Interesting view on lockdowns and responses to those saying we shouldn't meet with people for Thanksgiving.
But on a broader scale, for many people, their job is essential because it's the ONLY way they can provide for their families and yet they are being shutdown because government politicians are making the decisions as to what is/is not essential. Not even touching on mental health.
“You need to lockdown in your 500 square foot apartment in NYC and cannot have friends visit.”
“I will be at my 8,000 square foot second home on a four-acre lot in the Hamptons with my extended family.”
Sound about right?
The essential vs non essential reality divide, the non's can't live their work from home life w/o the essentials who make it possible, the ungrateful tail is wagging the exhausted dog
Someone stuck alone in a 400 sq ft studio in a city where everything is closed doesn't want to hear that they're selfish and stupid for wanting to spend an evening with family.
We really need to start calling out what is essentially quarantine privilege - people who are lockdown hawks because their quarantine conditions are far more comfortable than those of other people. Not everyone is in a position to forgo certain activities this readily.
This is only one part of it. The other part is people with comfortable living arrangements, quarantining with a significant other or other family members, or in a rural area that enables more freedom of movement etc.
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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Help me with these questions: 1. What is the definition of a "case" here in Oklahoma vs other reporting places in the US and around the world? 2. What is the definition of Oklahoma Covid-19 deaths? Is it anyone testing positive for the virus who dies in Oklahoma. Do all other places use Oklahoma's definition of Covid-19 deaths.
3. In Oklahoma a wide variety of tests for Covid-19 are used with various levels of sensitivity and specificity
making case definition difficult. What variety of tests are used in other reporting places?
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.