I also note that every regular blood donor knows that they should not donate blood if they have recently been sick. In general, I believe donors are supposed to wait at least two weeks after their symptoms have expired to donate blood.
This custom, if followed by regular blood donors, might have also influenced the results produced by the one antibody study of “archived” blood donated through the Red Cross. Certainly, few people who were currently sick or who had recently experienced virus symptoms would have donated blood. That is, those most likely to have recently had symptomatic cases of Covid would not be likely to donate blood. This, in turn, would serve to deflate the number of positive antibody results produced in this study.
One might say this cohort (those who had recently been sick) would be small, but in the “flu season” of the 2019-2020, this percentage was apparently extremely high in most U.S. states.
For example, according to current CDC estimates of “flu burden” for the 2019-2020, there were 36 million Americans in this ILI season who experienced “flu illnesses.” This means 10.8 percent of the U.S. population experienced symptomatic cases of ILI - primarily in the months November through February, the peak “flu months.”
While the CDC now says there were 36 million cases of ILI in these cold-weather month, previous estimates (published on April 4, 2020 before these “estimates” were curiously revised downwards) stated that that the “burden” of “flu illnesses) in this ILI season ranged from 39 million to 56 million Americans.
The median of this estimated range would be 47.5 million flu illnesses. This would equate to 14.3 percent of the American population having a “flu” illness before April 4, 2020. The high-end ILI estimate (56 million flu illnesses) would equate to 16.9 percent of the American population being “sick” with some virus before April 4, 2020.
In other words, the number of “sick” people who might have postponed giving blood in December and January was perhaps quite large. Also, December 2019 and January 2020 were the peak months of this “severe” and “widespread” flu season in America.
Because many people who might have normally given blood didn’t (because they were either currently sick or perhaps had recently been sick), the prevalence percentages of 2.03 percent or 1.44 percent are also probably an undercount.
And when counting possible “Covid” cases via antibody study findings, adjustments of only 1 or 2 percent could translate to 3.3 million or 6.6 million possible Covid cases.
Note: In future articles, I will present much more information about the flu season of 2019-2020 as I think this severe flu season is trying to tell us something about when the real “first wave” of Covid started. As noted, I think it is very significant that flu estimates were later significantly lowered, turning a season that had long been described as “severe” into one now described as “moderate.” I also believe the revised flu season estimates constitute yet another effort to conceal evidence of early spread.
You're probaly right or at least close! This was extremely contagious - in my small office of 50 employee's it went through like wild fire back in November 2019! At the time I recall so many people saying the exact same - that bug that's going around! When they started with the experimental shots I warned everyone that we ALL already had it and to NOT take them! People would ask how do you know and we would talk about the symptoms and most said it was the worst flu they ever had. One young girl in my office had difficulty breathing - that's how we were sure we all had it! Now multiply that by 300 million people in this Country! The records are there as I'm certain people went to doctors or hospitals and OTC medications were probaly excessive as well
Bill, you should come on my podcast Messy Times to discuss this. I live on the Space Coast of Florida, right near Patrick Air Force Base. Hundreds of kids in a local high school were knocked flat by an unknown respiratory illness in October and November 2019. Recall that Patrick had direct military flights to Wuhan, where the Chinese and American military had been holding "Olympics-like" games together - part of a person-to-person attempt to forestall WW3.... I've had front line doctors and nurses on the show talking about the fact that all of that acquired immunity was why our county had infection and hospitalization rates 3 standard deviations below the national mean in 1H20.
Of course, for stating those basic, verifiable facts, I was kicked off Linkedin and YouTube for - of course! - spreading "misinformation."
Dec 1, 2022·edited Dec 1, 2022Liked by Bill Rice, Jr.
This is excellent, and I appreciate a refresher summary of what can be said about R naught in the early days. In terms of asymptomatic infection, I had adopted GVB's opinion that it wasn't a thing until the mRNA inoculations were rolled out. I am still inclined to believe that.
