*The following article is a combination of two sections of a larger project I’m currently working on affectionately titled “The Anti-Vaxxers Handbook”. I’m hoping to be done the first version of it in the coming months but for now here is a preview of some of its content, hope you enjoy!*
In March of 2020 while COVID was spreading globally the W.H.O estimated the fatality rate of the novel virus was around 3.4%.1 This may seem like a low percentage but if the world was to experience the projected infection rates of the Imperial College’s Report 9 of 70-80% that translates in a global population of almost 8-billion to nearly 218-million deaths worldwide. As of this writing (Jun/11/22) 6,330,641 deaths2 have been attributed to COVID globally. A tragic number nonetheless but a number that represents a mere 2.9% of the projected 218-million figure.
How could COVID end up being 97.1% less deadly than originally projected? There’s a number of reasons including better treatment methods for COVID patients, the virus mutating into less deadly versions of itself, vaccine uptake and the epidemiological concept of infection rate. When COVID first hit testing availability was sparse and people were likely not to be tested for the virus unless they displayed severe symptoms. A lot of people likely contracted the virus without even knowing it or had a mild enough case that they never sought out treatment and therefore were never tested.
When the World Health Organization released their estimated fatality percentage in 2020 they used the number of confirmed cases as the denominator and the number of deaths as the numerator to crunch out the 3.4% figure. However as mentioned at the time, testing was sparse and a large number of cases went undocumented, the opposite is true for deaths. The net of the medical data system catches a large majority of deaths and as discussed later at times that “death tracking” net was cast too liberally. This created an over-inflated number as the numerator being divided by an under-represented denominator which produced an over-projection of COVID-19’s body-count.
When interviewed in March of 2020 President Trump hinted at the fact that he believed the W.H.O’s projection was over-inflated.
"Well, I think the 3.4 percent is really a false number. Now, and this is just my hunch, and — but based on a lot of conversations with a lot of people that do this. Because a lot people will have this and it's very mild. They'll get better very rapidly. They don't even see a doctor. They don't even call a doctor,"
Trump unknowingly was fleshing out the concept of infection rate VS case rate.
New York City experienced an extreme epidemiological wave of COVID early in the pandemic. As a result, based off of anti-body tests 21.2% or just over one-fifth of New-Yorkers now presented anti-bodies for COVID-19 indicating they had experienced infection.3 Extrapolated to an absolute number that 21.2% represents an estimated 1.7-million New Yorkers experiencing infection by the end of April 2020. A CDC study published later that year cited approximately 203,000 laboratory-confirmed COVID-19 cases were reported in NYC.4 That leaves a gap of 1,497,000 between confirmed cases and the projected true infection rate, even accounting for an over-estimation in the anti-body study due to the relatively small sample size and false positives a considerable gap would still exist.
Using the 203,000 laboratory confirmed cases in NYC as the denominator the CDC study put the “crude fatality rate” at 9.2% overall. Using the projected true infection rate garnered by the anti-body study as the denominator the fatality rate would be around 1% or 9-times less deadly. Keeping in mind that the results of the anti-body test were published by the end of April 2020 whereas the data the CDC is using spans from February to June 1st. Meaning the death figure of 18,676 extrapolated from the CDC study and used as the numerator for both equations represents at least an additional month of recorded deaths after the 1.7-million infected number was presented. This means even 1% may represent an over-projection.
Separate anti-body tests conducted in other parts of the country yielded similar results as the NYC one. A study conducted in Miami-Dade County found about 6% of participants experienced infection equating to a projected 165,000 cases whereas at the time only 10,000 cases had been confirmed in that same county, resulting in a 16.5 times gap between the recorded case counts and actual infection rate.5 Similarly in Santa Clara County they found an estimated 50 to 85 fold gap between projected infection rates and confirmed case counts.6
Part of the reason these gaps were so wide was because of availability of testing. These studies were conducted towards the beginning of the pandemic when as mentioned testing was sparse, regardless availability of testing has never quite closed that gap between recorded case counts and projected infection rates. Two years later in March of 2022 the Chief Medical Officer of Ontario Canada, Dr. Kieran Moore estimated that about ten times more Ontarians had likely experienced COVID-19 infection than what was shown in the case counts.7
In conclusion using Dr. Moore’s conservative estimate of the true infection rate of COVID being ten times more than what’s recorded in PCR counts the W.H.O’s original figure of a 3.4% fatality rate ends up being a 0.34% fatality rate. In absolute numbers that means the projected 218-million deaths globally extrapolated using that 3.4% number would be more like an estimated 21.8-million deaths. In reality that is even an over-shot since there have been 6,330,641 deaths attributed to COVID world-wide. That’s about 30% of the ten times infection rate estimate of 21.8-million. Using the actual recorded death number of 6,330,641 and the ten times infection rate, COVID’s actual fatality rate comes out as 0.102% a long way from the fifth horseman it was portrayed to be.
