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How many Americans had been infected by the coronavirus by the date of the lockdowns?
I hope you’re sitting down. Here’s my best estimate … and why I think I’m right and the ‘experts’ are spectacularly wrong.
When I discuss “early spread,” I’m really talking about “early cases.” How many Americans do I think had contracted the novel coronavirus by, say, the first day of 2020? Or by March 15, 2020, the date of the lockdowns imposed to “slow” or “stop” the spread of this virus?
I hope you are sitting down …
I believe at least eight million Americans had already been infected by this virus by December 1, 2019 - a month BEFORE the Wuhan outbreak was reported. This figure might have doubled to 16 million Americans by the final day of 2019.
By the time the lockdowns were implemented on March 15, at least 40 million Americans had probably already been infected. If we move move forward to May 1, 2020, probably 80 million Americans had already been infected, perhaps even more.
For context, the experts have repeatedly proclaimed that virtually no cases existed in America before mid-January 2020. This article gives the reasons this obscure freelance journalist (with a science education that ended in 11th grade) thinks he’s right and the experts have been spectacularly wrong all along.
Some experts acknowledge early cases
have been severely under-counted ….
To begin, at least some “experts” think the number of early cases was massively higher than the “case” estimates presented in the first weeks of the official pandemic. According to a May 1, 2020 article published in The Seattle Times:
“More than 1 million people in the U.S. so far have tested positive for the novel coronavirus (by PCR tests), but experts largely agree that is a vast undercount due to slow and limited diagnostic testing in Washington and elsewhere. Some modelers estimate as many as 10 to 20 times more people have been infected …
So according to at least “some” virus modelers, as many as 20 million Americans might have already been infected by May 1st, 2020.
Key question: How would the estimates of these modelers have changed if they had reason to conclude that “community spread” actually began by November 1, 2019 and not on or about February 1, 2020 (which is the assumption they worked with)? In other words, if virus spread had a “head start” of at least three months?
The main reason I believe “case numbers” are still a vast undercount is I believe the results of the “Red Cross antibody blood study” strongly suggest this.
As I point out in this article, this belatedly-published study found that 2.03 percent of blood donors in three states (California, Washington and Oregon) had already been infected by the virus by December 2019.
If one extrapolates the results of this sample of blood donors to the entire U.S. population of 331 million, we get 7.613 million Americans who had possibly been infected by this month.
Authors of the CDC’s Red Cross blood study stressed that results from these samples should not be “generalized” to the entire population. I, however, have chosen to ignore this guidance, which I think is another example of the effort to conceal evidence of early spread.
These cases don’t date to Dec. 16th; they date to Nov. and October ….
Almost all of the articles on the Red Cross blood study say the study’s results date possible infections to Dec. 13-16, 2019. But these are simply the dates this blood was collected, not the dates these people were infected by this virus.
Per numerous studies, it takes as many as five days for detectable levels of antibodies to develop. Detectable levels of antibodies also don’t develop until approximately 10 to 14 days after the “onset of symptoms” (or no symptoms for asymptomatic cases).
This means most of these positive donors probably had this virus in their system by at least early December. Indeed, most were probably infected in November if not October or even earlier.
So when journalists write that the study dates possible spread to Dec. 13-16, 2019, this isn’t accurate. It’s either sloppy, uninformed journalism or perhaps an intentional effort to bury what should have been the real lede of these stories - that virus spread in America, per this study, dates back to November, October or even September 2019.
By logic, if perhaps millions of people had been infected by some point in November, the number of people infected by this virus would have begun to multiply beginning in early November. The fact this virus had already begun to “spread” prior to mid-December 2019 is actually quite important.
If one believe at least 2.03 percent of the population in these three states had been infected by this virus by early December, how many more people would be expected to be infected 3 1/2 or six months later?
Note: As I will develop in later articles and in today’s Reader Comments, I actually think the 2.03 percent figure is probably a significant undercount as well, which is why I think the 7.6 million figure as of early December is probably low.
The importance of ‘R numbers’ and what these numbers are …
“R-ought” numbers inform one’s opinion on this question. ” This article, from the World Economic Forum’s website, provides a layman’s definition of this very important “R Number:”
“R …. measures an infectious disease’s capacity to spread. The R number signifies the average number of people one infected person will pass the virus to.”
This study from November 24, 2020, presents the range of R0 estimates as of the study date.
“The review by Liu et al. compared 12 studies published from January 1 to February 7, 2020, have estimated R0 ranging from 1.5 to 6.68. “
“… R0 of COVID-19 as initially estimated by the World Health Organization was between 1.4 and 2.4. (a median figure of 1.9) …”
“… The Imperial College group has estimated R0 to be between 1.5 and 3.5. While the Italian model estimated R0 between 2.76 and 3.25. “
An “Imperial College COVID-19 response team … used a model assuming R0 of 2.4 …”
R0 evaluated on the Diamond Princess Cruise Ship was 2.28 in early February.
SUMMARY: The lowest estimate of the R number is 1.4, but the figure might be as high as 6.7. The average estimate seems to be at least 1.9, which would mean that each person infected by this virus would subsequently transmit the virus to 2 other people.
For context, the RO for influenza in a typical flu season is 1.3 (lower than Covid’s numbers). Furthermore, the “effective” RO is said to be 1 or lower because of the prevalence of so many people getting flu vaccines, which are rarely effective at preventing the flu, but experts say they are.
How viruses can rapidly spread to many people
The WEF article explains how case numbers can rapidly multiply in the absence of “mitigation” measures like lockdowns, social distancing and masking, all intended to slow or stop this “spread.”
“An R of 1.5 would see 100 people infect 150, who would in turn infect 225, who would infect 338. In three rounds of infection, the number of people with the virus would have more than quadrupled to 438.”
The above synopsis doesn’t provide a time frame on how long it would take for cases to “quadruple,” which could vary depending on numerous factors.
Applying R numbers to the findings of the Red Cross study …
For sake of this thought exercise, I will stipulate that“only” 6 million Americans (not 7.6 million) had already been infected by December 1, 2019.
If the Covid R number was 1.5 and this number had “quadrupled” in two months (by February 1st), this would mean at least 24 million Americans had already been infected by the end of January 2020.
If this number (24 million) doubled and then doubled again by the lockdown dates of March 15, 2020, this would mean that approximately 96 million Americans may have already contracted this virus by time the government took extreme measures to slow or stop the (allegedly) budding spread.
While 96 million might seem like a massive, impossible-to-believe number, it would still only represent 29 percent of the country having been exposed to this super contagious virus by March 15th. Expressed differently, this would mean that 71 percent of the population (235 million Americans) had yet to contract this virus.
When cases were allegedly spiking, they were probably dying out …
Two reasons lead me to conclude that the virus was already “petering out” on its own by the date of the mid-March lockdowns.
1) Approximately one third of the population had already been exposed to the virus by this date … and thus had already acquired natural immunity to the original virus.
2) Winter viruses ALWAYS peter out beginning in late March and April when the weather warms up.
This theory might be countered by the argument that PCR tests were showing a massive surge in cases after April 1st, 2020. However, I think this is largely explained by the explosion in testing that began around this time. Said differently, if PCR tests had been widely administered months earlier, those results would have been through the roof. This is one reason I believe the administration of PCR tests was probably intentionally delayed (more on this in future articles).
The importance of the high-cycle-threshold PCR tests ….
The massive surge in “positive cases” is also no doubt explained by the fact that the cycle thresholds on PCR tests were set so high (intentionally in my opinion). As studies later revealed, as many as 80 to 90 percent of these positives might have been “negatives” if cycle thresholds had been, say 25.
In other words, I believe the spring 2020 surge in “cases” was a mirage. Yes, some people were still getting real Covid, but this percentage was a tiny fraction of the scary figures being published on a daily basis.
Where were all the “sick” people in April and May 2020?
We all remember many people who were “sick” from “something” in the flu season months of November, December, January and February (my two children and myself are in this group). However, I bet few of my readers remember many people in their network of friends and family members who were suddenly getting sick with a “flu-like” illness in April or May 2020.
The conspicuous incidences of “illness” occurred months earlier. Except for exceptions in a relatively small number of urban hospitals, the hospitals that banned all elective and routine medical procedures to brace for a surge of Covid patients were ghost towns in April and May 2020. Local doctor’s offices were not getting a flood of calls from patients complaining of fever, chills, shortness of breath, etc. But they were in November, December and January.
This is why we had to endure lockdowns (which were not 2 weeks) …
The May 2020 article from the WEF website identifies the “bottom line” of epidemiologists and also explains why the entire world was forced to endure many months of extreme lockdowns.
According to the article, the goal of the lockdowns was to bring the R number below 1. A figure “less than 1 means that the virus will eventually peter out – the lower the R, the more quickly this will happen.”
“… An R of 1 and above tends towards exponential growth. An R of below 1 tends towards the end of the outbreak.”
So why did our kids have to stay home and “go to school” via a computer for months? Why couldn’t we attend church, visit a restaurant, go to a basketball game or even let our children play at a public park? Because the experts were trying to get the R0 number below 1.
Here it should be acknowledged that, via common sense, extreme lockdowns, social distancing, banning groups of more than a handful of people, etc. would “slow” the spread of any virus. If most people had close contacts with, say, 50 people a day pre-lockdowns, those close contacts would have shrunk to maybe just immediate family members for perhaps most of the country after the lockdowns.
In the WEF article published May 8, 2020, the author points out that lockdowns did seem to reduce the number of future cases.
“In the UK, chief scientific officer Patrick Vallence said that the nation’s R number is currently thought to be between 0.6 and 0.9, though it varies regionally and in London could be as low as 0.5 to 0.7.”