This is awsome! thank you for the research! I was following Dr John Campbell (I think he's finding the red pill quite sour in taste now): a couple of weeks back he was not only mentionning this, but thousands of comments came from around the world to testify of their bad flu in the fall of 2019. PLEASE don't forget also, that in 2019 those who had to seek medical help for their 'bad lung cold" got medication for such (antibiotics, some cortisone pumps, etc...). Now, the minute they labelled the bug with a name, they stopped all prescriptions. -Good luck to y'all, come back when you're blue- type of approach. And that made a huge difference in later outcomes. And to add insult to injury, later ignoring the other off-label adequate medications. This I call a sin.
Very interesting & disturbing; our “experts” are either incompetents or liars. Either way they brought social, economic & educational disaster upon our nation.
The damned "pandemic" was over by May 1st, 2020, and I was recovered from even the malaise on 13 March 2020, so Gov. Gary Herbert Hoover and State Epidemiologist Angela Dunce locked everything down so I couldn't get novels other than SARS-Divok-2 from the library.
Sure glad I got cataract surgery in early January, 2020.
Think about this as well. The modelers cited by the Seattle Times said that as many as 10 to 20 million Americans may have contracted this virus by May 1st. But these modelers were working from the baseline ASSUMPTION that the first likely cases of "community spread" in America date back to only February 1st (or "latter January.")
How would these models and estimates change if these epidemiologists and statisticians accepted that "community spread" was actually occurring in early November 2019? That is, the spread commenced three months earlier than they thought.
If they accept that A happened (spread actually began three months earlier), they'd have to dramatically revise their models and estimates. So those estimates of 10 to 20 million infected people by May 1st would have to be be tripled or quadrupled ... or increased by even five or six-fold IMO.
An email friend who is a great student of Covid issues is skeptical of my large numbers. When I pressed him about the flaw in my “logic,” he said the R0 (infection numbers) must be wrong. I don’t mind others challenging my hypothesis as this is what should happen in science or journalism.
However, as I wrote in this email reply, I’m sticking to my guns on this piece.
In my reply I noted that one doesn’t need antibody studies to support the view that R numbers are at least 1.5. Here's my email reply to my skeptical friend:
“I don't think RO is wrong though. I can provide evidence of this from my other articles where I've identified 24 other Americans who had antibody evidence of early spread (and infections that date to before 2020). Many of these people not only became sick, they infected others in their close contacts, who also tested positive.
For example, in the DelRay Beach group of 11 people from one neighborhood who became sick in November and December 2019, this includes three married couples (and one child of these people). All of these people infected at least one other person. It would seem odd if they infected ONLY spouses. The R number in these cases is at least 3 - the unknown person who infected the first married person and then both couples in the marriage. In one case, both husband, wife and one of their children tested positive for antibodies - making that R number at least 4.
Tim and Brandie McCain both became sick at the same time - so one infected the other and we don't know the unknown person who infected the first McCain. Furthermore, the McCains’ roommate at the time became as sick as Tim (he never got an antibody test). Both of their children developed "mild cases" (although they later tested negative for antibodies .... but this fits my hypothesis that those with mild cases aren't as likely to later test positive for antibodies).
Still with the McCains, I'd say we have an RO of at least 4. 1) The first (unknown) person who infected the McCains; 2-3: Both McCains; 4) Their roommate. I won't count the children who had mild cases but it is an interesting coincidence they also developed symptoms. Brandie and other people in Sylacauga, Alabama report that it seems like "half" the town was sick from some virus at the time the McCains got sick.
I think I probably qualify as an example. I became very sick in early January (and had all the Covid symptoms). I think I got the virus from my daughter, who had symptoms one day before I did. She must have gotten sick in school, where about 10 of her classmates were also sick, plus her teacher, plus the teacher's three children. My son later got sick as well. My children had "mild" symptoms. I think we probably had Covid and, like Sylacauga (which is two hours to the north), it seems like half of Troy, Alabama was sick with something at the same time 3 of our 4 family members became sick.
