Egypt

Article

Egypt is a recurring place in the Astral Codex Ten archive, appearing 21 times across 21 issues between April 22, 2021 and August 01, 2025. The archive places it in contexts such as “Egypt’s veneration of cats led to lots of folks wanting to have/gift cat mummies as spiritual protectors in graves”; “the US imported rags for paper production from Egypt on several occasions”; “ancient Egypt to illustrate a great balance of transport”. It most often appears alongside China, Israel, Europe.

Metadata

Category: Places
Mention count: 21
Issue count: 21
First seen: April 22, 2021
Last seen: August 01, 2025

Appears In

- China (9 shared issues)
- Israel (8 shared issues)
- Europe (7 shared issues)
- United States (7 shared issues)
- US (7 shared issues)
- Argentina (6 shared issues)
- Brazil (6 shared issues)
- France (6 shared issues)
- Google (6 shared issues)
- Rome (6 shared issues)
- Spain (6 shared issues)
- Africa (5 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.

Your Book Review: Are We Smart Enough To Know How Smart Animals Are?

April 22, 2021 · Original source

Read to: better understand and relate to your pet with a side helping of pure joy of learning. Each of these books gives an overview of what we know about the domestication process of each animal, which also serves as a mini-primer on what domestication is and how it works. Spoiler alert: cats are barely domesticated and have had way less intentional selective pressure placed on them by humans than dogs. Did you know friendly domesticated cats might be the product of the TEMPLE-INDUSTRIAL COMPLEX/CAPITALISM? Egypt's veneration of cats led to lots of folks wanting to have/gift cat mummies as spiritual protectors in graves, which led to kitty mills where cats were bred to turn into mummies (I know, sad). Any cats that didn't get along so well with the temple workers would either escape or not be allowed to breed (nobody wants to get the crap scratched out of them every time they bring the food), all of which would combine into selective pressure enforced over short (and therefore plentiful) generations for cats that get along with people.

Your Book Review: Double Fold

April 30, 2021 · Original source

Perhaps the best illustration of the constantly expanding area of historical interest is the huge trove of medieval Jewish documents that was discovered in the geniza at Cairo in the 19th century and mostly brought to Europe. In the beginning, only Biblical texts attracted much interest, especially ones that had been presumed lost in the original Hebrew. Later, during the 20th century, the researchers suddenly became excited by the documents left behind by medieval Jewish intellectuals – previously unknown manuscripts of works by Maimonides and Judah Halevi, some of them written in their own hand. A generation or two later, new scholars looked into the everyday documents left behind in the geniza – receipts, contracts, and IOU’s, and used them to construct a social history of medieval Jews in Egypt. As Adina Hoffman and Peter Cole write in the book Secret Trash, there is only one constant in the research into the contents of the Cairo geniza: whatever had been left aside as boring and irrelevant by one generation became the cornerstone of the next generation’s scholarly pursuits.

The second example is even more interesting. In the 1850s, the US imported rags for paper production from Egypt on several occasions, and several journalists at the time reported that the deliveries had consisted of mummy wrappings. At least one newspaper, the Syracuse Daily Standard, proclaimed to its readers that it was being printed on mummy paper. This could in principle be verified by molecular analysis, but unfortunately almost all the libraries which had carried print runs of the Daily Standard had thrown them away. It’s possible that this helped us avoid the mummies’ curse, though in my opinion, getting recycled a second time made them even angrier. Maybe having lost so much historical material was part of the curse.

Inline links: mummy paper

Your Book Review: The Accidental Superpower

May 21, 2021 · Original source

He uses ancient Egypt to illustrate a great balance of transport. The reliable water and rich soil of the Nile’s floodplains created near-perfect farming conditions, and the Nile itself allowed easy travel and trade throughout the valley. Combined with impenetrable desert borders, this geography “was one of the few places in the world where there was enough water to survive, and enough security to thrive.” Because of that, the “geography nearly guaranteed that the Egyptians would be on the road to civilization.” He gives us a quick run through Egyptian history to tell a story of that road, beginning with the settlement of the area about eight thousand years ago, consolidation into a single kingdom more than five thousand years ago, and then stagnation as the increasingly centralized government devoted more labor to monument building rather than technological progress, eventually being conquered by seafaring people seeking to rule the Mediterranean. 2

Inline links: 2

To escape our pre-civilization/hunter-gatherer days – Zeihan refers to this as “when life sucked” – the mechanism that he identifies is basically a typical economist’s story. Sedentary agriculture as invented by the Egyptians and other ancient cultures became a transformative technology, letting populations grow and devote labor and resources to non-farming purposes. From this, we got specialization, increased production, trade (particularly where there was easy transportation – population centers were always near water) and capital formation in a self-reinforcing cycle. For thousands of years after this transformative technology was introduced, incremental improvements in agriculture and other areas followed, but “a robust, secure, and sustainable food supply” was the base of any civilization.

American foreign policy comes off looking surprising competent through Zeihan’s story. In describing the history of Bretton Woods, he runs through some key participants and highlights the benefits of their membership. India, hurting the Soviets in South Asia; Sweden, hurting them in the Baltic; Argentina and Egypt, limiting their influence in South America and the Middle East; and most significantly, China, depriving them of their best ports. Why did America fight in Korea and Vietnam? To demonstrate the value of the security guarantee component of the Bretton Woods regime (“if the Americans proved unwilling to engage the Chinese in Korea, then was their security guarantee for the Germans against the Soviets really worth what they said it was?”).

Book Review: The Revolt Of The Public

September 17, 2021 · Original source

[Egyptian dictator Abdel] al-Sisi aspired to the presidency, and his fate will provide a powerful signal with regard to the claims I have made in this book. If he can repress his way into a stable and long-lasting dynasty in the mode of Nasser and Mubarak, my analysis will be falsified. This isn't an impossible outcome. The future...is unknown. But as I observe, from afar, recent events in Egypt - and in Ukraine, Venezuela, Thailand, Turkey - I confess to many misgivings about the future of democracy, [but] far fewer doubts about the restlessness of the public or the crisis of authority.

The Israeli protesters attracted contradictory political fantasies because of the fuzziness of their definition. This repeated a pattern established in Egypt and Spain. The lack of leaders, programs, and organizational structure was if anything more pronounced. Those who spoke to the media on a regular basis, like Leef, were attractive and clever, but they lacked the power to command or decide, and they quarreled constantly among themselves. The question of whether to negotiate with the government divided the protesters. The goal of social justice - supposedly the North Star of the uprising - appeared to be as foggy a notion to them as to their media admirers.

Gurri argues all of this was connected, and all of it was a sharp break from what came before. These movements were essentially leaderless. Some had charismatic spokespeople, like Daphni Leef in Israel or Tahrir-Square-Facebook-page-admin Wael Ghonim in Egypt, but these people were at best the trigger that caused a viral movement to coalesce out of nothing. When Martin Luther King marched on Washington, he built an alliance of various civil rights groups, unions, churches, and other large organizations who could turn out their members. He planned the agenda, got funding, ran through an official program of speakers, met with politicians, told them the legislation they wanted, then went home. The protests of 2011 were nothing like that. They were just a bunch of people who read about protests on Twitter and decided to show up.

Ivermectin: Much More Than You Wanted To Know

November 17, 2021 · Original source

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.

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.

…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.

Who Gets Self-Determination?

March 30, 2022 · Original source

I appreciate hearing ideas I never would have thought of myself, and I never ever would have thought of this. I like how it simultaneously avoids starry-eyed “all people must be free” romanticism, and hard-headed “the strong do what they will, the weak suffer what they must” realpolitik, in favor of the vibe of some guy from a private equity firm trying to cut operating expenses: “Did anyone here notice that we have 195 countries, some duplicating each other’s portfolios? Do we really need both a Netherlands and a Belgium? And why do we still have an Egypt? People haven’t wanted Egypts for two thousand years!”

Your Book Review: The Internationalists

July 01, 2022 · Original source

They argue that the conflict between the West and the Islamic world isn’t really about the specific disagreements, as much as it is that many in the Islamic world reject the intellectual underpinnings that Europe formulated - the New World Order. This goes back to Sayyid Qutb, a leading member of the Muslim Brotherhood and inspiration to Al-Qaeda and ISIS. According to H&S, Qutb’s experience in the West and then interacting with the Nasser government in Egypt led to him rejecting in its entirety the Western conception of states, national sovereignty, and the Peace Pact.

The Qutbian enemy, therefore, is breathtakingly encompassing. The realm of Jahiliyyah is not merely the West, with its secularism, racism, imperialism, inequality, and sexual promiscuity. Nor is it simply Nasser and his henchmen, the brutes who ran torture chambers like Tora Prison. It encompasses all secular Arab governments—including those in Egypt, Jordan, Iraq, Syria. It also includes the ulema, the clergy who claim to speak for Islam, but support the lordship of man. It includes anyone who stands in the way of the establishment of an Islamic State. The enemy is the rest of the world.

Your Book Review: The Outlier

July 08, 2022 · Original source

Flush with confidence from his Panama Canal victory (his canalchemy? his Panamachievement?), Carter decides he should continue tackling foreign policy problems other people think are impossible. And there’s one obvious candidate: the conflict between Israel and the Arab states. Every single one of his advisors tells him this is a huge mistake and he definitely shouldn’t get involved, but knowing Carter, this only makes him want to do it more. His strategy: bring Egyptian President Anwar Sadat and Israeli Prime Minister Menachim Begin to Camp David for a series of intense negotiations. As usual, Carter believes that if he can just get the relevant parties in a room with him, he can convince them to see things his way.

Anyway, after two weeks of nonstop conversation between the three countries’ teams—during which negotiations almost fail more than once—they reach a deal. Essentially, the broad outlines are: 1) Egypt will officially recognize Israel and end the state of war between the two countries and 2) Israel will stop building settlements in the West Bank and transition towards self-governance for inhabitants of both the West Bank and Gaza [3]. The Camp David Accords, as they’re known, are a phenomenal success, putting the region on a path straight to the utopia it is today: a prosperous, conflict-free Middle East in which democracy and human rights flourish and the Palestinian people have full self-determination.

Shortly after his escape from Iran to exile in Egypt, the Shah is diagnosed with cancer, and since he’s been a consistent American ally, lots of influential people think we should let him come to the U.S. where he can benefit from our best-in-class treatment. Carter is against the idea at first (in fact, he directly predicts that granting the Shah entry to the U.S. could lead to Americans in Iran getting taken hostage), but eventually he’s worn down by his advisors and gives in. Less than two weeks after the Shah arrives, Carter’s prediction come true: the American embassy in Iran is overrun and 52 citizens are taken hostage. Ironically, even the Shah ends up worse off, as he ultimately dies not from his cancer but from a series of avoidable medical errors made by his American doctors.

Your Book Review: 1587, A Year Of No Significance

August 19, 2022 · Original source

So how well did the rest of the government function, given that the ruler was not really calling the shots, most days? I think we’ll get a better answer to that question by first zooming forward a few millennia, from ancient Egypt to the U.S.A.

The last time Wan-li ever ventured outside the Forbidden City was to visit his own tomb. Constructed during his lifetime, its interior bears comparison to the interiors of the pyramids of Egypt. (The exterior is less monumental.) Referred to superstitiously as the Mysterious Palace,

“The life of the kings of Egypt was not like that of other monarchs who are irresponsible and may do just what they choose; on the contrary, everything was fixed for them by law, not only their official duties, but even the details of their daily life”.

Links For September 2022

September 06, 2022 · Original source

39: Did you know: the Yom Kippur War started on October 6 (Ramadan 10 in the Arabic calendar). Egypt has commemorated it with two cities called Sixth Of October and Tenth of Ramadan, both with populations in the hundreds of thousands. This makes me wonder how Egypt thinks of the war: I had always learned it was a spectacular Israeli victory / Arab defeat, but countries don’t normally name that many cities after wars that they lost.

