Something has been bothering me about the way we are calculating vaccine effectiveness (VE) against death. The simplest way to explain to someone VE is to compare the fraction of total COVID Deaths of people who are vaccinated with the fraction of the total population that is vaccinated. If, for example, 80% of the population was vaccinated and 80% of COVID deaths were among the vaccinated, we would say the vaccine has 0 effectiveness against death. If the fraction of COVID deaths among the vaccinated was lower than 80%, then the vaccine has some effectiveness… the greater the difference between the % of people who are vaccinated & the % of COVID deaths among the vaccinated, the more effective we would judge the vaccine to be.
Thank you! I have no background in either statistics, science, or medicine yet the data collection and presentation upon which public policy and opinion seem to have been formed has seemed not to have been based on the right questions to frame it in any meaningful way, leading me to wonder if I'm just going mad, or living in an abjectly corrupt world. Even though I might have to revisit this multiple times to fully understand your work you restore some of my hope.
A slightly positive VE should be normalized to the adverse effects to determine actual risk. The problem is unreliability of VAERS, but we probably have enough insight to draw risk conclusions. Ultimately everyone needs to make a go-nogo decision about the next shot. Individual risk calculation is highly variable, but on average seems to re moment against vaccination.
A more important omission is causes of individual risk. Overall stats show most people are unaffected or mildly affected, and we have a lot of indications of what conditions increase risk -- obesity, vitamin D, diabetes -- conditions that degrade immune health. The bureaucracy wants to sell vaccines, so have suppressed this information, but can probably be reasonably extrapolated from the data we do have.
Great analysis - Thanks for working through that! Do you think that part of the leveling off in death % levels since Week 31 or so could be the booster campaign (since I think you're right to recognize some short-term gains in reducing severe outcomes)?
Are these graphs total all-cause deaths, or covid deaths? We should look at total deaths, because cause of death might be misattributed. For example, Bartram notes that vaccinated people may take longer to die following positive PCR, and if they take more than 28 days they are not counted as covid. https://bartram.substack.com/p/are-deaths-in-the-vaccinated-delayed
When you reach a significant level of vaccination, the people who aren't getting vaccinated will contain a significant proportion of people who weren't vaccinated because it was medically inadvisable -- i.e. they are so old and frail we thought that even a mild reaction to the vaccine would likely kill them, or they are on strong immuno suppressant drugs, and cannot mount a challenge to the vaccine agent no matter how many times you jab them, so it's a waste of time and money to do so, or they are in the middle of treatment for some other disease and getting vaccinated with anything is considered a bad idea at this time. These people aren't all that numerous, but they are also not going away. And when they catch covid, they unsurprisingly die at rates much greater than rest of the population. But it is very disingenuous to use their deaths as an argument that we need to get that tiny percentage of unvaccinated people vaccinated.
The UK has been great in releasing its data, but there still are times where you wonder 'why aren't you tracking <this thing>'? What percentage of Brits have been told it is not medically advisable for to take the vaccine should be something that we can get a rough estimate of, but if that figure is somewhere, I haven't been able to find it.
Nice work. One of the challenges with this type of analysis is the confounding factor of natural protection. For example, in any age cohort there will be vaxxed individuals who would have survived perfectly well without having been vaxxed.
What do you think of the situation in Britain? The fully vax rate is roughly 70% but the vaxed constitute roughly 80% of all deaths from Covid. It would seem that being vaxed make you somewhat more susceptible to dying of Covid.
This article seems to completely miss the point of what is in the data. There is no mention of whether these are Covid- or non-Covid-deaths. Non-Covid-deaths dominate the counts largely, and should not depend at all on the vaccination status (except for those people that are killed by the vaccin). The vaccination curve and death curve are shifted simply because there is a (differential) delay in reporting, and the population numbers are very rapidly changing.
Imagine Netflix releases a new episode of the Crown, and further imagine the graph of it's viewing adoption over time as a percentage of the population is the same as the vaccinated line. Then, in any age group graph, replace the vaccinated line with the Crown line. What does the graph show? It shows a correlation between watching the Crown and dying of Covid, but no causation.
What is needed is a randomized double blind placebo controlled study of test groups with and without the vaccine. If those two lines cross you have determined how long vaccine effectiveness lasts. (Perhaps one reason for the rush to vaccinate everyone is to make it more difficult to find unvaxxed candidates for such a study.)
Seems to support the outcome of that large Swedish study. Given that I would predict VE to continue to worsen into the negative realm by 8 months. Will be interesting to see if that happens on your graphs.