Mayor Michael Melham of Belleville, NJ was sick on or around November 20, 2019. He has said that "many" people at the same conference he attended were also sick. He said many of these people later contacted him by email, supporting his claim and stating they also think they had the same virus at the same time.
So the RO number from the Melham case study would be at least 2 - the unknown person who infected Mayor Melham and Mayor Melham himself. If even a couple of those other sick people also had Covid, this would mean the RO number was 3, 4, 5 or 6? Also, when I mention these unknown virus transmitters we also know from logic that some unknown carrier infected the first unknown carrier/spreader. So you could really add one R factor to these examples.
About 100 people contacted me saying they thought they had Covid. From this group of emails, I added at least 7 other "antibody-positive" early cases. Again, two or three of these cases were among spouses - one infected the other, plus we don't know the unknown person who infected the first member of the marriage.
We’ve both written about the French study where officials DID interview 11 people who later tested positive. 8 of these 11 individuals were either sick themselves in November or December or a close contact was (confirmed by the follow-up interviews). This is also proof that the infected weren't the only people getting infected.
What would be your estimate of how many Americans were sick by January 1st, 2020? Do you think these people who were sick transmitted the virus to others and who transmitted the virus to them?
Anyway, one can use micro case studies to support an R number of at least 1.5. You don't necessarily need antibody studies to prove or reject this theory. Individual case studies tell us what was happening. This is why officials didn't go back and interview those infected people or do "contact tracing" of all their close contacts.
The Red Cross study is important in that it tested blood that had been donated in mid-December 2019 and then early to mid-January 2020. One could assume there was not a long time-lag between the date the antibody test was administered and when these people had experienced an active infection. That is, detectable levels of antibodies had not had as much time to “fade” or “wane.”
Per my hypothesis, one reason there might have been greater “prevalence” (2.03 percent) in the Dec. 13-16 tranche of archived blood is that the antibodies had not had as much time to “fade” as the blood collected in mid-January in the other states. For example, if a donor gave blood January 17 and had a mild case of Covid in mid-November, this infection might not be as likely to be detected by blood drawn two months after this person had symptoms (or even no symptoms).
And/or: Virus prevalence was just lower in these states.
Another important (and I would say conclusive) finding from my study of antibody studies is that people who experienced mild or asymptomatic cases are much less likely to produce antibodies that last (or can be detected) many or even several months later.
In previous articles, I identified at least 24 Americans who tested positive for antibodies four or five months after experiencing symptoms. Almost all of these individuals had severe cases. For example, they had to go to the doctor several times (some were hospitalized) and/or they were bedridden for an extended period of time. None had what could be described as “mild” or “asymptomatic” cases.
This supports the findings of the studies I’ve read. People with mild cases aren’t as likely to later test positive for antibodies. As perhaps most people who have been infected by the novel coronavirus have mild or asymptomatic cases, it follows that this cohort is not as likely to have tested positive for antibodies weeks or months after these mild or asymptomatic cases.
Continuing with limitations or extra discussion regarding the Red Cross blood study ...
Furthermore, as I have either already written or will detail in future articles, the antibody results we do have are almost certainly producing a deflated (or low) number of likely “early cases.”
For example, the Red Cross study - while a pretty good random sample of Americans - is limited by the fact that the vast majority of blood donor are much older than the median age of 38.6. The median age of blood donors was, I believe, 52. Older Americans, including many retirees, do not interact with nearly as many people as younger students or working age citizens. This would mean the cohort most represented in the Red Cross blood sample would have been less likely to contract the novel coronavirus because they didn't come in contact with as many people as younger citizens do.
I also note that every regular blood donor knows that they should not donate blood if they have recently been sick. In general, I believe donors are supposed to wait at least two weeks after their symptoms have expired to donate blood.