As already discussed the fatality rate of COVID was effected by the discrepancy in the recorded case counts and the true infection rate of the virus. Anti-body testing found that the actual infection rate of COVID was multiple times higher than what was recorded in the confirmed numbers. However when fatality rates were presented to the public the denominator used in the deaths over cases calculation was the recorded number of cases and not an estimation of actual infections. This meant that unreported cases were left out of the equation, resulting in a majority of mild cases to not be included in the fatality rate calculation. This caused a smaller denominator which meant a higher fatality rate since the recorded deaths were being divided by a smaller value.
Conversely the numerator of the fatality rate equation, the recorded deaths may have been falsely inflated. Just as the case count number was misrepresented in the sense that it didn’t include an estimation of unrecorded cases the number of deaths was misrepresented in the sense that it included deaths that weren’t the result of COVID.
In April of 2020 when COVID was running rampant in NYC assumed deaths from the novel virus were added to the states and consequently the countries fatality count.
“New York City, already a world epicenter of the coronavirus outbreak, sharply increased its death toll by more than 3,700 victims on Tuesday, after officials said they were now including people who had never tested positive for the virus but were presumed to have died of it. The new figures, released by the city’s Health Department, drove up the number of people killed in New York City to more than 10,000, and appeared to increase the overall United States death count by 17 percent to more than 26,000.”8
New York was not the only state who adopted this practice of including assumed deaths. The cited article above from The New York Times goes on to say other states such as “Connecticut, Ohio and Delaware, are beginning to disclose cases where infection is presumed but not confirmed.” Meaning the polar opposite of what happened with case counts was now happening with deaths. Only confirmed cases were included in the denominator (cases) but assumed infections were added to the numerator (deaths).
On death certificates certain codes are included that indicate the cause of death, these are called ICD codes. COVID-19’s ICD code was U07.1 and a memo by the National Vital Statistics System which is part of the CDC (Center for Disease Control) was issued that answered some FAQ’s regarding the reporting of COVID deaths. One of the questions included in the memo was “Should “COVID-19” be reported on the death certificate only with a confirmed test?”9 In response the memo stated that:
“COVID-19 should be reported on the death certificate for all decedents where the disease caused or is assumed to have caused or contributed to death”
The same memo states that if terms such as “probable COVID-19” or “likely COVID-19” are used they would be assigned the new ICD code. Therefore if physicians or whichever medical professional was responsible for reporting the death indicated that it could have possibly been due to COVID but was not confirmed it would have still been captured in the U07.1 net.
Outside of the medical system reporting deaths directly another way of measuring mortality is available. This is the method of tracking something known as excess deaths. In essence a given population whether that be of a state, city or country has an average amount of deaths over a given time frame. Something like a pandemic would cause an abnormal spike since it would add to the average number of a given populations normal death rate. This abnormal spike above the average recorded fatality rate is what’s known as excess deaths.
In Canada between March and the start of June 2020 there was a recorded 7,500 excess deaths which aligned closely with the 8,345 deaths caused by COVID recorded in the same time-frame. Shortly after June excess deaths seemed to disappear and by July death counts looked the same as though there had been no pandemic and no excess mortality was observed through to the end of September.10
Now because documenting excess death is an aggregate method, the lack of them can partially be explained by less deaths occurring in that time frame due to less traffic accidents or work related fatality since most of the country was locked down. Nonetheless even with accounting for those if COVID was a serious threat to mortality excess death should have still been observed.
An alternate theory is that at the beginning of the pandemic unfortunately the most vulnerable succumbed to the disease causing a spike in death rates that fizzled out while in the same time frame new data and methods of treatment became available subsequently leading to health care staff becoming more successful at mitigating fatalities due to an increase in the quality of care for COVID-19 patients.
Outside of assumed COVID deaths being added to the numerator of the fatality rate equation and countries showing lack of excess death during the spread of SARS-COV-2 was the extreme skewing in mortality as a function of age.
It did become and was common knowledge that the elderly population was more susceptible to COVID-19, by just how much was never really emphasized. If the general public knew how much less likely they would be to die of COVID simply because they were under the age of 50 it is likely the population would have swayed towards more age specific public health measures instead of large draconian all-encompassing lockdowns.
By 2022 the CDC found that about 81% of COVID deaths were in people over 65 and that someone in the age demographic of 18-29 years was 97 times less likely to die of COVID than somebody above 65.11 Even in the first year of the pandemic after COVID had ripped through the East coast and the state of Washington the median age of the deceased was 75yrs old and in the other 13 jurisdictions that made up the study the median age of decedents was 78yrs old.12 Statistics Canada drew similar conclusions in their tracking and found that “..individuals age 85 and older account for over half of excess deaths” Other than the radical skewing of death as a function of age the CDC discovered that 94% of SARS-COV-2 deaths had at least one underlying health condition.13
Now this isn’t to say that the elderly are less valuable and should have just accepted the role of society’s sacrificial lamb. The extreme skew of mortality as a function of age should have influenced more targeted public health measures. Public health measures that would have specifically protected the elderly while leaving the remainder of society relatively untouched since the under 65 demographics posed little threat to causing large mortality rates or hospital overflow.
