it would falsely suggest I really didn’t want the job), and “is this something where the target has basically given implied consent to this level of manipulation” (eg the interviewer wants and even hopes that people will dress nicely for the interview). I think some of Adams’ manipulations seem closer to the bad cases than the good ones. He wrote about the moment he decided to use his persuasion powers to convince America to elect Trump. One day when he was doing his dispassionate observer act, he heard about Hillary’s estate tax plan and realized it would cost his estate lots of money. He had no particular principled stance against it (“You can argue whether an estate tax is fair or unfair, but fairness is an argument for idiots and children”) but concluded that: This was personal. This was also the day I decided to move from observer to persuader. Until then I was happy to simply observe and predict. But once Clinton announced her plans to use government force to rob me on my deathbed, it was war. Persuasion war.” Accepting for the sake of argument that Adams’ persuasive powers are as impressive as he thinks, he manipulated thousands of people who might have stood to benefit from an estate tax, or who sincerely believed in fairness-based arguments for an estate tax, to vote against their own interests/beliefs, in order to enrich him personally1. I think this requires some sort of standpoint where you consider their agency and interests less important than your own, and that’s why I described him as wanting to manipulate “lesser humans”. This coexists with him often being very nice, with many people saying his podcast helped them become better people, etc. @janiesaysyay writes: This essay is a great demonstration of the kind of leftist, myopic thinking Scott [Adams] was fighting. This is how [Alexander] describes [Coffee With Scott Adams], one of the most influential online shows: » "I had been vaguely aware that he had some community around him, but on the event of his death, I tried watching an episode or two of his show. I couldn’t entirely follow..." “Some community"?! CWSA was one of the first long running, online, interactive, alternative news shows. Scott was a trailblazer host with his reasonable, thoughtful take on current events, often describing the "2 screens” views of both the left and right political opinions on current events. Scott [Adams]' question and answer discussions with his audience brought varied insights, and gave Americans a nuanced view of news. At the end of his life, Scott was highly influential in American thought, culture and politics. CWSA made it acceptable to be an American, someone who was proud of the country, unashamed of their race; proud of the culture, and proud of the heritage which built the country. This made me wonder whether I was underestimating the reach of Adams’ podcast, so I tried to find statistics. CWSA ranks 50th on Apple’s top 100 news/politics podcasts2. It’s very close to the rankings of Jen Psaki (Biden’s ex-press-secretary) and Al Franken (ex-Senator), but also to very many people I have never heard of. I’m not sure how to interpret this. Comparing YouTube subscribers of Adams and various other podcasts I’ve heard of, all numbers in thousands: Joe Rogan: 21,000
Inline links: You Could Be MUCH More Persuasive, The Persuasion Playbook, Persuasion Techniques That Will Improve Your Business And Life, writes, nutter_just, https://substackcdn.com/image/fetch/$s_!r4fL!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F7d643c5f-b24c-4f01-baad-963686d680da_560x174.jpeg, 1, writes, 2, https://substackcdn.com/image/fetch/$s_!wOcC!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F141d78d7-8756-4ed6-bc53-081bac795a0a_728x250.png
Adams wasn’t an ivermectin true believer, and although my piece very narrowly avoided saying that he was, I should have been clearer about this and avoided implying it.
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