This custom, if followed by regular blood donors, might have also influenced the results produced by the one antibody study of “archived” blood donated through the Red Cross. Certainly, few people who were currently sick or who had recently experienced virus symptoms would have donated blood. That is, those most likely to have recently had symptomatic cases of Covid would not be likely to donate blood. This, in turn, would serve to deflate the number of positive antibody results produced in this study.
One might say this cohort (those who had recently been sick) would be small, but in the “flu season” of the 2019-2020, this percentage was apparently extremely high in most U.S. states.
For example, according to current CDC estimates of “flu burden” for the 2019-2020, there were 36 million Americans in this ILI season who experienced “flu illnesses.” This means 10.8 percent of the U.S. population experienced symptomatic cases of ILI - primarily in the months November through February, the peak “flu months.”
While the CDC now says there were 36 million cases of ILI in these cold-weather month, previous estimates (published on April 4, 2020 before these “estimates” were curiously revised downwards) stated that that the “burden” of “flu illnesses) in this ILI season ranged from 39 million to 56 million Americans.
The median of this estimated range would be 47.5 million flu illnesses. This would equate to 14.3 percent of the American population having a “flu” illness before April 4, 2020. The high-end ILI estimate (56 million flu illnesses) would equate to 16.9 percent of the American population being “sick” with some virus before April 4, 2020.
In other words, the number of “sick” people who might have postponed giving blood in December and January was perhaps quite large. Also, December 2019 and January 2020 were the peak months of this “severe” and “widespread” flu season in America.
Because many people who might have normally given blood didn’t (because they were either currently sick or perhaps had recently been sick), the prevalence percentages of 2.03 percent or 1.44 percent are also probably an undercount.
And when counting possible “Covid” cases via antibody study findings, adjustments of only 1 or 2 percent could translate to 3.3 million or 6.6 million possible Covid cases.
Note: In future articles, I will present much more information about the flu season of 2019-2020 as I think this severe flu season is trying to tell us something about when the real “first wave” of Covid started. As noted, I think it is very significant that flu estimates were later significantly lowered, turning a season that had long been described as “severe” into one now described as “moderate.” I also believe the revised flu season estimates constitute yet another effort to conceal evidence of early spread.
Had infected many millions of Americans by March 2020, without a real impact on excess death.
For me, that’s the punchline -- and the indictment.
You're probaly right or at least close! This was extremely contagious - in my small office of 50 employee's it went through like wild fire back in November 2019! At the time I recall so many people saying the exact same - that bug that's going around! When they started with the experimental shots I warned everyone that we ALL already had it and to NOT take them! People would ask how do you know and we would talk about the symptoms and most said it was the worst flu they ever had. One young girl in my office had difficulty breathing - that's how we were sure we all had it! Now multiply that by 300 million people in this Country! The records are there as I'm certain people went to doctors or hospitals and OTC medications were probaly excessive as well
Bill, you should come on my podcast Messy Times to discuss this. I live on the Space Coast of Florida, right near Patrick Air Force Base. Hundreds of kids in a local high school were knocked flat by an unknown respiratory illness in October and November 2019. Recall that Patrick had direct military flights to Wuhan, where the Chinese and American military had been holding "Olympics-like" games together - part of a person-to-person attempt to forestall WW3.... I've had front line doctors and nurses on the show talking about the fact that all of that acquired immunity was why our county had infection and hospitalization rates 3 standard deviations below the national mean in 1H20.
Of course, for stating those basic, verifiable facts, I was kicked off Linkedin and YouTube for - of course! - spreading "misinformation."
This is excellent, and I appreciate a refresher summary of what can be said about R naught in the early days. In terms of asymptomatic infection, I had adopted GVB's opinion that it wasn't a thing until the mRNA inoculations were rolled out. I am still inclined to believe that.