Inline links: Sixth Of October, Tenth of Ramadan

Response To Alexandros Contra Me On Ivermectin

February 01, 2023 · Original source

Carvallo said that zero people in the treatment group of his study got COVID, compared to 58% of people in the control group. This is a pretty implausibly big effect, even by the standards of other pro-ivermectin studies, although I don’t know if anyone else tried the exact same preventative protocol as Carvallo. I think this is a more nuanced story than Alexandros’ version where Buzzfeed just doesn’t know that sometimes studies happen at more than one hospital. Is fraud the best explanation? I think Alexandros thinks of Carvallo as just not keeping very good records, so he doesn’t have raw data, and probably mixed up his numbers a few times or gave false numbers, and didn’t have anything to send his collaborators when they asked. I think this is maybe possible, although it seems suspicious that he falsely said Dr. Lombardo was involved, falsely claimed the hospital involved was doing a different trial, and got very implausible results. I can imagine weird chains of events that would cause all of these things through honest misunderstandings. But they don’t seem like the best explanation. After discussing this with Alexandros, he objects to my use of the term “known fraudster”. Perhaps I should have said “highly credibly suspected fraudster” instead, although in a Bayesian sense nothing can ever be 100% and at some point plausibility shades imperceptibly into knowledge. Still, I feel like my description here was more accurate than Alexandros’, which just mentions the hospital approval issue and says nothing about any of the rest of this in a thousand word subsection about this study in particular. I did err in saying the Carvallo paper was retracted. According to the article: After BuzzFeed News raised questions about how the study’s data was collected and analyzed, a representative from the Journal of Biomedical Research and Clinical Investigation, which published the results, said late Monday, “We will remove the paper temporarily.” A link was removed from the table of contents — but was reinstated by Thursday. The journal’s explanation, provided after this story was published, was that the author “informed us that he has already provided the evidence of his study to the media.” I apologize for the error. Elalfy et al (still disagree with Alexandros) I described this as: 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 […] 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. In the summary post, Alexandros’ entire criticism of my coverage of this trial, one of the seven trials he focuses on as most unfairly covered and uses as the lynchpin of his argument that I am morally culpable for disastrously bad reporting, is: [Elalfy et al] are accused of incompetence for failing to randomize their groups multiple times in Scott’s piece. The paper writes in six separate places that it is not reporting on a randomized trial, amongst them on a diagram that Scott included in his own essay. Hard to imagine how else they could have made it clear. In his full post on this, he goes line by line to point out all the places they say they are non-randomized, pausing to snark about how dumb I am for not noticing each time4. But he never addresses the actual source of my confusion, which is the part of the paper where it says that: 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. If this was done as described, it should be an (almost) random trial; patients who come in on Wednesdays shouldn’t systematically differ from patients who come in on Thursdays5. But in fact, it looks (assuming I am understanding a very ambiguous table correctly) like there are very large pre-existing differences between the groups, sufficient to explain the entire result. If they in fact followed their days-of-the-week protocol, and it was random as expected, then I’m misunderstanding the table seeming to show very large differences, and they have indeed found evidence for ivermectin’s efficacy. If they didn’t follow their day-of-the-week protocol and it’s non-random, then maybe I’m understanding the table correctly and their groups had large differences to begin with and the fact that they had large differences at the end of the trial doesn’t demonstrate anything about ivermectin. This is all I was trying to say in the post, and instead of having any opinion on it Alexandros just makes fun of me for saying it. I think our actual crux is that Alexandros thinks a table of big differences between the groups has to be post-treatment (based on how big the differences are), whereas I’m not sure (because it’s unclear in the study, and also because the authors describe what could be a randomization method but also go on and on about how nonrandom they are). This is why I thought it mattered how random it was! Maybe instead of mocking me for this, you can admit it’s an important and relevant question! Ghauri et al (still disagree with Alexandros) I describe this as: 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. Alexandros notes that these are three differences between experimental/control groups, out of 33 listed characteristics that could have been different. There is approximately a 23% chance (he calculates) that you could get these differences by chance. He accuses me of failing to do a formal Carlisle test - the usual test you would use to determine whether weird differences between randomized groups are because of fraud - instead eyeballing it and getting it wrong. Here I do want to defend myself: I am not accusing Ghauri et al of fraud. In fact, this would be nonsensical: they admit they are assigning patients nonrandomly. Carlisle tests are usually done to show that something about group assignment is impossible (and therefore fraudulent) in a fair random assignment. But these people aren’t claiming to have done a fair random assignment, so I’m not sure what a Carlisle test would prove. My argument is more like: this is nonrandom, therefore we should expect it to be unfair. It is unnecessary, but helpful, to note an actual apparent unfairness - there’s some evidence they gave the ivermectin to less severe patients (as measured by corticosteroid use). Therefore, we can’t necessarily trust this to be a fair trial (which it was never really claiming to be). In the end I kept Ghauri as an okay study, although GMK didn’t so it ended out trashed in the final analysis anyway. I think my thinking was that I never claimed to be only looking at RCTs, so this non-RCT whose between-group-differences confirmed that it was indeed a non-RCT with all the risk of bias that entails, didn’t necessarily need to be ruled out. Still, I don’t think I was wrong to mention this possibility, and I think Alexandros was wrong to suggest that I needed to do extra tests for this to be fair. Borody et al (still disagree with Alexandros) I described this as: 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. Alexandros lists his full concerns here. My summary: Scott is being incredibly disrespectful to the authors, who are in fact a legendary gastroenterologist who invented life-saving h. pylori therapy and a brilliant immunologist who invented a well-regarded bronchitis vaccine (in particular, in describing their control group, I said “this is not how you control group, @#!% you”.