The article describes these virus-mitigation measures as “heroic” and assumes that if the lockdowns, etc. didn’t “stop” the spread, they certainly “slowed” the spread, which is no doubt true. This is why people like Anthony Fauci and Deborah Birx are proclaimed as heroes who “saved millions of lives.”
Alas, even if these officials slowed the spread beginning in late March, the spread had already begun at least seven months earlier (Regarding virus origination possibilities, I would go back to at least August 2019 and don’t discount the testimonials of people who believe they had this virus months before that).
The WEF article also notes that a goal of the lockdowns was to “prevent a second wave” of the virus. Here it is assumed that the “first wave” happened beginning in late March and April 2020. However, the “first wave” of the virus was almost certainly washing across America by November 2019. That is, all the experts completely missed the real “first wave.”
The ripple of cases in late March and April was made to seem like a tidal wave primarily by fraudulent PCR tests and a fear-hyping press.
If one assumes virus spread began to accelerate by December 1st, 2019, 20 million infections by May 1st (the modelers’ highest estimate) would mean that the number of cases for this very contagious virus had barely doubled in 150 days. The numbers had grown from maybe 7.6 million Americans to, at the very most, 20 million.
If we use the low-end estimates of the contrarian modelers, cases had only increased from 7.6 million in early December to 10 million by May 1st. That is, case numbers hadn’t doubled even once in five months. If the latter estimate is true, the novel coronavirus is/was barely “contagious” at all.
The modelers didn’t have all the information they needed ….
To be fair to virus modelers, the findings of the Red Cross antibody study weren’t released to the public until November 30, 2020 - so by May 1st, 2020 “modelers” wouldn’t have known of these results. In my opinion, this is another reason officials probably intentionally delayed publicizing these results. Doing so kept all the “modelers” in the dark (and the public).
While many American probably think it’s impossible that 66 million Americans (20 percent of the population) could have been infected by May 1, 2020, other thought exercises also suggest how even this large number/estimate might be far too low.
Previous flu seasons tell us how viruses really spread
… and WHEN they spread
For context, for several years, the CDC estimated that 50 million Americans contracted the flu in the the severe flu season of 2016-2017. (Years later, for some unknown reason, this estimate was reduced to 44 million cases of the flu. Estimates of “flu burden” for the 2019-2020 flu season published by the CDC on April 4, 2020 said that “flu illnesses” in America could have ranged from 39 million illnesses to 55 million illnesses. This estimate was also later significantly down-graded, prompting even more eye-brow-raising on my part.
Whether the ILI number from these flu seasons is 36, 44 or 55 million, these people became sick in a period of just a couple of months, most in the months of December, January and February - the peak months of every flu season.
The fact most people become sick with the flu (or an “Influenza Like Illness”) in a period of only a few winter months is a “known knowable” about flu and respiratory viruses. This is also a very important “known knowable” to my thesis.
In a severe or even typical flu season, on average, at least 10 million Americans become sick every month in the three peak months of a six-month flu season (per the CDC’s own historic ILI statistics). Why couldn’t or wouldn’t the same number of people have have been infected with this highly-contagious novel coronavirus?
Indeed, a known knowable about Covid is that cases spiked dramatically in the peak months of the flu seasons of 2020-21 and then again in 2021-2022 (even after most of the population had been vaccinated).
However, according to the official narrative, the novel coronavirus infected virtually no one in the peak months of the 2019-2020 ILI season. Instead, cases didn’t explode until late March and April, when typically an ILI is dying out. And this spike in cases occurred even though the entire country had locked down to prevent the “spread” of “cases” and almost the entire population was wearing masks to prevent the same outcome.
A note about ‘asymptomatic’ Covid cases ….
I’d also note that just about everyone who suffers from an Influenza-Like Illness (ILI) experiences symptoms. If a person has the flu or a flu-like illness, this person is “sick.” With Covid, depending on the study you believe, 20 to 80 percent of people who could be labeled as “cases” were asymptomatic and never become ill.
This means, unlike the flu, perhaps the majority of people infected by the novel coronavirus wouldn’t even know they’d been infected. So with Covid “case numbers,” unlike flu-season case numbers, one would have to tally all the people who became sick, plus the equally large number of people who never became sick.
That is, Covid “case” numbers would be much higher than flu numbers from a given flu season because the flu estimates don’t include “asymptomatic” cases.
If one believes the above deductions are believable or follow logic, the official “narrative” that no American had developed Covid before January 1st, 2020 is not just spurious or specious, but brazenly and stunningly so. Not only did officials conceal (or somehow “miss”) likely early cases, I believe they missed tens of millions of such cases.
As a reminder, if even a fraction of early cases had been identified, it’s possible none of the disastrous government responses that subsequently occurred would have happened.
When I write that officials have concealed evidence of “early spread,” what I’m really saying is that our trusted public health officials concealed evidence of early “cases.” And, in my opinion, these numbers must have been massive. While these numbers should matter (tremendously), as events actually transpired, this possibility was never even acknowledged as plausible or worthy of investigation.