This is awsome! thank you for the research! I was following Dr John Campbell (I think he's finding the red pill quite sour in taste now): a couple of weeks back he was not only mentionning this, but thousands of comments came from around the world to testify of their bad flu in the fall of 2019. PLEASE don't forget also, that in 2019 those who had to seek medical help for their 'bad lung cold" got medication for such (antibiotics, some cortisone pumps, etc...). Now, the minute they labelled the bug with a name, they stopped all prescriptions. -Good luck to y'all, come back when you're blue- type of approach. And that made a huge difference in later outcomes. And to add insult to injury, later ignoring the other off-label adequate medications. This I call a sin.
Very interesting & disturbing; our “experts” are either incompetents or liars. Either way they brought social, economic & educational disaster upon our nation.
#accountability
#crimesgainsthumanity
#treason
Yes, government was late to the party. When has it done anything on a timely basis?
Ok Bill.
Next assignment where did covid originate?
If time is wrong, place is as well.
I developed symptoms on 28 February, 2020.
The damned "pandemic" was over by May 1st, 2020, and I was recovered from even the malaise on 13 March 2020, so Gov. Gary Herbert Hoover and State Epidemiologist Angela Dunce locked everything down so I couldn't get novels other than SARS-Divok-2 from the library.
Sure glad I got cataract surgery in early January, 2020.
You make your case very well with your logic and numbers.
Think about this as well. The modelers cited by the Seattle Times said that as many as 10 to 20 million Americans may have contracted this virus by May 1st. But these modelers were working from the baseline ASSUMPTION that the first likely cases of "community spread" in America date back to only February 1st (or "latter January.")
How would these models and estimates change if these epidemiologists and statisticians accepted that "community spread" was actually occurring in early November 2019? That is, the spread commenced three months earlier than they thought.
If they accept that A happened (spread actually began three months earlier), they'd have to dramatically revise their models and estimates. So those estimates of 10 to 20 million infected people by May 1st would have to be be tripled or quadrupled ... or increased by even five or six-fold IMO.
An email friend who is a great student of Covid issues is skeptical of my large numbers. When I pressed him about the flaw in my “logic,” he said the R0 (infection numbers) must be wrong. I don’t mind others challenging my hypothesis as this is what should happen in science or journalism.
However, as I wrote in this email reply, I’m sticking to my guns on this piece.
In my reply I noted that one doesn’t need antibody studies to support the view that R numbers are at least 1.5. Here's my email reply to my skeptical friend:
“I don't think RO is wrong though. I can provide evidence of this from my other articles where I've identified 24 other Americans who had antibody evidence of early spread (and infections that date to before 2020). Many of these people not only became sick, they infected others in their close contacts, who also tested positive.
For example, in the DelRay Beach group of 11 people from one neighborhood who became sick in November and December 2019, this includes three married couples (and one child of these people). All of these people infected at least one other person. It would seem odd if they infected ONLY spouses. The R number in these cases is at least 3 - the unknown person who infected the first married person and then both couples in the marriage. In one case, both husband, wife and one of their children tested positive for antibodies - making that R number at least 4.
Tim and Brandie McCain both became sick at the same time - so one infected the other and we don't know the unknown person who infected the first McCain. Furthermore, the McCains’ roommate at the time became as sick as Tim (he never got an antibody test). Both of their children developed "mild cases" (although they later tested negative for antibodies .... but this fits my hypothesis that those with mild cases aren't as likely to later test positive for antibodies).
Still with the McCains, I'd say we have an RO of at least 4. 1) The first (unknown) person who infected the McCains; 2-3: Both McCains; 4) Their roommate. I won't count the children who had mild cases but it is an interesting coincidence they also developed symptoms. Brandie and other people in Sylacauga, Alabama report that it seems like "half" the town was sick from some virus at the time the McCains got sick.