Inline links: This table, his full post on this, 4, 5, here

Book Review: The Geography Of Madness

February 22, 2023 · Original source

She reminded me that yesterday she was unusually grumpy, so much so that she had apologized to me for it and tried to come up with explanations - and then later yesterday she had her period. Meanwhile, Bures’ counterargument is - what? That it sounds kind of sexist to accuse female hormones of making women overly emotional? Hasn’t he ever heard of stereotype accuracy? That people asked their doctors to be treated for it more often after they knew it was considered a medical condition, and was treatable? That seems to have a much simpler explanation! That there are no biomarkers? There are inconsistent biomarkers that work sometimes but not other times, just like for schizophrenia, epilepsy, cancer, and half the other conditions in medicine. That these conditions don’t occur in most cultures? From here: A World Health Organization (WHO) study on menstruation (1981) surveyed 5,322 women from Egypt, India, Indonesia, Jamaica, Korea, Mexico, Pakistan, Philippines, United Kingdom and Yugoslavia. . . The majority of women in all cultures report some premenstrual physical discomfort in addition to negative mood changes, however fewer women report mood change than physical change. The main cross-cultural difference was in the prevalence of specific symptoms. Immigrants to the United States report more PMDD the longer they’re here? True (source), but it’s a matter of degree, and seems more true of the PMDD diagnosis than specific symptoms. The diagnosis requires impairment, which is subjective. I imagine an immigrant from a culture where mental disorders are unthinkable - something that only happens to a few psychos in asylums - and where you work 12-hour days in sweatshops. Someone asks her “hey, has this mental disorder ever prevented you from working?”, and she says no, because obviously you grit your teeth and work through the symptoms. And I imagine an American seeing the same question and saying “Yeah, I did decide I had to take a couple of sick days because of that.” I’m not saying this definitely happened, just that it’s a possibility. Meanwhile, this entire area of study is a mess. The “PMDD is culture-bound” hypothesis was originally invented by feminist scholars trying to argue that the diagnosis was a sexist attempt to pathologize women as overemotional and untrustworthy (this is also where Bures got his “it’s just hysteria by a different name” idea). See for example here and here, the second of which says that “the feminist argument is that if women are angry/distressed, it is for good reason, not due to pathology”. Bures somehow swallowed and repeated this, and then some feminists on Vox wrote an article attacking him as a “male writer” who was denying women’s lived experiences of PMS and stereotyping them as stupid and gullible. Neither side has an argument beyond “I can think of a reason it would be sexist for people to disagree with me” and neither side will acknowledge that the other side is also feminists basing their argument entirely on how it would be sexist to disagree with them. Everything in every area of social science has been like this for at least the past twenty years. But also, this highlights the difficulties with declaring something culture-bound. How do you know if something’s culture-bound, vs. people don’t notice it or mention it if they don’t have a name for it? How do you know if something’s culture-bound vs. some cultures consider it too embarrassing or taboo to think about? How do you know if something’s culture-bound, vs. people will go to doctors about it if they think doctors can treat it, and otherwise they won’t? I’ll discuss these questions more later, but I want to finish Bures’ argument. He gestures at a few other possible candidates for culture-bound mental disorders, including repetitive strain injury and chronic pain. But he quickly moves on to a long section that tries to establish the reality of “voodoo death”, ie the thing where if you believe you are going to die hard enough, you actually die. I think most arguments for voodoo death are pretty bad, and I didn’t find Bures’ convincing. But bonus points for referencing a study claiming that chronically stressed people only die at higher rates if they believe chronic stress is bad for them, and if not then they don’t (this is not really how I interpret the abstract, but I haven’t looked closely) Is it weird to stay on the crazy train long enough to agree that cultural effects are strong enough to make you think witches are stealing your penis, and then get off it once people start talking about voodoo death? I think no - these are very different situations. Believing in koro can make you hallucinate that your penis is shrunken or gone, but no belief, however strong, can (directly) remove your penis itself. Culture → beliefs is fine; culture → reality is a step I’m not willing to take. V. Since I rejected Bures’ PMDD example, I want to digress to what I think is a stronger argument: anorexia, which Ethan Watters discusses in his book Crazy Like Us. Anorexia was mostly unknown in the West, until becoming “trendy” in the mid-1800s. During that period, doctors reported high prevalence of anorexia among “hysterics”, but the fad ended after about ten or twenty years, and it went back to being basically unknown. In 1983, famous singer Karen Carpenter died of anorexia, thrusting it back into the national news, and suddenly lots of people (in the West) were anorexic again. Meanwhile, foreign doctors who trained in the West went back to their home countries, searched far and wide for it, and found almost nothing. The few cases they did see didn’t resemble the typical Western version at all - for example, one Hong Kong psychiatrist was able to find a woman who refused to eat out of grief when a boyfriend left her, but she didn’t think she was fat, or feel any cultural pressure to be thinner. The absence of anorexia abroad was especially surprising since anorexics tend to end up in the hospital with extremely noticeable malnutrition that doesn’t really mimic anything else. It’s not really possible to hide severe anorexia the way you can hide severe depression. In 1994, Hong Kong got its own Karen Carpenter - a young girl died of anorexia, setting off a national panic and many public awareness campaigns. Near-instantly, anorexia rates shot up to the same level as the West, with the appropriate number of people presenting to hospital ERs with severe malnutrition. This story raises a lot of questions. For example: where did the first anorexics (Karen Carpenter, the girl in Hong Kong) come from? Why anorexia and not something else? And how come knowing about anorexia makes it spread so quickly? VI. Past this point I’m using this review to discuss my own thoughts, not Bures’ or Watters’. “Culture-bound” is less all-or-nothing than you’d think. Look hard enough, and you’ll find people having “culture-bound syndromes” from cultures they’ve never heard of. Ntouros et al in Thessaloniki describe “koro-like symptoms in two Greek men”. One, a paranoid schizophrenic: . . . reported for the first time a sensation that his penis retracts into the abdomen and a fear that it will subsequently be lost. This would be accompanied by anxiety and sadness pertaining only to the loss itself. He would then proceed to search manually for his penis and masturbate. No pleasure was gained by masturbation, but the anxiety would be lifted. Romero et al describe a case of koro in "an intellectually disabled Caucasian patient" in Spain. They write that "although it is widely regarded as an epidemic in South-east Asia, there are some isolated cases in other cultures as well." Wilson and Agin describe a 29 year old white male from New York, "not exposed to the Chinese culture”, who went to the doctor with a five month history of worrying that his genitals were retracting into his body: Sometimes, he would manually reaffirm the presence of his genitals. Occasionally he would, in private, remove his garments and visually confirm the presence of his genitals. On one occasion, while taking the train home from work, he experienced an acute exacerbation of these symptoms. His pain increased from 3/10 to 10/10, and he felt as if his genitals had fully retracted within his belly. Upon reaching his hometown, he immediately went to the local hospital emergency room where examinations for inguinal hernia, urinary tract infection, proctitis, prostatitis, and testicular disorders proved negative. He improved significantly on the anti-anxiety medication desipramine. Chowdhury surveys the evidence on koro and divides the condition into two types: culture-bound and non-culture-bound. The culture-bound type usually goes in large epidemics, hundreds to thousands of people, in koro-believing parts of Africa and Asia; the victims were usually previously psychologically normal. The non-culture-bound type hits a few scattered individuals, is not contagious, and can happen anywhere - Greece, Spain, America. Some patients are psychologically normal, but there are a disproportionate number of schizophrenics, drug users, brain damage victims, and other previously-mentally-ill people. Other culture-bound illnesses seem to be like this too. Running amok has been big in Malaysia for 300 years. The Columbine shooters seem to have been autocthonous American cases, equivalent to that one New Yorker who got koro - before their fame inscribed amok onto the US collective consciousness the same way Karen Carpenter’s inscribed anorexia. Japan’s jikoshu-kyofu affects occasional victims in the US under the name olfactory reference syndrome. Watters admits there were a tiny handful of unusual anorexia cases in Hong Kong before Westernization. And even that Indian there’s-a-lizard-in-my-skin condition differs only in species from delusional parasitosis. Delusional parasitosis - the false belief that you are infested with parasites and can feel them crawling in your skin - is actually an especially interesting case. Two groups are disproportionately represented among patients: menopausal women and cocaine addicts. Relatedly, two biological conditions that can sometimes cause weird skin sensations that feel like crawling insects are . . . menopause and cocaine use. So there’s no mystery here. But, also represented among delusional parasitosis patients are the roommates and family members of these people. The index case hallucinates insects for a well-understood biological reason; their close contacts hallucinate insects through social contagion. So a unified theory of these conditions might be: Some people have the condition for a normal biological or psychiatric reason. For example, someone might believe a lizard is crawling under their skin because they use cocaine, which causes hallucinatory crawling sensations. Or someone might believe their penis is missing because they’re schizophrenic, which makes them naturally hallucination-prone.

Inline links: stereotype accuracy, inconsistent biomarkers that work sometimes but not other times, here, source, here, here, and then some feminists on Vox wrote an article, chronic pain, are pretty bad, a study, Ethan Watters discusses in his book, Ntouros et al, Romero et al, Wilson and Agin, surveys the evidence, olfactory reference syndrome, delusional parasitosis

Against Ice Age Civilizations

March 03, 2023 · Original source

Civilizations about as advanced as Pharaonic Egypt

Areas likely above water during the Ice Age are in orange-brown (source) What would happen to the ancient civilizations we know about if sea level rose an additional 120m? We would lose Babylon, Rome, and most of Egypt. But: The Acropolis of Athens is 150m above sea level, and would be preserved for future archaeologists. Sparta (200m) and Thebes (250m) would also be fine.

