I wish everybody who is proposing strategies for dealing with pandemics read this short essay.

TL;DR: Richard Dawkins once said something like: "But when has theology ever said something that's of slightest use to anybody? When has theology said something that's demonstrably true and is not completely obvious? Science has found cures and vaccinations for all kinds of diseases, and theology in all that time has done nothing but talk about pestilences as a consequence of sin.". Let's ask ourselves, do we today have a "science" that is talking about pestilences as a consequence of sin? To me it seems like we do, that it is the mainstream epidemiology. It is talking about the pestilence of COVID-19 as consequence of sin of letting our economy keep running instead of stopping it with lockdowns. And it is amazing to me that many people whom I otherwise consider brilliant think that the "focused protection" epidemiology (which advocates separating families and attempting to build herd immunity using young people) is any less pseudoscientific.

There are, as far as I can see, three basic strategies with dealing with a pandemic. Those are:

1. Mainstream epidemiology. That is lockdowns, mask mandates and social distancing.
2. Focused protection. That is an attempt to restructure the society so to use natural immunity of the low-risk people to protect the high-risk people.
3. "Let it rip". That means, the government should simply do nothing.

In this short essay, I will explain as clearly as possible why I think the third strategy, "let it rip", is the best.

So, we are almost three years into the COVID-19 pandemic. And it is absurd to think this will be the last pandemic in history. Especially since we are massively using antibiotics in the egg industry, which gives birth to superbacteria, and we are doing dangerous gain-of-function research on viruses. Maybe there will be another pandemic even within my lifetime. Here are the lessons I think rulers should have learned from the COVID-19 pandemic:

1. Don't pretend that masks and social distancing help significantly. The Danish study on the masks failed to find a statistically significant result. The analysis of the raw data from it appears to suggest they provide around 18% protection. The Bengali study found no statistically significant result for cloth masks and the result for medical masks was right on the margin of error (p-value was 5%, which is usually considered a margin of error in science). Such protections are easily offset by changes in behaviour. And even from the epidemiological data, it is obvious masks have little or no effect. Places with mask mandates do not tend to have fewer COVID-19 deaths than places without mask mandates. And people who participated in the Danish and Bengali studies were undoubtedly more conscientious about masks than most people are. Most people are wearing dirty masks often not covering their noses^{[citation NOT needed]}.
   If you want an intuitive explanation of why masks have little effect, watch one of those YouTube videos in which a pearson wears a mask outside in a cold weather, so that you can clearly see how many small droplets pass through the mask. I think that, after that, the results of the Danish study or the Bengali study (and keep in mind people in those studies were wearing a single mask there, not two masks, and no N95 masks) should come as no surprise.
   As for social distancing, I am not sure whether it works at all. The famous MIT study is often cited as a proof that it does not. Now, you can argue that the MIT study is methodologically very questionable, and I would agree with that, however... Where is the evidence that it does work? I think we have to admit there is no hard evidence that it works. And by hard evidence, I mean something at least as rigorous as my latest paper about linguistics (you can read an English-language summary of that paper), that is, something with p-values and things that go with them. If you want to force everybody to obey some rules, you need to have hard evidence those rules actually work. Epidemiological data only makes it obvious social distancing does not have a huge effect: the places with strictest social distancing rules do not seem to tend to have fewer deaths. Maybe, just like masks, social distancing has some small effect (say, 18% protection) which is not visible by eye-balling the epidemiological data, but I see no reason to think that other than trusting your intuition and government propaganda over the empirical data.
   It is intuitive to think small droplets move in such a way that you are essentially safe from a person emitting those droplets on the other side of the room. But can we say it's at least possible that the MIT study is telling the truth, that, in most of the situations, that's not the case? Like I've said, I am not saying MIT study is good evidence that social distancing does not work (it appears to contain a bit of circular reasoning), but it's at least food for thought for those who think their intuition about how droplets move is strong mechanistic evidence that social distancing works. MIT study is certainly better than our intuitions, and it suggests that social distancing might not work. We need to look at the empirical data to determine whether it actually works. And to me it seems that the only empirical data we have is the highly-noisy data from places with social distancing and places without social distancing. And the effects of social distancing are not visible by eye-balling that data. Now, admittedly, neither are the effects of masks or vaccines visible by eye-balling the data about COVID-19 cases, even though they demonstrably do have some effect on lowering the spread of the disease. Like I've said, it's entirely plausible that, just like masks, social distancing provides around 18% protection. Maybe even more, but not a lot more. If you are going to claim that social distancing decreases the spread by about 45%, about as much as vaccines do, I'd like to hear what you think those changes in behaviour are that eclipse those effects of social distancing from being visible by eye-balling the epidemiological data.
   And understand that making ad-hoc hypotheses damages your credibility. At the beginning of the pandemic, the advocates of the mainstream epidemiology told us "Wear a mask to protect yourself.". Then the Danish study proved that masks do little to protect those who wear them (that they provide at most around 18% protection, similar to what earlier studies showed masks do against the flu). Then the advocates of the mainstream epidemiology changed their rhetoric. They are now saying "Wear a mask to protect others from you.". Now, that is a hell lot harder to test than the idea that masks significantly protect you from COVID-19, and is therefore an obvious ad-hoc hypothesis. We tell them that it implies places with masks mandates will have significantly fewer COVID-19 deaths. And, by that time, there has come quite a bit of epidemiological data from both places with mask mandates and without mask mandates, and we showed them that just eye-balling the data made it obvious that's not the case. Then the advocates of mainstream epidemiology responded by saying "You need to adjust for other factors.". Which is significantly harder to do, and is therefore an obvious ad-hoc hypothesis. Then, if you point out the fact (like I did in my previous blog-post) that adjusting for simple other factors, such as life expectancy (as COVID-19 almost exclusively kills the elderly, so we would expect countries with lower life expectancy to have less excess mortality) or distance from the equator (as the sun kills the coronaviruses, so we would expect countries farther away from the equator, with less sun, to have higher excess mortality), does not quite do the trick (if anything, it makes it look even more like non-pharmaceutical interventions are counter-productive), they will demand you to adjust for complicated other factors, such as population density (which varies widely between parts of a country). Which is a lot harder to do, and is therefore an obvious ad-hoc hypothesis (I believe somebody on mises.org actually made a statistical analysis and found that there is no correlation between population density and COVID-19 cases, but I cannot find it now.). Quite a bit like arguing with a Flat-Earther, as Flat-Earthers constantly make ad-hoc hypotheses when their "theory" is proven wrong. Except that Flat-Earthers know the science is not on their side, whereas the advocates of mainstream epidemiology think the science is on their side. And that scientism makes it even harder to argue with them.
   Maybe I sound like a global warming denier. But that's not remotely the same thing. With global warming, the best available data is sea temperature data, and eye-balling it makes global warming obvious. In fact, sea temperature data probably shows around 30% more warming than there really has been, due to the difference in the devices that used to measure sea temperature data and devices that measure it now. The best available data for whether non-pharmaceutical interventions work is excess mortality between places that had those and places that did not have those, and eye-balling that data does not make it obvious that non-pharmaceutical interventions work. Adjusting the continental temperature data for other factors such as time of observation bias does make global warming obvious even there. Adjusting the COVID-19 data for other factors does not make it any more obvious that non-pharmaceutical interventions work, in fact, it makes it look more like they aren't working.
   I used to believe the Earth was flat. Then I used to believe the global warming denier Tony Heller was telling the truth. But I grew out of that. I learned some very hard lessons about epistemology, and I am not falling into similar traps again.
   Mainstream epidemiology appears to be based on trusting incredibly simplistic computer models, with almost complete disregard for empirical data and the pre-COVID science. For example, most of those computer models are assuming everybody infected is equally likely to spread the disease. That's not the case: COVID-19 is spread by droplets, and people with symptoms emit way more droplets than people without symptoms. Since the vast majority of children have no symptoms if infected with COVID-19, the vast majority of children infected with COVID-19 will not spread the disease. And the main evidence the advocates of mainstream epidemiology have that closing schools is effective comes from those simplistic computer models. If the same computer models were applied further, it would follow that vaccines do not lower the spread of COVID-19. That would, of course, go against basics of pre-COVID epidemiology. But such simplistic computer models, which go against basic facts from the pre-COVID science, are what the mainstream epidemiology seems to be based on. Now, whether closing high-schools and universities is effective, I suspect it might be, but I have not seen any empirical evidence of that. And it's important to have actual empirical evidence because we are also dealing with the issues of soft sciences (What do students actually do when you cancel all the lectures? Do they stay home, or does a significant percentage of them go somewhere else instead?). Making a significant percentage of students fail their classes is a significant economic damage (see this update as an example what studying at a university is like during a pandemic), so it should be justified with hard data.
