4 ms·
How about some citations? At least a few of these claims are wrong. 2,3 I’ve definitely seen at least one study demonstrating the effectiveness of cloth masks i
by joyeuse6701 5y ago
How about some citations? At least a few of these claims are wrong. 2,3 I’ve definitely seen at least one study demonstrating the effectiveness of cloth masks in limiting the projectile spread of the disease. Like, recorded video exploring different masks (not all were effective).
5. China’s lockdown was effective, what are you talking about?
To your last point, Brazil is a good example of a complete failure of individual level solutions.
- native_samples 5y agoOK. No lockdown has been or can be effective because their goal is to reduce case numbers yet when lockdowns are released, cases don't go up. Look at the UK case curves for the last weeks for an especially stark example. Scientists built models on the assumption that lockdowns were effective, and those models of course predicted a huge wave of cases. Politicians decided to proceed anyway with removing restrictions (the so-called "freedom day") and cases dropped drastically. If lockdowns are judged by their own standards of significantly suppressing case numbers, this outcome would not be possible. Citation: https://www.telegraph.co.uk/news/2021/07/28/many-variables-neil-ferguson-making-covid-claims-confidently/ https://www.telegraph.co.uk/news/2021/07/28/many-variables-n... "> This week, Prof Ferguson, of Imperial College, said he was positive the crisis would be in decline by the autumn, despite warning earlier in the month that it was "almost inevitable" that there would soon be 100,000 cases a day and possibly 200,000." The UK is not the only place to have seen this outcome. When Texas decided to eliminate restrictions Biden was so confident that the restrictions were working he said it was "neanderthal thinking". Following their decision, nothing happened. Case curves didn't move at all. If the restrictions were having an impact, that should be impossible, because judged by their own standards their effectiveness is measured in impact on case curves. Now it's my turn to ask you for citations. Why do you think China's lockdown was effective, in the face of evidence from so many other places that they don't work? And why do you think Brazil is a counter-example that shows collectivism works? Remembering that the tiger-protecting rock style arguments so often used to justify them are a fallacy. Edit: oh, I forgot masks. By all means, cite your study, but it doesn't affect my point. Remember that masks as source control are justified by reference to asymptomatic/pre-symptomatic people. People who feel very sick with COVID don't want to go outside anyway, they want to stay at home in bed or even go to the hospital. Masks-for-all were therefore justified via reference to the presumed prevalence of people who didn't know they were sick but were spreading it anyway. This itself has a large number of problems, e.g. when China tested all of Wuhan they concluded that asymptomatic infectiously people couldn't be found. Even the WHO stopped claiming there were asymptomatically infectious people quite early on, refining it only to pre-symptomatic. Given that, demonstrating that if you cough directly into a bit of cloth that most of the cough goes into it has no real relevance. If people were being told they only had to wear masks if they were visibly sick yet had to go outside anyway it might be relevant, but they weren't. Instead the rule was everyone has to wear masks, all the time, even if they are healthy, just in case they actually aren't. For that to work, physically, you have to demonstrate both that asymptomatic spread is a real thing, a large problem, that cloth masks block virus even when someone doesn't have any symptoms and that they block it sufficiently to actually matter. Given that case curves look very smooth and organic, with no clear spikes or drops when mask mandates are added and removed, it seems clear that mask mandates don't work and isolated studies by motivated scientists aren't enough to change that: the ground truth is the data itself.