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Apples to oranges. Minimum wage going up does not give more buying power to the working class. A business has to cut costs to cover it, or raise prices. Cutting usually involves cutting labor costs somehow. That means less hours for workers with them hurting more party time, or it means workers will be laid off. Merit based pay increases and bonuses are a better incentive for productive workers and does not increase costs across the board.
Lockdowns are literally killing small businesses. Increasing the minimum wage would kill small businesses. There is your comparison.
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Lockdowns are literally killing small businesses. Increasing the minimum wage would kill small businesses. There is your comparison.
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I get the sense that these questions serve the purpose of trying to show the virus isn't as bad as data suggest. You questioned the data I gave and wanted OSDH data. I gave that, but now it's not about consistency but the quality of data overall. If that's your perspective, I'm not sure that any information I provide would be helpful. But, on to your questions, the case definitions are searchable on the OSDH website, but in brief, it's somewhat complicated and they do their best to make sure they're giving accurate and timely data, including removing duplicate tests. It's no accident that hospitalizations spike about two weeks after cases spike and will come down about two weeks after cases start to come down. For deaths, I'm not going to dive fully into that. @steross and others have talked about this more and with more first-hand knowledge. What I would say is that you have to basically be saying that fellow medical professionals are engaging in unethical behavior at a large scale for deaths to be that wrong. On the other hand, our deaths match pretty well the increase that we see in COVID cases and COVID hospitalizations. There's always some error in the data, but when that many indicators line up consistently, it's a good sign that your data are appropriate. I'd also add that there are actual experts who publish on the CFR regularly using more complex and accurate methods than the rough version I'm doing that takes data inconsistencies as well as sensitivity and specificity into account. Their last estimates also suggest the CFR is around 1%.
A note on false positives. They are a bigger deal when cases are low because they operate as a function of your total negative cases. If 10% of your true negatives come back positive, then 5% of your overall population will come back with a false positive when 50% of the population is negative. It jumps to 9% when 90% of the population is negative. So, when you see cases increasing, a smaller and smaller proportion of that population are false positives. That doesn't necessarily mean that your CFR will be artificially lowered when cases increase because testing gets strained at the same time where you miss more cases. Again, the legit modelers take both into account. Before, I was just showing you the more accurate way to derive a rough CFR.
A note on false positives. They are a bigger deal when cases are low because they operate as a function of your total negative cases. If 10% of your true negatives come back positive, then 5% of your overall population will come back with a false positive when 50% of the population is negative. It jumps to 9% when 90% of the population is negative. So, when you see cases increasing, a smaller and smaller proportion of that population are false positives. That doesn't necessarily mean that your CFR will be artificially lowered when cases increase because testing gets strained at the same time where you miss more cases. Again, the legit modelers take both into account. Before, I was just showing you the more accurate way to derive a rough CFR.
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https://www.jhunewsletter.com/article/2020/11/a-closer-look-at-u-s-deaths-due-to-covid-19
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Not sure why, but the article is gone. Here's the archived version.
https://web.archive.org/web/2020112...1/a-closer-look-at-u-s-deaths-due-to-covid-19
https://web.archive.org/web/2020112...1/a-closer-look-at-u-s-deaths-due-to-covid-19
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