Inline links: source

The top 80m of the Great Pyramid would rise above the waterline, forming a little island. The part of the Pyramid above the water would still be taller than the entire Leaning Tower of Pisa. It would be pretty hard to miss! So a 120m sea level rise wouldn’t be enough to wipe out evidence of our crop of ancient civilizations, and shouldn’t be enough to wipe out evidence of a previous crop, unless they had a very different geographic distribution than ours. Argument 2: Where Are The Crops And Livestock? We can do genetic analysis of crops and livestock, compare them to wild plants and animals, and make good guesses about where and when they were domesticated. Wheat was domesticated somewhere around Karaca Dag, Turkey, around 9000 BC. Barley was domesticated somewhere around Jarmo, Iraq, around 9000 BC. Cows were domesticated somewhere around Cayonu Tepesi, Iraq, in 8500 BC (then a second time, in Pakistan, later on). Rice was domesticated in two places in China around 10,000 BC. All of these crops were invented exactly where the standard historical narrative says there were late pre-agricultural people of exactly the type who would domesticate crops. They spread at about the same rate as sedentary living in general, monuments, and other signs of complex civilization. The only known exception is Gobekli Tepe, a megalithic site in Turkey, which may very slightly predate known agriculture. But it also might very slightly post-date known agriculture, or exactly-date known agriculture (it’s just sixty miles from Karaca Dag, and it would make sense if they were the people who domesticated wheat). That one anomaly aside, there’s a very tight agriculture <—> things that seem to require agriculture coupling. So if there were Ice Age civilizations, what did they eat? It couldn’t have been any of our known crops, which post-date them. Could it have been their own crops, which were later lost? Seems unlikely. Throughout most of history, civilizations have risen and fallen, but they don’t lose agriculture! The empire divided longs to unite, the empire united longs to divide, but the Chinese never fragmented so hard that they forget how to cultivate rice and rice went extinct. Maize has survived nine millennia of rising and falling bloodthirsty Mexican empires. Almost everyone in the Amazon died in the 1500s when European diseases swept through, but they still left us manioc, squash, and chiles. Could Ice Age civilizations have thrived without domesticating any plants? We increasingly realize that agriculture isn’t all-or-nothing, there’s a spectrum from picking wild plants when you come across them to domestication, irrigation, and the full suite of agricultural technologies. It wouldn’t surprise me if some combination of early-non-domestication-involving agriculture and hunting-gathering off of very rich lands could create enough sophistication to build a Stonehenge or a Gobekli Tepe. But you’re not getting Egypt or Great Britain off of that, sorry. Argument 3: Lead Levels Thanks to commenter WTFwhatthehell for bringing this one up. Many ancient civilizations mined lead. Some of the lead made it into the atmosphere and settled down again in other places. You can measure the amount of lead in different places to see how much lead humans are mining. This isn’t perfect - the resolution is closer to continental than global - but you can check lots of different continents and get an okay reading. This paper finds lead levels started rising 1000 BC, which it links to the Phoenician expansion happening around that time. In theory, this could suggest that no ancient civilization reached a tech level where it started mining lead, ie the tech level the Phoenicians had in 1000 BC. This is in theory only, because I can’t find a clear record of anyone checking. I assume ice core scientists would have noticed if it happened, but there’s no publicly available dataset with lead levels 10,000 years before present, nor is there a paper titled “We Checked To See If There Were Anthropogenic Lead Emissions In 10,000 BC And There Definitely Weren’t”. Here is a paper that looks at lead level in human bones. They don’t do a great job explaining how lead makes it into human bones, but it seems like a mix of the kind of lead pollution that makes it to Greenland ice cores, plus personally wearing or consuming things that have touched lead. This study investigates skeletons from 12,000 BC onwards, and finds that lead levels start rising in 5,000 BC, when people developed “cupellation”, a technique for using lead to purify gold and silver (it then goes up much further between 1000 - 500 BC, probably the same spike the Greenland cores found). So this presents some very weak evidence against significantly elevated lead from 12,000 BC onward. But it doesn’t rule out small amounts of lead mining far away from the bones’ previous owners, and doesn’t rule out a civilization lasting from 15,000 - 13,000 BC. A Great Britain-level civilization would be expected to raise lead levels a lot, and this pretty strongly rules it out. I would expect an Egypt-level civilization to at least invent cupellation, but I don’t know if its lead would necessarily make it to wherever these bones came from. A Stonehenge or Gobekli Tepe level civilization isn’t ruled out at all. Conclusion I think there’s pretty strong evidence against lost Egypt- or Great Britain- level Ice Age civilizations. I don’t want to rule out a lost Stonehenge or Gobekli Tepe level civilization, but there’s not much positive evidence, and there’s some negative evidence. Stonehenge was built by Neolithic farmer-pastoralists, who had lots of domesticated crops and animals. Gobekli Tepe was built right next to the area where wheat was domesticated at around the same time. Existing early monuments mostly suggest a story where sedentary city- and temple- building civilizations either require domesticated agriculture, or invent it very quickly. None of this means Ice Age people didn’t have fascinating cultures of their own which were advanced in other ways - interesting laws, taboos, mythologies, customs, oral traditions. Tyler Cowen says that everything started earlier than you think, and this is what we’ve been finding about various forms of human culture too (cf. Against The Grain, The Dawn Of Everything). I just don’t expect lost Ice Age cities or giant monuments. I think Michael Shermer’s attempt to argue the same case is weak, relies on a still-controversial rejection of the Younger Dryas Impact Hypothesis, and generally leans too much on the absurdity heuristic without moving the needle one way or the other. All of the following predictions are about structures on Earth built by homo sapiens without time travel: 20% chance we ever find something demonstrating equal or greater architectural advancement to Gobekli Tepe, dating from before 11,000 BC.

Inline links: Karaca Dag, Jarmo, Iraq, Cayonu Tepesi, Iraq, in two places in China, WTFwhatthehell, This paper finds lead levels started rising 1000 BC, https://substackcdn.com/image/fetch/$s_!rPgI!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6265c4a7-a563-477c-afbc-7b3c9b8dd73e_1280x1247.jpeg, Here is a paper, https://substackcdn.com/image/fetch/$s_!SS8H!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0b5de41a-38d8-4145-821d-5e2f6d2de228_534x215.png, Against The Grain, The Dawn Of Everything, Michael Shermer’s attempt to argue the same case, Younger Dryas Impact Hypothesis

Your Book Review: The Weirdest People in the World

August 11, 2023 · Original source

A big silent intellectual change of the past quarter century is the broadening of our self-concept. Educated Westerners are starting to expect each other to know Chinese and Islamic history, which are still ongoing, and perhaps something about pre-Columbian America whose stories were traumatically ended by the conquest of the New World. The earlier past is moving into the light, too. Ancient states like Babylon and Egypt are gradually coming alive: Hammurabi and Gilgamesh get more play relative to Solon and Achilles. And before that, the real prehistory of the first cities, the Neolithic, the growth of agriculture, the end of the Ice Age at 10,000 BC, modern humans around 100,000 BC, the first humans at 1mya (million years ago)… these dates are gradually getting fixed in the mind as turning points in the story of us.

Inline links: story of us

The difference between Greece and Rome on the one hand, and Babylon and Egypt on the other, was that Greeks and Romans had written down their stories for us. Their stories had become our story. History was a narrative. Each of its chapters had a beginning, middle and end. How else would you tell it? Now, as we go farther back, we have less and less writing to rely on. Even when we have writing, on papyrus or stone, it isn’t self-interpreting – it’s not history the way Herodotus and Livy tell us history, with the explicit goal of recounting the past. Earlier still the texts die out completely, and we are left with stones and bones. Our knowledge of this history has to come from science: from archeology, anthropology (in the hope of using present societies to learn about past societies), and now also the new science of historical population genetics. Joe Henrich has done more than most to teach us our history using these tools. His marvelous book The Secret of Our Success told the human narrative from the point of view of the unique human capacity for cumulative culture1.

