US death peaks 2020-2021: Excess deaths by age group
In my last post, I identified the months and states where the highest increases in deaths occurred in the United States in 2020 and 2021—that is, the peaks of the death waves.
There were 6 peaks: in April, July and December of 2020, and in January, August and September of 2021. In those peak months, I selected a sample of states where deaths increased more than 60%. The intent was to capture a snapshot of what was going on, when and where whatever was killing people was at its worst.
Obviously, this strategy just provides a very general overview of the death peaks—a deeper look will be required to see what the situation was in the individual states included in each sample, as well as in the counties within those states, where the number of excess deaths could have varied a lot.
We also looked at the places people died in the death peaks, and saw that overall, 90% of excess deaths occurred in 3 places: among inpatients in medical facilities (55%); at home (23%); and in nursing homes and long term care facilities (12%). All 6 death peaks were similar in that respect; however, most of the excess deaths in nursing homes/long term care facilities were associated with the first peak in April 2020—aka the New York City mass casualty event.
In this paper, I look at excess deaths by age group during the death peaks, and as usual, find some strange and surprising things.
I also provide an update on the coverup of excess US deaths, with a spurious claim by Dr. Jessica Hockett that mortality data was fabricated, and from Dr. Pierre Kory , a “debate” about a false dichotomy that excludes the possibility of democide.
A summary of excess deaths by age group
Table 1 below contains a summary of excess deaths by age group, in the peak months and states with the highest excess deaths. (Note 1)
Although the concept of “excess deaths” can be complicated, it doesn’t have to be, and per my usual policy, it’s a matter of basic math here. “Excess deaths” is the number of deaths that occurred in the peak month, minus the average number of deaths that month in 2018 and 2019. If the result is a negative number, there was a deficit in deaths; if the result is a positive number, there were excess deaths.
The number of excess deaths at the top of Table 1, shown with yellow bars, is just for context—the number of deaths at each peak can’t be compared directly, since each peak included a different number of states with different populations. On the top left, shown in red bars, is the total number of excess deaths in all the peaks combined.
The lower part of Table 1, with yellow bars, shows the percent change in deaths in each age group, compared to the 2018-2019 average; this can be used to compare the different death peaks. In the center of the table are the states included in the sample for each death peak, which are the states that had more than a 60% increase in deaths that month, and at least 4,000 excess deaths overall in 2020-2021.
Impact on children
In all 6 death peaks, children under 14 were mostly unaffected—the exception was an increase in deaths among 5-14-year-olds in the August and September 2021 peaks. This change may or may not have had anything to do with the COVID19 vaccines, which were rolled out to 12-15-year-olds on May 21, 2021, but which weren’t officially rolled out for children aged 5-11 until November 2021. It would be possible to break this 10-year age group down into 5-year age groups for more information, but that’s a project for another day (or person).
Impact on adults
In the April 2020 peak, deaths increased fairly equally across the board for adults 45 and older. The same was true in the July 2020 and December 2020 peaks, except deaths increased to similarly high levels starting at age 25.
It seems very odd that whatever was killing people killed roughly the same percentage of adults in all age groups—as if it didn’t distinguish between the young and strong and the elderly and weak. That seems like something a chemical poison might do.
The pattern of deaths got even stranger in 2021, when deaths in the peak months started to increase most among younger adults and the middle-aged, especially the 35-44 year age group.
Did the vaccines have something to do with that change? It definitely seems like something worth looking into—which, of course, means the Centers for Disease Control will definitely not be looking into it.
Death rates in peak months and states, 2018-2021
I wondered if changes in population may have affected excess deaths, especially in 2021—maybe deaths decreased among the elderly because so many had already died. So I looked at the death rates by age group—the number of deaths per 100,000 people in peak months and states, shown in the series of charts below.
The usefulness of these death rates is very specific to this paper—they show the death rate per 100,000 people, in the peak month, in the combined sample states. To get the death rate, I divided the number of deaths in the peak month in the sample states, by the combined population of the sample states, and multiplied the result by 100,000. For more information, see Note 2.
