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Statistics for new Covid-19 cases are unreliable.

1 Name: Anonymous 2020-07-25 07:23
The statistics for new cases are unreliable for at least two reasons:

1) The testing is very inaccurate (high rate of false positives), and
2) The methods for recording new cases are very poor (people that skip their tests are getting recorded as positive)

The statistics for covid-related deaths are unreliable for at least one reason: People that don't die of covid are getting recorded as having died from covid.

So why do people keep relying on data that is unreliable? Are they unintelligent? Are they deceptive and politically-motivated? Do they have an agenda? Do they want covid to be blown out of proportion so they can stay home from work and receive more stimulus checks?
2 Name: Anonymous 2020-07-25 08:57
>>1
The issues you mentioned would still result in an under-reporting of actual positives. Unreliable tests would encourage spread of the virus and complicate contact tracing.

Provide proof that people are being reported as dying from the virus erroneously. That data is from hospitals managing cases. It seems incredibly unlikely that there was no involvement from the virus when someone suffering from it dies with a comorbid condition.

People are relying on imperfect data because they live in the real world and care about their families and human lives in general.
3 Name: Anonymous 2020-07-25 12:01
>>2
People get recorded as a covid-related death if they die for any reason after having tested positive for covid. People get recorded as testing positive for covid if they schedule a test and then fail to appear.

So you have people that were never tested being recorded as positive. And you have people that die in motorcycle accidents being recorded as covid-related deaths. The policies for recording cases of covid and covid-related deaths are bad, and it is leading to bad data.

schedule a covid test
skip it
get recorded as a covid case
die in an accident
get recorded as a covid-related death
This is a problem. The data is unreliable.
4 Name: Anonymous 2020-07-25 13:57
>>3
people that die in motorcycle accidents being recorded as covid-related deaths

Yeah I'm gonna need a source on that
5 Name: Anonymous 2020-07-25 15:55
>>4
https://cbs12.com/news/local/man-who-died-in-motorcycle-crash-counted-as-covid-19-death-in-florida-report

Go back to the question. This isn't a political argument, this is about scientific data.
6 Name: Anonymous 2020-07-25 17:52
>>5
https://www.snopes.com/fact-check/florida-motorcyclist-covid-death/

He was reported as a covid death because he tested positive, but was then removed. So, true facts, but outdated. It's not surprising that across the entire country a handful of screw ups like that might occur.
7 Name: Anonymous 2020-07-25 19:09
>>6
He was reported as a covid death because he tested positive, but was then removed. So, true facts, but outdated. It's not surprising that across the entire country a handful of screw ups like that might occur.
It wasn't a screw-up though. The person that recorded him as a covid-related death was following policy to the letter. This isn't an example of one person making a mistake, it's the case that revealed poor methods of data collection.

They can change that one case because it got media attention, but if they don't change their policy then the problem still exists.
8 Name: Anonymous 2020-07-25 20:08
>>7
So, you really think that kind of incredibly unlikely event is so common that the majority of recorded deaths aren't actually related to the virus?
9 Name: Anonymous 2020-07-25 21:13
>>8
No, I do not believe that that one specific example of why the methods of recording cases of covid and recording covid-related deaths is widespread.

What I do think is that that example serves as a good example of why some of the methods of recording covid cases and covid-related deaths are bad, and leading to bad data.

If you want to know how many people have covid and the test to detect covid has a 30% false positive rate then you can't just look at how many people test positive. The reason you can't do that is because someone could test 1 million people that don't have covid and the results would come back that 300,000 of them have covid, even though none of them have covid. Then it would be very easy to mislead people by printing a headline "300,000 new cases of covid!"
10 Name: Anonymous 2020-07-25 22:39
>>9
I haven't been relying on test data since about day 14. It's deeply flawed (especially in the US). But the number of deaths is fairly reliable. The majority of death data is reported from hospitals directly managing the care of patients with the disease.

I prefer to extrapolate the data on the infected rate based on the hard science of survivorship for infected and disease progression.

If we take that data and parse it back based on the progression and estimate the number of infected, the number of presumptive cases far outweighs the number of actual positive tests.

I think the disease is less serious than a 3-5% death rate, but that rate is highly variable, depending on the availability of ventilators and supportive care. 143,868 recorded deaths - still a small enough number of infected that hospital systems aren't overwhelmed yet, so assume a death rate around 1% and you get 14.3 million infected.

CDC's antibody testing suggests about 10 times the actual recorded infections due to the fact that ~40% of infected spread the virus but don't develop symptoms. Only around 5% of cases are potentially life-threatening, and about 20% are severe and possibly debilitating.

The science is evolving still, so I just assume around 10% of the population is or was infected. I'm projecting a final death toll around 1-3 million.

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