Inline links: book, 1

Your Book Review: Why Nations Fail

August 25, 2023 · Original source

Even if correct, it is much less interesting and useful than it appears. Epistemic status: I have a decade-old PhD in economics (not in the field of economic growth) and a handful of peer-reviewed papers in moderately-ranked journals. I'm not claiming to make any original technical points, or to give a comprehensive evaluation of the economic growth literature. My criticisms are largely straight from the authors' own mouths. 1. What is this book about? Why is it not very good? Acemoglu and Robinson (AR) argue that countries are rich or poor because of their political institutions, not culture, geography or policy ignorance. I'll do this as much as possible in AR’s own words. Why Nations Fail was written during the Arab Spring, so the preface begins with Egypt. Some stress that Egypt’s poverty is determined primarily by its geography, by the fact that the country is mostly a desert and lacks adequate rainfall, and that its soils and climate do not allow productive agriculture1. Others instead point to cultural attributes ... Egyptians, they argue, lack the same sort of work ethic and cultural traits that have allowed others to prosper, and instead have accepted Islamic beliefs that are inconsistent with economic success. A third approach, the one dominant among economists and policy pundits, is based on the notion that the rulers of Egypt simply don’t know what is needed to make their country prosperous, and have followed incorrect policies and strategies in the past. Unsurprisingly, those other economists and policy pundits turn out to be wrong and the authors turn out to be right. In this book we’ll argue that the Egyptians in Tahrir Square, not most academics and commentators, have the right idea. In fact, Egypt is poor precisely because it has been ruled by a narrow elite that have organized society for their own benefit at the expense of the vast mass of people. And the Egyptian lesson turns out to be general. Whether it is North Korea, Sierra Leone, or Zimbabwe, we’ll show that poor countries are poor for the same reason that Egypt is poor. Countries such as Great Britain and the United States became rich because their citizens overthrew the elites who controlled power and created a society where political rights were much more broadly distributed, where the government was accountable and responsive to citizens, and where the great mass of people could take advantage of economic opportunities. What are “institutions” anyway? (The economic and political kind, not the prison and mental hospital kind.) Basically, AR mean politics. The word "institutions" occurs over 1000 times in Why Nations Fail2. I'll just focus on how AR use it without worrying about the dictionary, different schools of economics, or other social sciences. They begin with what institutions do rather than what they are. Nogales, Arizona, is in the United States. Its inhabitants have access to the economic institutions of the United States, which enable them to choose their occupations freely, acquire schooling and skills, and encourage their employers to invest in the best technology, which leads to higher wages for them. They also have access to political institutions that allow them to take part in the democratic process, to elect their representatives, and replace them if they misbehave. The word is used dozens more times before ARattempt a more general definition. Each society functions with a set of economic and political rules created and enforced by the state and the citizens collectively. Economic institutions shape economic incentives: the incentives to become educated, to save and invest, to innovate and adopt new technologies, and so on. It is the political process that determines what economic institutions people live under, and it is the political institutions that determine how this process works. So while economic and political institutions can be separated, it is the political institutions that matter in the long run. The good kind of institutions that lead to economic growth are "inclusive", as opposed to "extractive". To be inclusive, economic institutions must feature secure private property, an unbiased system of law, and a provision of public services that provides a level playing field in which people can exchange and contract; it also must permit the entry of new businesses and allow people to choose their careers. ... such rights must exist for the majority of people in society. Political pluralism is necessary, but not sufficient without a strong centralised state. ... political institutions that distribute power broadly in society and subject it to constraints are pluralistic. ... the key to understanding why South Korea and the United States have inclusive economic institutions is not just their pluralistic political institutions but also their sufficiently centralized and powerful states. A telling contrast is with the East African nation of Somalia. I am still a bit hazy as to the relative importance of de jure written rules versus the de facto struggle for power. AR are somewhat circular: Politics is the process by which a society chooses the rules that will govern it. Politics surrounds institutions ... When there is conflict over institutions, what happens depends on which people or group wins out in the game of politics ... The political institutions of a society are a key determinant of the outcome of this game. They are the rules that govern incentives in politics. But overall, you could just say ‘politics’ and not be too far off. AR do this themselves occasionally. South Korea ended up with very different economic institutions than the North because different people with different interests and objectives made the decisions about how to structure society. In other words, South Korea had different politics. AR's academic reputation is based on statistical analysis, but Why Nations Fail tries to do narrative history, IMHO not very well. When Jeffrey Sachs reviewed the book, he complained: They never define their key variables with precision, present any quantitative data or classifications based on those definitions, or offer even a single table, figure, or regression line to demonstrate the relationships that they contend underpin all economic history. Instead, they present a stream of assertions and anecdotes about the inclusive or extractive nature of this or that institution. AR replied baldly: Sachs ... argues that we provide no evidence. Right, we do not in the book. But that’s because a book for a general audience is not the right forum for presenting academic research, and we spent many years of our lives precisely on writing academic papers providing exactly the sort of evidence. ... So yes, we don’t provide the econometric evidence in the book, which isn’t of course the right place to do it, but econometric evidence is abundantly loud in the way it speaks on these topics. So, don't expect Why Nations Fail to be an accessible explanation of AR's academic work, which is what I was hoping for when I first read it. What do they spend over 500 pages on then? Well, after the preface, there's fifteen chapters of, as Sachs says, "assertions and anecdotes". Not just about "the inclusive or extractive nature of this or that institution", to be fair, but how institutions can change at "critical junctures" such as the Black Death or colonisation, and why it can be in elites’ interests to block economic innovation if it threatens their power, so that growth under extractive institutions is unlikely to be sustained. These chapters are not particularly good – I found them poorly organised and repetitive – but not particularly bad, if you are willing to accept the underlying premise that institutions are the main determinant of economic growth. Cumulatively they have an effect similar to the Old Testament, if you are willing to accept the underlying premise that the fortunes of the nation of Israel are determined by the LORD. Only the second chapter, ‘Theories that Don't Work’, makes a sustained argument against alternative theories. Geography is disposed of by noting the stark differences at the US-Mexican, North-South Korean and East-West German borders, and the reversal of fortune by which the present day US and Canada only became richer than Mexico, Central and South America following European colonisation. Culture is hand-waved away with the assertion that institutions determine the any relevant cultural behaviours, not the other way around, referring to the same border examples, the rapid catch up of Catholic Europe despite Weber's Protestant Ethic, the malign influence of the European and Ottoman empires on Africa, the range of outcomes within the former British Empire, and the more European population of Argentina and Uruguay versus the US and Canada, or of Columbia versus Ecuador and Peru. Not a bad list of anecdotes, but one could equally well point to the cross-border success of Ashkenazi Jews, overseas Chinese, or Baltic and Volga Germans. Ignorance is simply dismissed with the assertion that "if ignorance were the problem, well-meaning leaders would quickly learn what types of policies increased their citizens’ incomes and welfare, and would gravitate toward those policies." Various good and bad policy changes are explained as the result of political pressures rather than improved knowledge. The implication seems to be that good policies are so obvious they don’t require expert knowledge or advice, or that the experts never get it wrong. This appears most implausible in the debate over socialism and economic planning. Writing off the entire Communist experience as simply another elite trying to preserve its power feels inadequate, especially considering that some distinguished bourgeois economists thought central planning was a plausible road to riches until quite late in the day. Genetics or race is not mentioned, but would presumably attract the same counterexamples as geography and culture. Another theory AR do not discuss is crude exploitation: while colonial empires are excoriated, it is for setting up persistent extractive political institutions rather than for a direct theft of resources. The prosperity of white-owned South African farms next to poverty-stricken Bantustans is explained by the better quality of the institutions available to whites under apartheid, not relative population densities and land quality. For the rest of the book, I'll just list a few nitpicks to signal I read the whole thing and know a bit of history, but feel free to skip this – the real evidence for AR's thesis is in their academic papers, and I'll discuss those in the next section. I think AR overrate the importance of the Glorious Revolution, to the point of claiming it "created the rule of law" – after all, Parliament had already deposed and executed a king, then brought back the king’s son on their own terms after a decade of republican government. No less a luminary than Edmund Burke asserted "The Revolution was made to preserve our ancient indisputable laws and liberties, and that ancient constitution of government which is our only security for law and liberty." Also, strong signs of British economic uniqueness – the abnormal growth of London and reliance on coal as a fuel – predated 1688.

Inline links: 1, 2, dictionary, schools, economics, social sciences, reviewed, replied, Protestant Ethic, planning, distinguished, bourgeois, Glorious Revolution, Edmund Burke, predated

The preface has Egypt passing seamlessly from the Ottomans to Napoleon to British colonialism, while chapter 2 describes Muhammed Ali's rule (1805-48) as "a path of rapid economic change". Tarring Nasser's regime as "another elite as disinterested in achieving prosperity for ordinary Egyptians as the Ottoman and British had been" also seems unfair – whatever his faults, he did redistribute land to peasants, build the Aswan dam, and push an extensive program of industrialisation.

Inline links: Nasser's, peasants

We probably shouldn't judge this book too much on hindsight, given it's about the long run and AR were prudent with their predictions: "the fact that the extractive regime of President Mubarak was overturned by popular protest in February 2011 does not guarantee that Egypt will move onto a path to more inclusive institutions." Even so, the clear implication was that the Arab Spring was on the right track and Brazil was setting itself up for the long run better than China.

Book Review: The Alexander Romance

September 19, 2023 · Original source

You can see the zigs and zags where one culture seizes control of the narrative, then gives it up. Alexander spends a while standing on the site of Alexandria, talking about how it will be the greatest city in the world by far and extend until the end of time, and how its patron god Serapis is the true god of the universe - then leaves and basically never thinks about either of them again. I am told there is a version written by Persians where Alexander is the son of a Persian Shah instead of an Egyptian Pharaoh, and a version written by Jews where Alexander kneels before the High Priest in Jerusalem and agrees that Judaism is the true religion. After Alexander’s death, the generals read out his will, which begins with effusive and totally-unrelated-to-anything-that-has-happened-before praise for the city of Rhodes, its people, and its glorious history; in the footnotes, the editor writes “one may suspect a Rhodian had a hand in the addition of the first four paragraphs”.

Nectanebo was a pharaoh who was also a wizard. He ruled Egypt wisely; when enemies attacked, he would magically vaporize their armies from afar. One day he scryed some enemies approaching Egypt’s border (probably the Persian army of Cambyses?); when he tried to vaporize them, the magic didn’t work. He realized that the gods had decreed that Egypt must fall, so he fled to Macedonia, working as a magician-for-hire to make ends meet.

Book Review: I See Satan Fall Like Lightning

November 17, 2023 · Original source

He contrasts this with the Bible. Lots of Bible stories also fit the pattern. As in Babylonian and Norse mythology, the world begins with a primordial murder: Cain kills Abel. But the clearest example is the story of Joseph and his brothers. Joseph’s brothers grow jealous of him, coveting his beautiful multi-colored coat. They form a mob, gang up on him, and are about to kill him, when a slave caravan comes by and they decide to sell him as a slave instead. Then Joseph becomes as close to a god as the monotheistic Israelites are willing to accept (Prime Minister of Egypt) and founds the next stage of Israelite civilization as some kind of culture-hero figure.

Book Review: Cyropaedia

January 10, 2024 · Original source

Lots of ancient civilizations started as city-states, and - even after reaching imperial glory - were still in some sense city-empires. Rome, Carthage, and Babylon are all obvious. But even the less obvious ones still fit the pattern. Assyria was centered around the city of Assur. Egypt shifted imperial centers over the dynasties, but it was usually either Memphis or Thebes. So what city did Persia start out as? What was the urban seed of Cyrus’ conquests?