I think I probably qualify as an example. I became very sick in early January (and had all the Covid symptoms). I think I got the virus from my daughter, who had symptoms one day before I did. She must have gotten sick in school, where about 10 of her classmates were also sick, plus her teacher, plus the teacher's three children. My son later got sick as well. My children had "mild" symptoms. I think we probably had Covid and, like Sylacauga (which is two hours to the north), it seems like half of Troy, Alabama was sick with something at the same time 3 of our 4 family members became sick.
Mayor Michael Melham of Belleville, NJ was sick on or around November 20, 2019. He has said that "many" people at the same conference he attended were also sick. He said many of these people later contacted him by email, supporting his claim and stating they also think they had the same virus at the same time.
So the RO number from the Melham case study would be at least 2 - the unknown person who infected Mayor Melham and Mayor Melham himself. If even a couple of those other sick people also had Covid, this would mean the RO number was 3, 4, 5 or 6? Also, when I mention these unknown virus transmitters we also know from logic that some unknown carrier infected the first unknown carrier/spreader. So you could really add one R factor to these examples.
About 100 people contacted me saying they thought they had Covid. From this group of emails, I added at least 7 other "antibody-positive" early cases. Again, two or three of these cases were among spouses - one infected the other, plus we don't know the unknown person who infected the first member of the marriage.
We’ve both written about the French study where officials DID interview 11 people who later tested positive. 8 of these 11 individuals were either sick themselves in November or December or a close contact was (confirmed by the follow-up interviews). This is also proof that the infected weren't the only people getting infected.
What would be your estimate of how many Americans were sick by January 1st, 2020? Do you think these people who were sick transmitted the virus to others and who transmitted the virus to them?
Anyway, one can use micro case studies to support an R number of at least 1.5. You don't necessarily need antibody studies to prove or reject this theory. Individual case studies tell us what was happening. This is why officials didn't go back and interview those infected people or do "contact tracing" of all their close contacts.
The Red Cross study is important in that it tested blood that had been donated in mid-December 2019 and then early to mid-January 2020. One could assume there was not a long time-lag between the date the antibody test was administered and when these people had experienced an active infection. That is, detectable levels of antibodies had not had as much time to “fade” or “wane.”
Per my hypothesis, one reason there might have been greater “prevalence” (2.03 percent) in the Dec. 13-16 tranche of archived blood is that the antibodies had not had as much time to “fade” as the blood collected in mid-January in the other states. For example, if a donor gave blood January 17 and had a mild case of Covid in mid-November, this infection might not be as likely to be detected by blood drawn two months after this person had symptoms (or even no symptoms).
And/or: Virus prevalence was just lower in these states.
Another important (and I would say conclusive) finding from my study of antibody studies is that people who experienced mild or asymptomatic cases are much less likely to produce antibodies that last (or can be detected) many or even several months later.
In previous articles, I identified at least 24 Americans who tested positive for antibodies four or five months after experiencing symptoms. Almost all of these individuals had severe cases. For example, they had to go to the doctor several times (some were hospitalized) and/or they were bedridden for an extended period of time. None had what could be described as “mild” or “asymptomatic” cases.
This supports the findings of the studies I’ve read. People with mild cases aren’t as likely to later test positive for antibodies. As perhaps most people who have been infected by the novel coronavirus have mild or asymptomatic cases, it follows that this cohort is not as likely to have tested positive for antibodies weeks or months after these mild or asymptomatic cases.
Continuing with limitations or extra discussion regarding the Red Cross blood study ...
Furthermore, as I have either already written or will detail in future articles, the antibody results we do have are almost certainly producing a deflated (or low) number of likely “early cases.”
For example, the Red Cross study - while a pretty good random sample of Americans - is limited by the fact that the vast majority of blood donor are much older than the median age of 38.6. The median age of blood donors was, I believe, 52. Older Americans, including many retirees, do not interact with nearly as many people as younger students or working age citizens. This would mean the cohort most represented in the Red Cross blood sample would have been less likely to contract the novel coronavirus because they didn't come in contact with as many people as younger citizens do.