One country did recognize this extreme skew in age vs mortality rates and severity of COVID-19 infection, that country was Sweden. Sweden’s response was very aloof compared to that of other European and North American nations. They likely properly interpreted the data and realized the most vulnerable were the elderly so they decided to leave the general population alone and not instate over-reaching lockdowns.
As a result Sweden was chastised in the media, with its citizens being accused of having “…gone along with policies leading to large-scale death.”14 According to one journalist who returned to Sweden in 2020 to be with their parents they documented such horrors as “Cafes full to the brim, people picnicking in parks, on the same blanket.” ON THE SAME BLANKET!!! MY GOD!!! SAVE US!!! *Drops to knees and reaches palms out the sky*
Nonetheless just as the denominator of the deaths over cases fatality rate calculation was skewed so was the numerator. Assumed deaths from COVID-19 and deaths that were the result of other underlying health conditions were included in COVID-19’s overall body count resulting in a larger number. Inside that number was also the radical skewing of fatality by age demographic as shown by the CDC data over 80% of fatalities were in people over 65 years old. Meaning the general public not included in that age demographic were at much less risk of developing a severe or a fatal case of COVID. Therefore lockdown policies and or public health measures that targeted the elderly and vulnerable should have been implemented instead of broad stroke lockdown policies.
Footnotes:
Quint Forgey, “Trump Floats His Own Coronavirus Hunches on ‘Hannity,’ ” Politico, March 5, 2020, https://www.politico.com/news/2020/03/05/trump-disputes-coronavirus-death-rate-121892
"Coronavirus Death Toll", Worldometer, June 11 2022, https://www.worldometers.info/coronavirus/coronavirus-death-toll/
Caroline Lewis, “21 Percent of NYC Residents Tested in State Study Have Antibodies from COVID-19,” Gothamist, April 23, 2020, https://gothamist.com/news/new-york-antibody-test-results-coronavirus
"COVID-19 Outbreak - New York City, February 29 - June 1, 2020", CDC, November 20 2020, https://www.cdc.gov/mmwr/volumes/69/wr/mm6946a2.htm
“Second Round of COVID-19 Community Testing Completed; Miami-Dade County and the University of Miami Miller School of Medicine Announce Initial Findings,” Miami-Dade County, April 24, 2020, https://www.miamidade.gov/releases/2020-04-24-sample-testing-results.asp
Eran Bendavid et al., “COVID-19 Antibody Seroprevalence in Santa Clara County, California,” MedRxiv, April 17, 2020, https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
Lucas Casaletto, "Ontario to lift mask mandate by end of March despite risk of spread due to BA.2 subvariant: Moore", CityNews, March 3 2022, https://ottawa.citynews.ca/local-news/ontario-to-lift-mask-mandate-by-end-of-march-despite-risk-of-spread-due-to-ba2-subvariant-moore-5123420?fbclid=IwAR0fdyXb8COKRnfHY_FPjxnuzzqa0lborojcj_NvipVt0bsEtxo3eShQ3FA
J. David Goodman and William K. Rashbaum, “N.Y.C. Death Toll Soars Past 10,000 in Revised Virus Count,” New York Times, April 14, 2020, https://www.nytimes.com/2020/04/14/nyregion/new-york-coronavirus-deaths.html
“COVID-19 Alert No. 2: New ICD Code Introduced for COVID-19 Deaths,” National Vital Statistics System, Centers for Disease Control, March 24, 2020, https://www.cdc.gov/nchs/data/nvss/coronavirus/Alert-2-New-ICD-code-introduced-for-COVID-19-deaths.pdf
“Provisional Death Counts and Excess Mortality, January to September 2020,” Statistics Canada, November 26, 2020, https://www150.statcan.gc.ca/n1/daily-quotidien/201126/dq201126c-eng.htm
“Underlying Medical Conditions Associated with High Risk for Severe COVID-19: Information for Healthcare Providers,” Centers for Disease Control, May 13, 2021, https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-care/underlyingconditions.html#ref_3
“Characteristics of Persons Who Died with COVID-19—United States, February 12–May 18, 2020,” Centers for Disease Control, July 17, 2020, https://www.cdc.gov/mmwr/volumes/69/wr/mm6928e1.htm
Cole Lauterbach, “Maricopa County Clarifies How Officials Classify a ‘COVID-Attributed’ Death,” The Center Square, September 2, 2020, https://www.thecentersquare.com/arizona/maricopa-county-clarifies-how-officials-classify-a-covid-attributed-death/article_8269def2-ed63-11ea-872c-d7fbb82999a4.html
Erik Augustin Palm, “I Just Came Home to Sweden. I’m Horrified by the Coronavirus Response Here,” Slate, April 29, 2020, https://slate.com/news-and-politics/2020/04/sweden-coronavirus-response-death-social-distancing.html