Some Practical Considerations Before Descending Into An Orgy Of Vengeance

July 23, 2024 · Original source

Sorry, I don’t know how this one got in there. The most complete response was by Postcards From Barsoom, which recommended Right Wing Cancel Squads. That there are so many of us who feel queasy at the thought of getting low-level proles fired from their jobs for sounding off online is a very good thing. It speaks to the fact that, unlike the enemy, we actually have a moral centre. Notably, this was never a serious debate on the left. Those few left-wing voices in the early teens who championed classical liberal principles of freedom of expression were summarily cancelled themselves, and are largely on our side now. In an ideal world, we would all give one another vastly greater latitude. No one would get mobbed, fired, forced to resign, kicked out of school, or ostracized from their professional networks for the non-crime of an unpopular opinion. No one would have to worry about people combing through decade-old social media posts looking for gotcha words that weren’t gotchas when they were written, but became crimespeak ex post facto. In the long run, it’s essential that we aim for permissive social mores regarding public and private discourse. This is a simple matter of technological context. Social media means that there is a more or less indelible record of your every public utterance; sure, you can try to scrub it, but that won’t stop screenshots; sure, you can try to cloak yourself behind a pseudonymous identity, but that just means you need to worry about doxxing. Cell phones mean that your private conversations can be recorded. We live in an electronic surveillance society now. We’re all watching one another, all the time, and short of a Carrington Event knocking us back into the iron age, there’s no realistic possibility of that changing. If we keep holding one another to impossible standards of public discourse, we will live in a totalitarian hell; that is, indeed, precisely the world that we have all lived in, for the last decade. The only way we avoid this is by adopting a public ethos that is exceptionally forgiving. But we do not live in that world yet, and that is entirely the left’s fault. [...] If we are going to arrive at a social compromise in which we do not punish people for their speech, a reaffirmation for the Sand Age of the ancient Saxon right to plainly speak one’s mind, it is necessary that everyone develop a keen appreciation of just how horrible the alternative is. This can only be grounded in a visceral revulsion at the very thought of cancellation, the way the world has looked at chemical weapons ever since the Great War, which in turn must come from direct, personal experience of what it feels like to be on the receiving end. To this end, distasteful as it may seem, the liberal’s face must be pressed down into her own steaming pile of excrement. She must be made to taste it, and gag, and swallow nonetheless. She must be made to weep burning tears. She must be traumatized, and made to understand that this is what she did, that these are the rules of engagement that she established, that these are the consequences of loss in this awful game that she has forced all of us to play. She needs to beg for the game to end, for the rules to change. Take a second to sympathize. From the Right’s perspective, the Left has beaten, shamed, and terrorized them for at least a decade. Now, the moment they get some chance to retaliate, their enemies say “Hey, bro, come on, being mean is morally wrong, you’ve got to be immaculately kind and law-abiding now that it’s your turn”, while still obviously holding behind their back the dagger they plan to use as soon as they’re on top again. I won’t be able to convince anyone of the ethics of seeking vengeance vs. turning the other cheek. But a few thoughts on the specific practical arguments being deployed: 1. Nobody Learns Anything Useful From Being Persecuted Going back to that excerpt from the Postcards From Barsoom blog: If we are going to arrive at a social compromise in which we do not punish people for their speech, a reaffirmation for the Sand Age of the ancient Saxon right to plainly speak one’s mind, it is necessary that everyone develop a keen appreciation of just how horrible the alternative is. This can only be grounded in a visceral revulsion at the very thought of cancellation, the way the world has looked at chemical weapons ever since the Great War, which in turn must come from direct, personal experience of what it feels like to be on the receiving end. To this end, distasteful as it may seem, the liberal’s face must be pressed down into her own steaming pile of excrement. She must be made to taste it, and gag, and swallow nonetheless. She must be made to weep burning tears. She must be traumatized, and made to understand that this is what she did, that these are the rules of engagement that she established, that these are the consequences of loss in this awful game that she has forced all of us to play. She needs to beg for the game to end, for the rules to change. You mean like you’re doing now? The right-wingers admit that they have suffered terribly at the hands of cancellation mobs. Okay, check. They admit it’s made them so mad that they want a bloodbath of cancelling liberals harder than anyone has ever been cancelled before. Okay, check. And now they say . . . that lefties must suffer terribly at the hands of cancellation mobs, because it will teach them that cancellation is wrong? If being on the receiving end could teach people cancellation was bad, it would have taught you that. It obviously hasn’t, so try a different strategy. 2. This Isn’t Tit For Tat, It’s The Nth Round Of A Historical Dialectic “Given that liberals invented cancel culture ten years ago, shouldn’t we get ten years of conservative cancel culture, just to be fair?” asks someone totally divorced from historical reality. Modern progressive cancel culture is the successor of the 1950s establishment that would cancel you for being an atheist pinko peacenik. Curtis Yarvin calls cancellation “the Brown Scare”, by analogy to the Red Scare that came before. And Arthur Miller called the Red Scare a “witch hunt”, by analogy to actual witch hunts, the Spanish Inquisition, and the history of burning heretics at the stake. And what was Diocletian’s persecution of the Early Church if not cancel culture? People joke that “cancel culture began with Socrates”, but I don’t buy it. Seen on Wikipedia: [In 1345 BC], Akhenaten … ordered the defacing of Amun's temples throughout Egypt … Archaeological discoveries at [Amarna] show that many ordinary residents of this city chose to gouge or chisel out all references to the god Amun on even minor personal items that they owned, such as commemorative scarabs or make-up pots, perhaps for fear of being accused of having Amunist sympathies. When the Priests of Amun came back into power, they took the low road: This culture shift away from traditional religion was reversed after his death. Akhenaten's monuments were dismantled and hidden, his statues were destroyed, and his name excluded from lists of rulers compiled by later pharaohs. And since righteous vengeance had been attained and both sides now had experience with cancel culture being morally wrong, everyone agreed the ledger was balanced, and nobody ever tried cancelling anyone else ever again. No, seriously, we got the entire rest of history. Aldous Huxley famously described the state of things c. 1944 as: Only one more indispensable massacre of Capitalists or Communists or Fascists or Christians or Heretics, and there we are—there we are in the Golden Future. Just one more indispensable cancellation, and there we are! Instead, I think of unfreedom of conscience as a scourge that has troubled humanity throughout history, like famine or plague or war. As with all scourges, very-long-run progress coexists with occasional disastrous relapses. The solution isn’t to get the other side and balance the ledger, it’s to keep developing the physical and social technology that’s gradually improved things in the past. 3. You’re Not Debating Whether To Become Like Woke People, You’re Already Like Woke People An old psychoanalyst’s trick: if somebody ruminates too much over some decision, it’s to distract from some other decision they’re trying not to notice. The hidden decision here is whether to treat people as collectives or individuals. One of the fundamental problems with wokeness was that it believed in collective guilt and collective punishment. White people caused slavery, therefore white people stood condemned. No matter that the actual white person involved was 150 years removed from slavery, or was a Polish immigrant whose family hadn’t even been in the country at the time, or whatever. They have some excuse like “well all white people benefit from white supremacy in tangible ways, or at least didn’t speak out against it”. I hate to say it, but “some left-wing journalist got people cancelled, therefore I should be able to cancel a left-wing Home Depot employee because The Left endorsed cancel culture” is the same kind of argument. “But wasn’t the Left monolithically united behind cancel culture?” You can find some data here. I’m presenting a representative sample of questions, but check the rest to keep me honest: Unless you really lay on the tribal signifiers, it’s hard to find a definition where most Democrats support cancel culture and most Republicans oppose it! (the above poll probably overestimates support for cancel culture, because it talks about saying “things widely considered hateful” instead of, like, one tweet expressing a widely-shared opinion at the wrong time) Liberals invent a fictional entity called “The Right”, which is full of all of the most racist and fascist things that NYT was ever able to produce an out-of-context quote showing one Claremont guy saying, then believe that any action is justified against “The Right” because it’s an ontological threat against democracy, then rile up a mob against a Google guy who sends the wrong memo. Likewise, conservatives invent a fictional entity called “The Left”, which is full of all the most horrible woke things that FOX was ever able to find one Gender Studies professor saying, then believe that any action is justified against “The Left” because it’s coming for our children, then rile up a mob against a Home Depot woman who makes a bad tweet. 4. Nobody Is Ever Both-Sides-ist Enough I hate this because I’ve fought with these people on the Left, and they sound exactly the same. “If you feel like compromising with the Right, it’s important to remember what they’ve done. They separated families and locked children in cages. They forced 10-year-old rape victims to carry their rapists’ babies. They murdered our grandparents by refusing to mask in the middle of a pandemic. They killed thousands of American soldiers in a war over fake WMDs, then cut VA funding so the soldiers they wounded would die on the street. At this very moment, they’re boiling our planet alive to protect fossil fuel barons’ profits. How dare you suggest it could possibly be wrong to cancel someone like that!” This isn’t a knock-down argument. Sometimes you’re right when you think your enemies are bad, and they’re wrong when they think you’re bad. I can’t say for sure this isn’t one of those times. But: The fact that your enemies are just as sure as you are should make you less sure.

Inline links: Postcards From Barsoom, Right Wing Cancel Squads, calls, Wikipedia, https://substackcdn.com/image/fetch/$s_!kWBR!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F091055e1-265a-4c3d-88ed-8e18d1a73d09_642x355.png, find some data here, https://substackcdn.com/image/fetch/$s_!PFOa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9a2ecad6-df80-45a9-ae36-1da9cacf9392_604x312.png, https://substackcdn.com/image/fetch/$s_!DsK8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1b2b376e-c9f7-4a20-a586-cc337448475a_620x302.png, https://substackcdn.com/image/fetch/$s_!uN26!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe3e18655-04f5-4f11-bdaa-314c09084ced_819x324.png, https://substackcdn.com/image/fetch/$s_!nmE9!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa5cd863a-f067-4c6f-909c-994a6f331a94_655x303.png, https://substackcdn.com/image/fetch/$s_!xvzc!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6a0440e6-548d-4b3a-9e35-97e62a515515_667x311.png, https://substackcdn.com/image/fetch/$s_!HKLM!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc536a7a3-0a21-4978-8024-221253c4dddd_601x450.png

Meetups Everywhere Spring 2025: Times & Places

March 25, 2025 · Original source

If you need to change a meetup date or you have any other questions, please email skyler[at]rationalitymeetups[ period]org. Africa & The Middle East Egypt CAIRO Contact: Mostafa Shahat Contact Info: ms[a t]mostafashahat[period]com Time: Sunday, April 20th, 12:00 PM Location: Consoleya | We'll be in the main coworking space on the ground floor. I'll be wearing a name tag with 'ACX MEETUP' on it, and there will be a small sign on the table. Coordinates: https://plus.codes/8G2H26XR+P4

Inline links: https://plus.codes/8G2H26XR+P4

Your Review: Joan of Arc

August 01, 2025 · Original source

The answer was, as it happened, that the Edwards first and third had spent the past sixty years building the most professional army in Europe. England, like the rest of post-Roman Europe, had been founded on a military basis of feudal levies, with each vassal providing soldiers at his expense to fight alongside the king’s personal retinue. These soldiers could be called out for long enough to stop marauding Vikings but not for much longer, so any attempt to raise an army for even a single year's campaign required agonizing negotiations with each individual leader and, worse, meant that the troops were all either sullen conscripts or proud knights eager for glory and jealous of their honor. These knights might fight like the devil - as everyone from Greece to Egypt to Tunis had learned to their cost - but leading these men was like herding cats.

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