I have done some more analysis, this time by “age group”. Using this with “employment type” we can start to cross-reference some data.
Doing this cross-referencing is not hard. But it does get somewhat difficult trying to explain. It’s sort of an: If A=B AND A=C, THEN B=C. For those that like data, I give you the data. For those that don’t, the best I can do is offer you the summary.
Personally, I found the information telling. I hope that it allows you, as well, an opportunity to see the data in a way that has not been presented otherwise (at least not that I know of), and most definitely is not being presented by the media.
As a reminder, this data is from Iowa, and comes from the Iowa Covid website.
DEATH BY AGE GROUP………………….
Let’s first look at the “unknown pre-existing conditions” by age group (you will come to understand why)..…..
18-40: 2
41-60: 51
61-80: 242
81 and greater : 300
As is, the data indicates that 542 people 61 or older had “unknown pre-existing conditions”, or 91% of all unknowns. That is a high correlation of all unknowns being above 61.
If you recall, the data in the “retired/unemployed/disabled” categories (that is, “not working”) showed 578 “unknowns”. That results in a 93% correlation between “not working” and “61 or older”. This too is a high correlation.
Using the above data, and if one would graph it (I did) you would find a curve that steepens increasingly with age. Once this graph is drawn, you can use that line to interpret it for any specific age or age range.
Not surprisingly, it shows that more of the “unknowns” in the 41-60 range are found considerably more towards the 60 end of the range than towards 41.
Add to the 542 “above 61” unknowns the majority of the 43 “unknowns” in the 41-60 range (that fall toward closer to 60)…..you now approach a nearly 100% correlation between those “close to 60 and over” and those “not working”.
Therefore one can reasonably confidently infer that the “unknown pre-existing conditions” applies to only “not working” people.….which correlates almost exclusively to people over 60. That is……for whatever reason, the “unknowns” are found only in people of or nearing retirement age, and very probably retired.
That is important because the inverse is true…..
Among people under 61……“unknown pre-existing conditions” largely do not exist. The few that do, are minimal and pretty much statistically irrelevant. (And perhaps apply to disabled, or otherwise early retired due to possible health reasons.)
The presence of “unknowns” being only in the retirement age is bothersome, if not outright troublesome.
Previously, I suggested that these “unknowns” were people that had fallen off the grid, such as welfare, or otherwise not having gotten documented medical help. Looking at the age correlation, that now appears incorrect.
Instead, it suggests the data is simply inadequate for those people who died of Covid over the age of 60.
More telling….is that over 50% of the “unknowns” come from 81 or older. This strongly suggests that the majority of the “unknowns” are coming from the infirm/nursing home group of people.
Perhaps, especially in the early stages of the pandemic, pre-existing conditions data was simply not sought after to be recorded. Or it could be that researching and recording the data was (or maybe still is) simply not necessary or otherwise not considered important to do.
What we do know as a fact of data…… is that a high percentage of Covid deaths (just under 50%) are from people in long term care. So recording the death as “Covid” was almost assuredly considered important (for financial reasons, for one), but recording other existing conditions may not have been considered necessary.
On the other hand, it is well recognized that deaths attributed to Covid means that a person died with Covid, not necessarily because if it. Indeed, the high number of documented “unknowns” leads one to speculate that another truly comorbid condition was majorly in play with the Covid attributed death, but Covid was given full credit nonetheless. This though, is only speculation.
Regardless of the cause of this “unknown pre-existing conditions” data, it leaves a HUGE hole in being able to evaluate the impact of possible pre-existing conditions, and very possibly they were comorbid conditions. If that would be the case…..it means that the number of deaths because of Covid is substantially overstated.
Despite this, we have excellent data for people under 61 not tainted with “unknowns”, so let’s take a look at that.