2. Don't pretend immune people cannot spread the virus. While vaccines do indeed decrease the spread of COVID-19 by around 45% (as this study suggests), and provide some small protection (maybe 13%, if the Israeli data, from the country which massively tests both the vaccinated and the unvaccinated, is anything to judge by^[1]) against infection, those protections are more than offset by the changes in behavior. Countries with higher vaccination rate mostly have more COVID-19 cases, rather than less (Chile, Israel...). And natural immunity is almost certainly even worse than vaccine-induced immunity.
   And this is a huge no-no, done by both people advocating mainstream epidemiology and people advocating focused protection. People advocating mainstream epidemiology often say vaccine passports protect immuno-compromized people for whom vaccine won't work. Well, if vaccines provide only around 45% protection against spreading, and only around 13% protection against infection, vaccine passports may very well be counter-productive. Sunetra Gupta, the main epidemiologist advocating focused protection, suggested that only people who survived COVID-19 should be allowed to work in nursing homes. Since natural immunity provides even less than 45% protection against spreading, and it presumably provides no protection at all against infection, implementing that suggestion would almost certainly do more harm than good.
   I also think it is undeniable that vaccine passports are setting a dangerous precedent. Don't you think there is a lot of truth to what anti-vaxxers are saying "If Jews were the spreaders of typhus in the Third Reich, then the unvaccinated are now spreaders of COVID."?
3. Don't make arrogant assumptions about soft sciences. It's absurd to say you can predict how people will behave in such extreme situations such as a pandemic. And understand that computer models, while they are very useful in hard sciences, are often worse than useless in soft sciences. I am saying that as a computer science student who has published a few papers about linguistics (the latest one being about applying collision entropy and birthday paradox to calculate the p-values of some patterns in the names of places in Croatia). I have tried to make a computer model of the phonological evolution of languages (which is used in my Etymology Game), and, when I validated it using the real-world data, I got surprised that it performs little better than chance (if it even does word better than chance, it's possible that the control model which I took as "chance" actually does worse than chance). The same is likely true for your computer models of things in soft sciences. And that's in normal situations. It would then, of course, do worse than chance in non-normal situations.
   Almost everybody thought shutting down most business will result in fewer people dying in car accidents. As it turns out, deaths from car accidents increased in 2020 compared to 2019. It is hard to explain how lockdowns and business closures may have worked if there were more traffic accidents, rather than less, right?
   And I think proponents of focused protection are doing the same mistake. What would actually happen if we tried to implement focused protection? That is, if we separate families and order young people to try and build herd immunity (which is, in all likelihood, impossible for COVID-19, as immunity from COVID-19 is not remotely sterilizing immunity)? Something tells me it won't go well either.
   And understand that government actions made to address the pandemic have the unintended consequences beyond the pandemic. Shutting down most business and giving people large stimuluses will lead to a huge inflation. Right when the economy appeared to have recovered, a huge inflation started. And large inflation especially hurts people like me, who are without a job and who live of money they got by selling a house.
4. Don't spread too much propaganda about vaccines. If you ask any vaccine-hesitant person why they are hesitant to get vaccinated, the most common response you will get is something along the lines of "All that propaganda is smelly to me". And that's understandable. Government propaganda is often saying that, unless everybody gets vaccinated soon, the virus will evolve to be vaccine-resistant. That's very far from truth, as the resistance to vaccines is a lot harder to evolve than, for example, resistance to antibiotics. Besides, how is everybody getting vaccinated supposed to reduce the small chance of that happening? Isn't saying that like saying everybody being preventatively put on antibiotics will decrease the chance of superbacteria evolving because bacteria will not be able to procreate and thus mutate as much? That's obviously not how biology works. And saying things like that kills your credibility.
   Also, don't you think media propaganda is to blame for the increase in suicide? What else do you think causes suicide during a pandemic? The country with the biggest increase in suicide was Japan. Japan did not have a lockdown, so you cannot blame lockdowns for suicide. Japan was, compared to other countries, hit by the pandemic relatively little (so much so that it had negative excess mortality in 2020), so you cannot really blame the pandemic for suicides either. The only explanation I can see is the fearmongering by the media. Put it simply, loudly yelling "We will all be infected by a deadly vaccine-resistant virus." kills, it causes suicide.
   Also, ask yourself, how irresponsible are anti-vaxxers really, compared to other irresponsible things people do? Could it be that being against COVID-19 vaccination is only as irresponsible as being anti-gun? COVID-19 vaccinations are estimated to have saved around 300'000 lives in 2021 in the USA. According to the famous study done by Gary Kleck in 1995, guns also save around 300'000 lives each year in the USA (around 400'000 people believe a gun saved their life in the last year, but around 25% of that number is probably a result of telescoping, that is, remembering distant events as if they were more recent than they really were). Yet you don't hear nearly as much pro-gun propaganda as you hear pro-vaccine propaganda. You think Gary Kleck's methodology is bad? Well, explain to me why do you think the methodology of the study I linked to, estimating that vaccines saved 300'000 lives in 2021 in the US alone, is good? Do you even understand their methodology? I personally don't. Also, if you are going to claim the Gary Kleck's methodology is bad, isn't there a burden of proof on you to do or at least point to a better study? As far as I know, no other study tried to estimate the number of lives saved by guns in the US each year. If you think it's enough to complain about the flaws in methodology to discard a study, read up on conspiracy theorists (perhaps The Mad Revisionists - the conspiracy theorists who claim the Moon doesn't exist) and consider the matters again. You cannot manufacture the truth by discarding the evidence. That's not how science works. Gary Kleck's study is, until you point to a better study, the best data we have. And I see no reason to think that almost everybody who thinks a gun saved their life is somehow mistaken, which seems to be the only way Gary Kleck's study could be wildly wrong.
5. Preserve the rule of law. That means, don't pass blatantly unconstitutional eviction moratoriums, and let the same laws that apply to everybody else apply to the pharmaceutical companies producing vaccines. Otherwise, you are setting a very dangerous precedent. Unless, of course, that is what you want. Maybe you want people to believe rule of law is worse than useless.
   Also keep in mind that the Constitution was written during a severe smallpox pandemic. Since the Founding Fathers thought that laws such as eviction moratoriums were not a good idea back then (that's why they made them unconstitutional), they would also think that now, when the epidemiological situation is a lot better. And, yes, they understood how smallpox spread. They inoculated the entire army with smallpox with a precursor of vaccine that had around 3% mortality rate, so that the soldiers won't catch smallpox during a battle, which would kill around 20% of them. It is undeniable the Founding Fathers thought eviction moratoriums were a bad idea. It is slightly harder to tell what they would think about lockdowns or forced vaccination for everybody (you could argue they didn't force everybody to get vaccinated with a "vaccine" that kills 3% of the people only because it had 3% mortality rate), but I think they would also think those were a bad thing as well.