Be aware of the difference in scale of the charts for older and younger age groups. Because the death rates of older people are so much higher than they are for younger people, this was necessary in order to see the details in younger age groups. But, it can be misleading; for example, in Chart 1, the death rate for both age 55-64 (in dark green) and age 45-54 (in bright blue) more than doubled—yet the increase for 55-64-year-olds appears very small in comparison.
PEAK 1 - April 2020: Connecticut, Massachusetts, New Jersey, New York
Chart 1 shows death rates per 100,000 by age group, during the first death peak in April 2020, as well as in April of 2018, 2019 and 2021, for comparison.
In April 2020, the states of New Jersey, New York, Connecticut and Massachusetts experienced more than a 60% increase in deaths.
This death peak is otherwise known as the New York City mass casualty event, in which deaths skyrocketed more than 100% in 25 counties in the NYC metropolitan area in Spring 2020, killing more than 50,000 extra people in just 8 weeks. Apparently, it impacted Connecticut and Massachusetts as well.
In April 2020, the death rate for adults 25 and older doubled or more, nearly tripling for some age groups.
By April 2021, the death rates for all age groups had returned to near normal, but were a little higher overall than they were in 2018 and 2019.
PEAK 2 - July 2020: Arizona, Texas
Chart 2 shows death rates by age group in the July 2020 peak, which primarily affected Arizona and Texas.
The increases in death rate were not as enormous as in the first death peak—but nevertheless resulted in huge increases of more than 50% for adults 25 and older. For children and adults under 25, there was little or no impact.
By July 2021, death rates were much lower than they had been in July 2020, but remained elevated, compared to 2018 and 2019.
PEAK 3 - December 2020: Arizona, California, Kansas, Nevada, New Mexico, Ohio, Oklahoma, Pennsylvania
Chart 3 shows death rates by age group in the third death peak in December 2020, in which 8 states had more than a 60% increase in deaths: Arizona, California, Kansas, Nevada, New Mexico, Ohio, Oklahoma and Pennsylvania.
Mid-way through December 2020, the 14th, is when the COVID19 vaccination campaign officially began for adults 16 and up.
Once again, a year later in December 2021, death rates had declined considerably—but this time, only for older age groups. For younger people—ages 25-54—death rates remained high—close to what they were during the death peak. This is consistent with my general observations about excess deaths for adults in this age range.
PEAK 4 - January 2021: Arizona, California
Chart 4 shows death rates by age group during the peak of January 2021—the month after the vaccination campaign began—compared to January of 2018, 2019 and 2020.
Only 2 states, Arizona and California, had more than a 60% increase in deaths that month, and were included in the sample of states with the highest increases in deaths.
For all age groups, death rates were normal in January of 2018, 2019 and 2020—then nearly doubled, or more than doubled, for adults 35 and older in January 2021.
Death rates for young children were again unaffected, as in all the other death peaks. However, there were noticeable increases in death rates for everyone 15 and older in 2021.
PEAK 5 — August 2021: Florida, Louisiana, Mississippi, Texas
The fifth peak in August 2021 primarily affected Florida, Louisiana, Mississippi and Texas.
For adults 15 and older, death rates were already somewhat elevated in August 2020, then increased further in August 2021.
One interesting thing is that, for ages under 65, the increase in death rates in 2021 was greater than the increase in 2020; but for ages 65+, the first increase in death rates in 2020 was larger than the increase in 2021.
I don’t know what it means, but it’s consistent with the idea that the later 2021 death waves were more deadly for younger adults than they were for older people.
PEAK 6 — September 2021: Alabama, Florida, Georgia, Idaho, Kentucky, South Carolina, Tennessee, Texas
In the sixth death peak in September 2021, 8 states experienced a 60% or more increase in deaths: Alabama, Florida, Georgia, Idaho, Kentucky, South Carolina, Tennessee and Texas.
