I had a similar thought. In reality, it is likely a mix of mostly natural immunity and some without - no way to know the actual number as that data is not presented. However, those with natural immunity are some sub-part of the "unvaccinated". Based on other data, they are likely the lowest-risk cohort and are pulling down the overall…
I had a similar thought. In reality, it is likely a mix of mostly natural immunity and some without - no way to know the actual number as that data is not presented. However, those with natural immunity are some sub-part of the "unvaccinated". Based on other data, they are likely the lowest-risk cohort and are pulling down the overall "unvaccinated" numbers. My conclusion, which is qualitative and not quantitative, is that the lowest risk is almost certainly those with only natural immunity. Those with no immunity at all (natural or vaccinated) could fall anywhere on the chart, we just don't know.
Also, the vaccinated data are certainly muddied by prior infection. If the distribution of natural immunity is the same across all categories, which it most likely is not, then the rates for each category are proportionally correct but the absolute numbers are aided by the underlying natural immunity and artificially low.
What I'm struck with over and over in this whole fiasco is how blurred the data is. Regarding immunity, there are four distinct groups:
1. vax only
2. natural only
3. natural plus vax
4. no vax or natural
Any report or analysis that combines these groups is basically useless.
I do a bit of data analysis for my work, and I always try to avoid lossy aggregation. That is, capture the data in most the most granular form and aggregate during the analysis as appropriate. Then I or someone else can always come back and aggregate it differently. Storage and processing is dirt cheap. It seems like "public health" is stuck in the 20th century. Of course reverse Hanlon's Razor applies. That is, we shouldn't assume incompetence. Aggregation often serves propaganda goals. Lumping naturally immune with "unvaccinated" suits their narrative.
I had a similar thought. In reality, it is likely a mix of mostly natural immunity and some without - no way to know the actual number as that data is not presented. However, those with natural immunity are some sub-part of the "unvaccinated". Based on other data, they are likely the lowest-risk cohort and are pulling down the overall "unvaccinated" numbers. My conclusion, which is qualitative and not quantitative, is that the lowest risk is almost certainly those with only natural immunity. Those with no immunity at all (natural or vaccinated) could fall anywhere on the chart, we just don't know.
Also, the vaccinated data are certainly muddied by prior infection. If the distribution of natural immunity is the same across all categories, which it most likely is not, then the rates for each category are proportionally correct but the absolute numbers are aided by the underlying natural immunity and artificially low.
What I'm struck with over and over in this whole fiasco is how blurred the data is. Regarding immunity, there are four distinct groups:
1. vax only
2. natural only
3. natural plus vax
4. no vax or natural
Any report or analysis that combines these groups is basically useless.
I do a bit of data analysis for my work, and I always try to avoid lossy aggregation. That is, capture the data in most the most granular form and aggregate during the analysis as appropriate. Then I or someone else can always come back and aggregate it differently. Storage and processing is dirt cheap. It seems like "public health" is stuck in the 20th century. Of course reverse Hanlon's Razor applies. That is, we shouldn't assume incompetence. Aggregation often serves propaganda goals. Lumping naturally immune with "unvaccinated" suits their narrative.