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COVID 19: Sebastian Rushworth MD: Do Lockdowns Prevent COVID Deaths?

I really like astute critique of allegedly scientific studies.

Sebastian Rushworth M.D lists his web site as “grounded in science”. And I accept that totally after reading his scatching critique of a Lancet article. It shows just how poorly The Lancet reviews studies, because the numerous flaws are outrageous vs real science.

Select excerpts, with emphasis.

Sebastian Rushworth MD: Does lockdown prevent COVID deaths?

by Sebastian Rushworth M.D, Nov 9 2020

A very interesting article was recently published in Lancet that sought to understand which factors correlate, on a country level, with covid related outcomes. The study was observational, so it can only show correlation, not causation, but it can still give pretty strong hints as to which factors protect people from covid, and which factors increase the risk of being harmed.

The most interesting thing about the study, from my perspective, was that it sought to understand what effect lockdowns, border closures, and widespread testing have in terms of decreasing the number of covid deaths. Although correlation does not automatically imply causation, if there is a lack of correlation, then that strongly suggests a lack of causation, or at least, that any causative relationship that does exist is extremely weak. And considering the amount of money, effort, and resources that have been poured in to lockdowns this year, and that continue to be poured in to them right now, it would be pretty disappointing if lockdowns had such a minimal effect that there was no noticeable impact on mortality whatsoever. Am I right?

...First of all, as mentioned, all the data in this study is observational, so no conclusions can be drawn about cause and effect.

Second, May was relatively early in the pandemic, and it’s now November, so we’re missing about half a year’s worth of covid data...

Third, the analysis builds on publicly available data, often provided by different governments themselves, with widely varying levels of trustworthiness, and with different ways of classifying things. As an example, data from Sweden is infinitely more reliable than data from China...

Fourth, the reseachers who put this study together gathered an enormous amount of data, pretty much everything they could think of under the sun that might in some way correlate with covid statistics. That means that this study amounts to “data trawling”, in other words, going through every relationship imaginable without any a priori hypothesis in order to see which relationships end up being statistically significant. When you do this, you’re supposed to set stricter limits than you normally would for what you consider to be statistically significant results. They didn’t do this.

...The results are presented as relative risks (not absolute risks), which tends to make results look more impressive than they really are...

...

Ok, let’s get to the most important thing, which the authors seem to have tried to hide, because they make so little mention of it. Lockdown and COVID deaths. The authors found no correlation whatsoever between severity of lockdown and number of COVID deaths. And they didn’t find any correlation between border closures and covid deaths either. And there was no correlation between mass testing and covid deaths either, for that matter. Basically, nothing that various world governments have done to combat covid seems to have had any effect whatsoever on the number of deaths.

...the researchers didn’t correct for the fact that they were looking at a ton of different relationships, rather than just one single relationship between two variables. As I have discussed previously in my article on scientific method, the more relationships you look at, the more strictly you have to set the cut-off for statistical significance, since you will otherwise just by chance get a lot of relationships that seem significant but aren’t.

...The authors who performed this study used a 95% confidence interval, as though they were only looking at one relationship between two variables. But they were in fact looking at a ton of variables (they never even specify how many) and a huge number of relationships, so they should have set their confidence interval much more widely.

They did have some results that they claimed were statistically significant, which I haven’t bothered to mention yet, because they’re certainly not significant after statistical correction.

...
First of all, lockdowns do not seem to reduce the number of COVID deaths in a country. Oops. Based on this data, if you want to decrease the number of COVID deaths, you should encourage more people to start smoking, and possibly also start a communist revolution, to equalize wealth as far as possible. Just kidding. As I’ve mentioned, the data is observational, so we can’t say anything about causality. What we can say from this is that lockdowns don’t seem to work – if they have any effect at all, it is too weak to be noticeable at a population level.

...obesity is the strongest covid risk factor that we can do something about. And even if it isn’t the obesity itself that kills people, when we fix the obesity, we also fix the many derangements in metabolism and immune function that go along with it.

You might also be interested in my article about whether vitamin D can be used to treat covid, or my article about whether a low fat or low carb diet is more effective for weight loss.

WIND: wow! This is the sort of critical analysis that is so badly lacking in public discourse and other medical matters. A breath of fresh air.

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