Overall, the pattern of deaths in peak 6 was very similar to the pattern in peak 5 (which makes sense because they are consecutive months). Children were unaffected, but death rates for ages 25 and older were somewhat elevated in September 2020, then increased further in September 2021.
However, this time, the increases in death rates for all adults 25 and older tended to be larger in 2021 than in 2020.
Overall, the increases in death rates in the last peak tended to be more modest than in the previous peaks, at least in older age groups.
Discussion for people who are genuinely interested in the facts about US mortality—or not
Is it just me, or does it seem like no one is even trying anymore? An astounding number of people these days seem to think their unsupported opinions about facts matter more than the actual facts. It’s hard to tell sometimes whether it’s laziness, corruption, incompetence, or something else.
Don’t get me wrong—I don’t have anything against opinions, especially when they emanate from someone wise. Opinions can be food for thought, and the impetus for discussion, investigation, and revelation.
What I have a problem with are opinions masquerading as facts. And there is no place I’m more tired of opinions masquerading as facts than when it comes to US mortality, especially in 2020 and 2021. The number of people inflicting us with their baseless opinions about it, or outright lying about it, is mind-boggling.
Might as well roll the dice on what we’ll hear next: There were no excess deaths; there were excess deaths, but they were all due to toxic treatment and prevention protocols; the deaths were fabricated in a massive criminal conspiracy. No one ever seems to have any actual supporting evidence from the CDC WONDER database, in spite of its extensive search capabilities, which are 100% free and available to the general public.
Do their theories fit the evidence we’ve seen here—that adults of all ages were impacted across the board by the death waves? Do their theories fit the evidence we discovered last time, that most deaths occurred among hospital inpatients, and at home? Do their theories fit all the other mortality data I’ve documented on my CVax Risk page, and elsewhere on my blog?
I sure hope some of the baseless opinionators out there will make good use of the evidence I’m coming up with, but I won’t be holding my breath—the facts seem to be problematic for a lot of different agendas.
Data fabrication in WONDER?
I’m not opposed to the possibility of data fabrication in general, because the reality is, we live in a world where a lot of things are definitely fabricated. In fact, there is certain data in the WONDER database that would probably be pretty easy to manipulate—for example, population numbers, which are used to calculate death rates, including the sometimes suspect “age-adjusted” death rates.
However, there are some serious limitations on data fabrication in a database like WONDER, which is freely accessible to the general public 24/7. This database is widely accessed on a regular basis, not only by CDC employees, but also by other government agencies, academic institutions, private companies, and many interested individuals, like me. The results of their searches are routinely stored, both in the WONDER database itself, and in private documents.
In other words, a lot of people will observe and document everything that happens in the WONDER database, so any criminal fraud would have to take place right under the noses of thousands of users, without arousing suspicion.
In addition, mortality data, obtained from death certificates, is stored at the county, state and federal level. To the best of my knowledge, no significant inconsistencies have been found between county, state and federal death data.
Jessica Hockett magically transforms her unsupported hypotheses of data fabrication into fact
Up to now, I’ve given Jessica Hockett the benefit of every doubt, assuming her hypothesis that deaths in the NYC mass casualty event were fabricated was made in good faith. But she apparently has little interest in collecting evidence to support her largely unsupported hypothesis, instead preferring to simply adopt the belief that it magically transformed into fact. She said in this recent article:
“Unfortunately, official data related to the New York City’s staggering city death toll appear false. Authorities have not yet disclosed proof the event occurred as presented. There is no complete list of names, no way to obtain death certificates of all the deceased, no federal inquiry into what happened or why, and very little interest from American anti-mandate/health freedom advocates in probing what transpired.
“The unbelievable hospital mortality is not well- or fully-explained by ventilator use, extant data on nursing home residents who died in the hospital, or Remdesivir. We also have bizarre death processing reported by the medical examiner, and a taxpayer-funded hospital system refusing to release basic data to the public.”