Nice work. One of the challenges with this type of analysis is the confounding factor of natural protection. For example, in any age cohort there will be vaxxed individuals who would have survived perfectly well without having been vaxxed.
Steady-state? If the boosters are coming every 6 months, then 3, then omicron vax, then booster for omicron… What steady-state????
Thank you! I have no background in either statistics, science, or medicine yet the data collection and presentation upon which public policy and opinion seem to have been formed has seemed not to have been based on the right questions to frame it in any meaningful way, leading me to wonder if I'm just going mad, or living in an abjectly corrupt world. Even though I might have to revisit this multiple times to fully understand your work you restore some of my hope.
A slightly positive VE should be normalized to the adverse effects to determine actual risk. The problem is unreliability of VAERS, but we probably have enough insight to draw risk conclusions. Ultimately everyone needs to make a go-nogo decision about the next shot. Individual risk calculation is highly variable, but on average seems to re moment against vaccination.
A more important omission is causes of individual risk. Overall stats show most people are unaffected or mildly affected, and we have a lot of indications of what conditions increase risk -- obesity, vitamin D, diabetes -- conditions that degrade immune health. The bureaucracy wants to sell vaccines, so have suppressed this information, but can probably be reasonably extrapolated from the data we do have.
Great analysis - Thanks for working through that! Do you think that part of the leveling off in death % levels since Week 31 or so could be the booster campaign (since I think you're right to recognize some short-term gains in reducing severe outcomes)?
Are these graphs total all-cause deaths, or covid deaths? We should look at total deaths, because cause of death might be misattributed. For example, Bartram notes that vaccinated people may take longer to die following positive PCR, and if they take more than 28 days they are not counted as covid. https://bartram.substack.com/p/are-deaths-in-the-vaccinated-delayed
When you reach a significant level of vaccination, the people who aren't getting vaccinated will contain a significant proportion of people who weren't vaccinated because it was medically inadvisable -- i.e. they are so old and frail we thought that even a mild reaction to the vaccine would likely kill them, or they are on strong immuno suppressant drugs, and cannot mount a challenge to the vaccine agent no matter how many times you jab them, so it's a waste of time and money to do so, or they are in the middle of treatment for some other disease and getting vaccinated with anything is considered a bad idea at this time. These people aren't all that numerous, but they are also not going away. And when they catch covid, they unsurprisingly die at rates much greater than rest of the population. But it is very disingenuous to use their deaths as an argument that we need to get that tiny percentage of unvaccinated people vaccinated.
The UK has been great in releasing its data, but there still are times where you wonder 'why aren't you tracking <this thing>'? What percentage of Brits have been told it is not medically advisable for to take the vaccine should be something that we can get a rough estimate of, but if that figure is somewhere, I haven't been able to find it.
Nice work. One of the challenges with this type of analysis is the confounding factor of natural protection. For example, in any age cohort there will be vaxxed individuals who would have survived perfectly well without having been vaxxed.
What do you think of the situation in Britain? The fully vax rate is roughly 70% but the vaxed constitute roughly 80% of all deaths from Covid. It would seem that being vaxed make you somewhat more susceptible to dying of Covid.
This article seems to completely miss the point of what is in the data. There is no mention of whether these are Covid- or non-Covid-deaths. Non-Covid-deaths dominate the counts largely, and should not depend at all on the vaccination status (except for those people that are killed by the vaccin). The vaccination curve and death curve are shifted simply because there is a (differential) delay in reporting, and the population numbers are very rapidly changing.
Imagine Netflix releases a new episode of the Crown, and further imagine the graph of it's viewing adoption over time as a percentage of the population is the same as the vaccinated line. Then, in any age group graph, replace the vaccinated line with the Crown line. What does the graph show? It shows a correlation between watching the Crown and dying of Covid, but no causation.
What is needed is a randomized double blind placebo controlled study of test groups with and without the vaccine. If those two lines cross you have determined how long vaccine effectiveness lasts. (Perhaps one reason for the rush to vaccinate everyone is to make it more difficult to find unvaxxed candidates for such a study.)
Seems to support the outcome of that large Swedish study. Given that I would predict VE to continue to worsen into the negative realm by 8 months. Will be interesting to see if that happens on your graphs.
Nice work. One of the challenges with this type of analysis is the confounding factor of natural protection. For example, in any age cohort there will be vaxxed individuals who would have survived perfectly well without having been vaxxed.