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- COVID data comments
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This kind of data mishmash is common in medical reporting, because local governments control how, when, and where vital statistics are recorded.
And for the US, some political input on evaluating death certficiates seems possible. In this example, the reporting entities are compiling data from lots of sources and it can get confusing for them and us.
For the US this might be 48 states plus Washington DC. Or not.
Example:
Local government has a holiday, FooBar Day on a Monday, and so they do not report any deaths. Coroners office closed. The next business day, the missed deaths are reported and the data compilers do not necessarily know about holidays. So Tuesday after the Monday looks anomalous.
Point:
You may want to avoid getting 'wrapped around the axle' when you see things like this. AFAIK all of the entities are trying to follow their own protocols. Often you may need to take a look at something else to see if the data is okay.
Example excess deaths:
Normally on the first Monday of July, FooBar County reports an average 20 all cause deaths, with a sigma of 3. But you have 38 deaths all from some catchall category. You might want to assume there are excess deaths: ##38 - ( 20 + \sigma*2) = 12## excess deaths. (yes, 2 ##\sigma## not 3, we used this as a a guideline for a vital statistics project for past epidemics)
There are a lot of other things going on. The above is just a simplification. I use the CDC site
Source | Deaths | Data timestamp |
---|---|---|
https://www]cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html | 175,651 | Aug 23 2020 12:15PM EDT |
https://www]worldometers.info/coronavirus/#countries | 180,724 | August 24, 2020, 16:47 GMT |
Johns Hopkins U ARCGIS* | 176,901 | 8/24/2020, 10:27:56 AM |
https://covidtracking.com (Atlantic magazine) | 168,858 | Aug 24 at 12:19 pm ET |
* Dynamic URL, use Google |
This kind of data mishmash is common in medical reporting, because local governments control how, when, and where vital statistics are recorded.
And for the US, some political input on evaluating death certficiates seems possible. In this example, the reporting entities are compiling data from lots of sources and it can get confusing for them and us.
For the US this might be 48 states plus Washington DC. Or not.
Example:
Local government has a holiday, FooBar Day on a Monday, and so they do not report any deaths. Coroners office closed. The next business day, the missed deaths are reported and the data compilers do not necessarily know about holidays. So Tuesday after the Monday looks anomalous.
Point:
You may want to avoid getting 'wrapped around the axle' when you see things like this. AFAIK all of the entities are trying to follow their own protocols. Often you may need to take a look at something else to see if the data is okay.
Example excess deaths:
Normally on the first Monday of July, FooBar County reports an average 20 all cause deaths, with a sigma of 3. But you have 38 deaths all from some catchall category. You might want to assume there are excess deaths: ##38 - ( 20 + \sigma*2) = 12## excess deaths. (yes, 2 ##\sigma## not 3, we used this as a a guideline for a vital statistics project for past epidemics)
There are a lot of other things going on. The above is just a simplification. I use the CDC site
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