In support of her largely unsupported hypothesis of data fakery, Hockett provided a link to an article she wrote in September 2023, in which she proposed 5 hypotheses about how the mortality data could have been fabricated. I critiqued Hockett’s 5 hypotheses in the second half of this paper—and made her aware of it at the time. I don’t know whether she ever read it or not, but that’s neither here nor there, since Hockett is free to read, or ignore, anything she wants to—the only person responsible for the integrity of Hockett’s hypotheses is Hockett herself.
The details about this “false” data have always been sketchy, including the basic issue of what counties and agencies Hockett thinks may have been involved in the criminal conspiracy to alter government records. Hockett has consistently limited her commentary and claims to 5 counties comprising New York City proper—however, as I’ve shown previously multiple times, the NYC mass casualty event heavily impacted 25 counties in the NYC metropolitan area, which experienced massive increases in death of more than 100% in April 2020.
Also, as we’ve seen in this post and the previous one, the NYC mass casualty event apparently spilled over into Connecticut and Massachusetts as well. Were those deaths also fabricated? What about the other death waves in 2020 across the US—were those deaths fabricated? These critical details remain a mystery.
In my critique, I refrained from pointing out that Hockett’s hypotheses revealed a serious lack of knowledge about how the CDC WONDER database works—I got the distinct impression that Hockett hadn’t used the WONDER database much herself, if at all. Two of Hockett’s hypotheses were just not feasible, given the inherent constraints of the database.
However, in my critique, I pointed out that 2 of the remaining 3 of Hockett’s hypotheses could be investigated further, using the free search functions of the CDC WONDER database itself. Hockett either hasn’t done this additional investigation, or any other additional investigation along those lines—or if she has, she’s kept the results to herself.
Pierre Kory covers up US democide with a false dichotomy
False dichotomies always raise my ire—we’re surrounded by them. False dichotomies are used to convince people they have only 2 choices, thus effectively constraining ideas: Republican or Democrat; liberal or conservative; Darwinian evolution or Christian creationism; Germ Theory or Terrain Theory.
In Dr. Pierre Kory’s case, he titled his false dichotomy, “Debate: Was Covid-19 A Pandemic Caused By A Novel Pathogen Or Was It Created Solely By Harmful Policies and Fear Propaganda?”
My answer to Dr. Kory’s debate is the same answer I always give to false dichotomies: “No.” If he doesn’t get why my 1-word answer works in this situation, that’s not my problem.
COVID19 was a democide. It wasn’t a pandemic caused by a novel pathogen, or created solely by harmful policies and fear propaganda. Kory and Hockett both need to face that dark reality.
***
NOTES
1) To find deaths by age group in the peak months in the sample states, run the saved searches below in the CDC WONDER database. Citations for these searches are below.
July 2020: https://wonder.cdc.gov/controller/saved/D157/D375F068
December 2020: https://wonder.cdc.gov/controller/saved/D157/D375F070
January 2021: https://wonder.cdc.gov/controller/saved/D157/D375F071
August 2021: https://wonder.cdc.gov/controller/saved/D157/D375F072
September 2021: https://wonder.cdc.gov/controller/saved/D157/D375F073
2) To find the population by age group for the sample of states in each death peak, run the following searches; citations are below for these searches.
Due to limitations of the WONDER database, in order to get the population numbers for the age groups in the sample states, the searches were structured to find yearly deaths (not just deaths in the peak month), among residents of the sample states (not deaths that occurred in the sample states—which is what we are measuring here). To find the number of deaths that occurred in the sample states in the peak months, see Note 1.
April 2020: https://wonder.cdc.gov/controller/saved/D176/D375F125
July 2020: https://wonder.cdc.gov/controller/saved/D176/D375F376
December 2020: https://wonder.cdc.gov/controller/saved/D176/D375F456
January 2021: https://wonder.cdc.gov/controller/saved/D176/D375F464
August 2021: https://wonder.cdc.gov/controller/saved/D176/D375F468
September 2021: https://wonder.cdc.gov/controller/saved/D176/D375F469