This is an update to a previous post here referencing the phenomenon of “Hot Lots”, in which it was shown that there is a strong suspicion that the Covid-19 injection batches are not being produced consistently, with most lots seemingly relatively harmless (in the short term at least), while others are considerably more dangerous and causing great harm. As before, without knowing for certain the quantity manufactured in each lot, we cannot make definitive statements, but certainly the data itself implies that there is something not quite right, intentionally or unintentionally, about the manufacturing and/or distribution process.

First, we show the current distribution of Lot Numbers by manufacturer as compared to the previous post:

As before, another caveat is that the lot number data in VAERS is terribly inconsistent and does not appear to have been subject to even a minimal amount of data Quality Control. Regardless, I do not believe this affects the observable trends and the general conclusions that we can gather from this data. It just means that our numbers are not as precise as they could be.

Next, we plot the histograms showing the frequency of occurrence of lots containing various ranges of death and adverse events. We find that this time around, 100% of the deaths occurred in 11.1% of the available lot numbers (whereas it was 4.6% in the prior post). Also, only 5.3% of the lots cause more than 100 adverse events, and only 12% of the lots cause more than 10 adverse events.

So as before, we again conclude that a minority of lots are causing the majority of harm.

Now we show charts showing the Top 100 “Hottest” lots for each manufacturer. Deaths first:

Pfizer

Moderna

JNJ

Now show all Adverse Events:

Pfizer

Moderna

JNJ

Since the Pfizer lot numbers typically start with two letters (eg. “EN”), followed by a 4 digit number, what happens when you group adverse events together based on the first two letters of the lot number? It perhaps become a bit easier to see which lots are associated with the greatest harm. In the first chart, what you will see is that group EL is associated with 1401 deaths, followed by group EN, at 1126, then EJ at 946, and EW at 928. Note that we removed any groups from the chart which didn’t have at least 2 deaths in order to remove some of the noise from our chart. The 2nd chart shows the same type of thing, but for all adverse events instead of just deaths. In this case, EW stands out at 67343 adverse vents, followed by EL at 43002, ER at 37276, and EN at 36309. For this chart, any lot number groups which had less than 100 events were removed to make the chart clearer.

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Moderna lot numbers are trickier, as it appears some of them are a 7 or 8 digit numeric value only, and are start with “300” or “3000” at the beginning of it (eg. “300001176”), while others are mostly a 3 digit number followed by a letter, followed by “20A” or “21A” (eg. “039K20A”). We can create groups for the first type by including the next digit that follows the “300” or “3000” (eg. “300001176” would be considered group “300001”). For the second type, we will create groups based on the middle letter and every character after it (eg. “039K20A” would be considered group “K20A”). We again remove from the 1st chart any group which doesn’t have at least 2 deaths and remove from the 2nd chart any groups which have less than 100 adverse events.

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Same procedure, now do the JNJ jabs:

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Downloadable data in an Excel spreadsheet now also includes tabs to see breakdown of Deaths and AEs by both Lot and State: