I have been delving into some data analysis again. There are two pictures I would like to share to clearly demonstrate the futility of the current corona vaccines. The plots are based on excess mortality in the EU and the vaccination rate as provided by the EU.
The first plot shows the overmortality compared to the 5 years before corona (red curve). The green curve shows (on an unrelated axis) how many people got their first vaccine. What is surprising, is that the vaccine correlated with a spike in overmortality. This is to be expected because the elderly were the first to receive them. From that perspective: the vaccine functions as a weed-whacker. If the vaccine doesn’t kill grandpa, then corona probably won’t either.
The second point often heard is: the vaccines are efficient. Looking at this plot, this is difficult to confirm. The first peak, had a total overmortality of ~170’000. The second peak an overmortality of ~275’000. And the third peak, which we are only halfway, already has an overmortality of ~161’000. When that peak is over we are very likely looking at ~300’000. Thus: there is no measurable positive impact of vaccination. You might argue: ‘yes but without the vaccine it would be worse’. On the contrary, Such ‘pandemic’ tends to become endemic after a series of peaks, even without vaccination. So the lower peak amplitude we see now, would very likely have happened without the vaccine as well.
In the first plot I only looked at excess mortality towards the baseline, without adding any standard deviations. If we add 4 sigmas, we end up with pretty much the same results. Peak1 ~ 47’000 death, Peak2: ~91’000 death. Peak3: currently 65’000 death, expected ~117’000. However, in this plot it becomes even more apparent that vaccination had no measurable impact.
A few questions come to mind…
– The EU is pretty big; it’s strange to plot together things that are much more local and disperse. For example, plotting the number of Germans getting vaccinations on week X together with the number of unvaccinated Spaniards that 2000km away suffer a wave of deaths on the same week makes little sense. A lot of context would be needed here to gain any insight, wouldn’t it?
– Actually, if plotting vaccinations, why plot the first dose instead of the full vaccination status? How helpful is it to be half-vaccinated?
– Even assuming that the first dose provides some immunity (how much?), there is a lag in time before the immunity starts working. Maybe that dent in the 3rd wave is because of the vaccinations! (or maybe not – just giving an example of how easy it is to reinterpret random data)
– But anyway since the vaccination plot is “on an unrelated axis” (what?? you know the XKCD, right?), it’s impossible to say what any of this means.
What was the point of this at all?
Hello Horacio,
A lot to go through,
– this data covers the European union (as provided by the European mortality monitoring Euromomo), so local flare-ups are not affecting the overall data.
– The data is furthermore lowpassfiltered, so each death is spread out over 12 weeks. Thus, if someone dies a week earlier or later, it doesn’t matter. This makes the analysis more robust towards time based effects.
– I plotted the first vaccination status because then there is an apparent correlation with overmortality. How that is to be explained is open. My guess was either the vaccine kills elderly, or they are more susceptible to corona afterwards or potentially there was a corona peak at exactly the same moment.
– The second vaccination was mostly done by week 270. From then onward, we see no lowering of overmortality, which was the point of the entire post.
– The green line is on a related axis because it comes from the WHO, which covers the european union, but does not have exactly the same countries included as euromomo.
The point:
– The vaccines or not efficient. -> this is pretty much proven by these plots
– The vaccines are not safe -> this is suggested by these plots but not clearly proven.