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"No, you cannot compare highly disparate countries like that." No? You seem to like citing the New York Times, but they were previously absolutely sure you cou

"No, you cannot compare highly disparate countries like that." No? You seem to like citing the New York Times, but they were previously absolutely sure you could compare them. I can no longer view this story but know what it said at the time: it said Sweden was a "cautionary tale for the world". https://www.nytimes.com/2020/07/07/business/sweden-economy-coronavirus.html https://www.nytimes.com/2020/07/07/business/sweden-economy-c... Back then there was no Nordic exception, because Sweden wasn't proving lockdown theory wrong. The idea that there is something special about it only emerged after their results became much better than elsewhere, revealing that public health had no clue what it was doing anywhere else. By the way, please don't use the New York Times as a source for anything. It's both paywalled and notoriously biased. "Are you willing to compare China and Vietnam with Sweden too?" I already said this above: "Sweden's peers are rich western countries". "The jury is still out about the effects of the lockdowns" The jury went home a year ago dude, you just can't accept what they found. There is no correlation between severity of countermeasures and outcomes (when looking at countries with reliable data). This has been examined six ways from Sunday and the results are always the same - no correlation. You can tell people they should ignore almost all of the data to try and create doubt here, but those of us who actually are intellectually honest will ignore you, because that's not how science is done. Lockdowns were a catastrophe of stupidity, incompetence and malice by the public health community. They must never be allowed to happen again.

spupe 4y ago
> By the way, please don't use the New York Times as a source for anything. It's both paywalled and notoriously biased. I could give you a number of other credible sources to verify that hospitals were in fact exceptionally strained at several points last year, a verifiable and true statement that you do not believe in. You are welcome to provide a source for your claims, I'm sure it would come from a very good, unbiased source. > The jury went home a year ago dude, you just can't accept what they found. There is no correlation between severity of countermeasures and outcomes (when looking at countries with reliable data). This has been examined six ways from Sunday and the results are always the same - no correlation You are wrong again. To just focus on one example, here is a paper published in Science last year, suggesting various distancing measures produced significant reductions in transmission of COVID [1]. I would advise you to follow your own advice and have a look at the evidence, because in this short discussion you were proven factually wrong twice already. [1] https://www.science.org/doi/10.1126/science.abd9338 https://www.science.org/doi/10.1126/science.abd9338
- native_samples 4y ago
  "hospitals were in fact exceptionally strained at several points last year" I've not disagreed with that. Are you conflating "strained" with "collapsed"? Here's the definitions I'm using - very busy isn't collapse or near collapse. It's just busy. You want hospitals to be busy otherwise it means you over-built capacity. The UK healthcare system is currently in a state of collapse. People are dying in ambulances because they're sitting in queues outside hospitals. They're dying on waiting lists because by the time the hospitals can put them into surgery it's already too late. Hospital managers themselves are naming precise dates for when their entire region will "collapse" and they're using that word specifically. The cause is a combination of the general backlog caused by lockdowns, bed-blocking caused by staff fleeing care homes (forced vaccinations etc), a new WFH culture in primary care doctors, and a refusal to abandon useless anti-COVID measures inside hospitals that reduces throughput. But that's a very rare situation, rather specific to the UK, and is also quite recent. "here is a paper published in Science last year, suggesting various distancing measures produced significant reductions in transmission of COVID [1]" It wasn't published last year. It is dated 15 Dec 2020 and uses data only from the first wave. If you're going to cite scientific papers at least describe them correctly! Look, there are tons of junk science papers on this topic because academics are desperate to believe that their advice worked. This particular paper is of a genre popular just after the first wave, in which they take as axiomatic that any reduction in transmission was caused by their suggested policies and then build a model on that assumption. The model then calculates how much of the reduction came from each intervention. These papers are all invalid because the possibility that SARS-CoV-2 acted like every other respiratory virus in the world, and comes in waves that naturally peter out, was ignored entirely. It's unscientific. Later on more waves came and this idea was destroyed by the evidence, but the sort of paper you're citing wouldn't have taken that into account.

spupe 4y ago

> By the way, please don't use the New York Times as a source for anything. It's both paywalled and notoriously biased. I could give you a number of other credible sources to verify that hospitals were in fact exceptionally strained at several points last year, a verifiable and true statement that you do not believe in. You are welcome to provide a source for your claims, I'm sure it would come from a very good, unbiased source. > The jury went home a year ago dude, you just can't accept what they found. There is no correlation between severity of countermeasures and outcomes (when looking at countries with reliable data). This has been examined six ways from Sunday and the results are always the same - no correlation You are wrong again. To just focus on one example, here is a paper published in Science last year, suggesting various distancing measures produced significant reductions in transmission of COVID [1]. I would advise you to follow your own advice and have a look at the evidence, because in this short discussion you were proven factually wrong twice already. [1] https://www.science.org/doi/10.1126/science.abd9338 https://www.science.org/doi/10.1126/science.abd9338

native_samples 4y ago
"hospitals were in fact exceptionally strained at several points last year" I've not disagreed with that. Are you conflating "strained" with "collapsed"? Here's the definitions I'm using - very busy isn't collapse or near collapse. It's just busy. You want hospitals to be busy otherwise it means you over-built capacity. The UK healthcare system is currently in a state of collapse. People are dying in ambulances because they're sitting in queues outside hospitals. They're dying on waiting lists because by the time the hospitals can put them into surgery it's already too late. Hospital managers themselves are naming precise dates for when their entire region will "collapse" and they're using that word specifically. The cause is a combination of the general backlog caused by lockdowns, bed-blocking caused by staff fleeing care homes (forced vaccinations etc), a new WFH culture in primary care doctors, and a refusal to abandon useless anti-COVID measures inside hospitals that reduces throughput. But that's a very rare situation, rather specific to the UK, and is also quite recent. "here is a paper published in Science last year, suggesting various distancing measures produced significant reductions in transmission of COVID [1]" It wasn't published last year. It is dated 15 Dec 2020 and uses data only from the first wave. If you're going to cite scientific papers at least describe them correctly! Look, there are tons of junk science papers on this topic because academics are desperate to believe that their advice worked. This particular paper is of a genre popular just after the first wave, in which they take as axiomatic that any reduction in transmission was caused by their suggested policies and then build a model on that assumption. The model then calculates how much of the reduction came from each intervention. These papers are all invalid because the possibility that SARS-CoV-2 acted like every other respiratory virus in the world, and comes in waves that naturally peter out, was ignored entirely. It's unscientific. Later on more waves came and this idea was destroyed by the evidence, but the sort of paper you're citing wouldn't have taken that into account.