We can talk about specific countries all day even though it's unnecessary (indeed, you can see the policies don't work just by examining case curves individually, without comparisons between them). But it's pointless. Everyone who claims Sweden doesn't disprove the scientific basis for lockdowns just comes up with a random new justification as each one is shot down. First it was "Sweden is different because of population density". That was dealt with. Then it was "Swedes don't like to be physically close to each other" (lol). That was dealt with. Then it was "actually Sweden was locked down even though everyone said they weren't". Now it's "but you can't compare Sweden to anywhere except Denmark and Norway". Etc.

The justifications here are based on working backwards from a desired conclusion, yet there's no rational way to do it. For instance, is this talking point "all its immediate neighbours", as you put it? Or just some of its neighbours? Because Sweden is also neighboured by some Baltic states, and if you include those, Sweden is no longer the worst in that little group. So the usual construct is "Scandinavian neighbours", not "all immediate". The incoherency of this claim is a good sign it's made up on the spot - data cherry picking, exactly what people aren't meant to do.

So. "Experts" said Sweden would suffer mass death from not locking down: 90,000 deaths predicted by the ICL model alone. There was no postulated Scandinavian Exception in any model or scenario. Nor has anyone presented any sort of mechanistic or biological explanation for how such an Exception should work. Instead, once their data disproved the underlying theory, people started desperately trying to retrofit the narrative to claim it actually a success rather than accept the truth that epidemiology is, as a field, so incompetent as to be fraudulent. Reality came nowhere near the predictions.

But, if you wish, just ignore Sweden (or Texas, or Florida, or the Dakotas) and present a methodology that reliably selects from case curve data alone the dates of policy changes. It cannot be done. But case data is ground truth: policy was justified on the grounds it would change the rate of infections. Because policy changed for everyone in a country on a single day, there should be very clear artificial changes in infection numbers a few days after that (it takes a few days for symptoms to develop and people to get tested). If you cannot reliably find such changes from the data, then the policies have failed by their own logic. Comparisons are irrelevant at that point because they weren't justified that way.