I hope that now the "let it rip" strategy of dealing with pandemics seems a lot more reasonable now than it seemed before reading this. I understand that you feel the need to do something rather than nothing. But you need to understand that the same tendency made medieval physicians do things such as bloodletting, which were worse than useless.
The COVID-19 pandemic probably started on a wet market, and there is little government could do to prevent it. Although it may have been contained if only the Chinese government did not try to censor the early reports about it. But there are things governments can do to prevent future pandemics. Governments could stop funding the dangerous gain-of-function research. And they could also stop massively subsidizing the egg industry, which, the way it's done today, gives birth to superbacteria. Unless they do those things, I am afraid they have no right to say they care about public health.

UPDATE on 26/08/2023: Just thought I might give a quick example how difficult studying at a university during a pandemic is. I think what caused a significant amount of hassle was the fear that restrictions that were not currently in place would come in place, so people behaved as if those restrictions were already there. For example, my Computer Architecture professor Ivan Aleksi was afraid what would happen if the physical laboratory exercises were cancelled. For our laboratory exercises in Computer Architecture classes, at the FERIT University in Osijek, we use PicoBlaze as an example of a simple computer. He was afraid that, if the physical laboratory exercises were cancelled, students would run into a lot of technical problems trying to use existing PicoBlaze assemblers and emulators on various computers they have at home (in my opinion, rightly so). He knew I knew both JavaScript and assembly language, so he asked me to create a PicoBlaze assembler and emulator that could be run in any modern Internet browser. I succeeded at that, however, that was not an easy task. It wouldn't be an easy task even for experienced developers, yet alone me. I didn't have enough time for studying the university curriculum. Professor Ivan Aleksi in return freed me from the assembly language test, but I am quite sure it would have taken far less time to prepare for an assembly language test than to make that PicoBlaze assembler and emulator. And it turned out that my work was basically in vain, because laboratory exercises were not actually cancelled. If I wasn't tasked to make a PicoBlaze assembler and emulator because of the professor's fear that physical laboratory exercises would be cancelled, perhaps I would have already graduated.
Not to mention that, during the pandemic, I often ran into technical problems making me unable to follow the lectures and auditory exercises. Many of them were caused by the programs the professors chose to use to hold lecutres and auditory exercises being incompatible with Oracle Linux, which I was forced to use at the time (because Windows 10 and Ubuntu both crashed at the beginning of my attempt to install them on my laptop due to the BIOS bugs, and Oracle Linux only logged a ton of ACPI errors, but otherwise it worked). Many of them were caused by professors attempting to use the CarNET servers, which were overloaded and didn't work, so the lectures and exercises had to be cancelled. If it was this bad on a university teaching IT, I can only imagine how bad the situation was at other universities. If not for such problems, maybe I would have already graduated.

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^[1] It is hard to tell whether that 13% is an underestimate or an overestimate. Maybe vaccines provide less than 13% protection against infection, and unvaccinated, being less health-conscientious, are slightly more likely to attend indoor celebrations than vaccinated people are. Maybe vaccines provide significantly more than 13% protection against infection, but vaccinated are behaving as if they cannot spread the virus and are massively attending indoor celebrations. I see no way to tell what's going on in Israel.