Below is an analysis of people under 61 years of age……
Covid deaths with known pre-existing conditions:
18-40: 18 (0.9% of all deaths)
41-60: 100 (5.1% of all deaths)
Make note again that of the 100 deaths that occurred in the 41-60 range, significantly more occurred at the upper range near 60. Therefore, it can be interpreted that the vast majority of Covid deaths start with people approaching 60. It’s fair to interpret that as while people age towards 60, pre-existing conditions increasingly show up.
Deaths with no pre-existing conditions……..
18-40: 2 (0.1% of all deaths)
41-60: 12 (0.6% of all deaths)
The above is a percentage of total deaths only. Now we can look at the percentage of deaths per total positive tests.
Deaths and death rate for people under 61 with pre-existing conditions……..
18-40: 18 (0.01% of all positives)
41-60: 100 (.007% of all positives)
Deaths and death rate for people under 61 with no pre-existing conditions……..
18-40: 2 (0.001% of all positives)
41-60: 12 (0.06% of all positives)
Deaths and death rate for all Covid deaths to people under 61……..
18-40: 20 (0.007% of all positives = 7 out of every 100,000 positives)
41-60: 112 (0.042% of all positives = 42 out of every 100,000 positives)
SUMMARY:
The chance of death due to Covid for those under 61 is rather low, far lower than total deaths of those when over 61 are included and averaged out over the entire population. Especially true when deaths over 81 are included.
The death rated is even lower yet to people with no pre-existing conditions…1 out of every 100,000 documented positives.
It appears that the common denominator for the vast majority of those that have died of Covid…..is having a pre-existing condition. Not age. Or at least, not age directly.
Age appears to be a indirect factor for the simple reason that an increase in age brings an increase in the likelihood of one having a pre-existing condition.
This appears to be likely true through all ages…..the curve starting to rise notably more steeply as one approaches 60, and gets increasingly steeper after that.
Unfortunately, the (perhaps critical) missing data on pre-existing conditions from those 61 and over, makes it more difficult to accurately analyze this age group. Especially if that missing data perhaps involves truly comorbid conditions as major contributing (and perhaps leading or only) causes of death.
(In my opinion.)
Doing this cross-referencing is not hard. But it does get somewhat difficult trying to explain. It’s sort of an: If A=B AND A=C, THEN B=C. For those that like data, I give you the data. For those that don’t, the best I can do is offer you the summary.
Personally, I found the information telling. I hope that it allows you, as well, an opportunity to see the data in a way that has not been presented otherwise (at least not that I know of), and most definitely is not being presented by the media.
As a reminder, this data is from Iowa, and comes from the Iowa Covid website.
DEATH BY AGE GROUP………………….
Let’s first look at the “unknown pre-existing conditions” by age group (you will come to understand why)..…..
18-40: 2
41-60: 51
61-80: 242
81 and greater : 300
As is, the data indicates that 542 people 61 or older had “unknown pre-existing conditions”, or 91% of all unknowns. That is a high correlation of all unknowns being above 61.
If you recall, the data in the “retired/unemployed/disabled” categories (that is, “not working”) showed 578 “unknowns”. That results in a 93% correlation between “not working” and “61 or older”. This too is a high correlation.
Using the above data, and if one would graph it (I did) you would find a curve that steepens increasingly with age. Once this graph is drawn, you can use that line to interpret it for any specific age or age range.
Not surprisingly, it shows that more of the “unknowns” in the 41-60 range are found considerably more towards the 60 end of the range than towards 41.
Add to the 542 “above 61” unknowns the majority of the 43 “unknowns” in the 41-60 range (that fall toward closer to 60)…..you now approach a nearly 100% correlation between those “close to 60 and over” and those “not working”.
Therefore one can reasonably confidently infer that the “unknown pre-existing conditions” applies to only “not working” people.….which correlates almost exclusively to people over 60. That is……for whatever reason, the “unknowns” are found only in people of or nearing retirement age, and very probably retired.
That is important because the inverse is true…..
Among people under 61……“unknown pre-existing conditions” largely do not exist. The few that do, are minimal and pretty much statistically irrelevant. (And perhaps apply to disabled, or otherwise early retired due to possible health reasons.)
The presence of “unknowns” being only in the retirement age is bothersome, if not outright troublesome.
Previously, I suggested that these “unknowns” were people that had fallen off the grid, such as welfare, or otherwise not having gotten documented medical help. Looking at the age correlation, that now appears incorrect.
Instead, it suggests the data is simply inadequate for those people who died of Covid over the age of 60.
More telling….is that over 50% of the “unknowns” come from 81 or older. This strongly suggests that the majority of the “unknowns” are coming from the infirm/nursing home group of people.
Perhaps, especially in the early stages of the pandemic, pre-existing conditions data was simply not sought after to be recorded. Or it could be that researching and recording the data was (or maybe still is) simply not necessary or otherwise not considered important to do.
What we do know as a fact of data…… is that a high percentage of Covid deaths (just under 50%) are from people in long term care. So recording the death as “Covid” was almost assuredly considered important (for financial reasons, for one), but recording other existing conditions may not have been considered necessary.
On the other hand, it is well recognized that deaths attributed to Covid means that a person died with Covid, not necessarily because if it. Indeed, the high number of documented “unknowns” leads one to speculate that another truly comorbid condition was majorly in play with the Covid attributed death, but Covid was given full credit nonetheless. This though, is only speculation.
Regardless of the cause of this “unknown pre-existing conditions” data, it leaves a HUGE hole in being able to evaluate the impact of possible pre-existing conditions, and very possibly they were comorbid conditions. If that would be the case…..it means that the number of deaths because of Covid is substantially overstated.
Despite this, we have excellent data for people under 61 not tainted with “unknowns”, so let’s take a look at that.
Below is an analysis of people under 61 years of age……
Covid deaths with known pre-existing conditions:
18-40: 18 (0.9% of all deaths)
41-60: 100 (5.1% of all deaths)
Make note again that of the 100 deaths that occurred in the 41-60 range, significantly more occurred at the upper range near 60. Therefore, it can be interpreted that the vast majority of Covid deaths start with people approaching 60. It’s fair to interpret that as while people age towards 60, pre-existing conditions increasingly show up.
Deaths with no pre-existing conditions……..
18-40: 2 (0.1% of all deaths)
41-60: 12 (0.6% of all deaths)
The above is a percentage of total deaths only. Now we can look at the percentage of deaths per total positive tests.
Deaths and death rate for people under 61 with pre-existing conditions……..
18-40: 18 (0.01% of all positives)
41-60: 100 (.007% of all positives)
Deaths and death rate for people under 61 with no pre-existing conditions……..
18-40: 2 (0.001% of all positives)
41-60: 12 (0.06% of all positives)
Deaths and death rate for all Covid deaths to people under 61……..
18-40: 20 (0.007% of all positives = 7 out of every 100,000 positives)
41-60: 112 (0.042% of all positives = 42 out of every 100,000 positives)
SUMMARY:
The chance of death due to Covid for those under 61 is rather low, far lower than total deaths of those when over 61 are included and averaged out over the entire population. Especially true when deaths over 81 are included.
The death rated is even lower yet to people with no pre-existing conditions…1 out of every 100,000 documented positives.
It appears that the common denominator for the vast majority of those that have died of Covid…..is having a pre-existing condition. Not age. Or at least, not age directly.
Age appears to be a indirect factor for the simple reason that an increase in age brings an increase in the likelihood of one having a pre-existing condition.
This appears to be likely true through all ages…..the curve starting to rise notably more steeply as one approaches 60, and gets increasingly steeper after that.
Unfortunately, the (perhaps critical) missing data on pre-existing conditions from those 61 and over, makes it more difficult to accurately analyze this age group. Especially if that missing data perhaps involves truly comorbid conditions as major contributing (and perhaps leading or only) causes of death.
(In my opinion.)
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