I recognize that public awareness is crucial in order to form a reforming movement, which I think is the only available way to achieve a positive change. Thus, besides making this paper heavily referenced I will simplify each section and organize it in a way that makes the reader a thinker.
1.1 Scientific Literature
There were so many essential characteristics known about COVID19 since before it was declared a health emergency. So, what are these known features?
COVID19 is believed to be a new disease caused by a novel strain of known common cold viruses, the Coronaviruses. New strains of Flu and common cold viruses and other types of viruses are regularly studied and tracked by different health organizations including WHO and the CDC to assess the need for intervention without any special attention from the media for a valid reason; there is no scientific or rational reason to be worried.
“Although the majority of infections with the four endemic CoVs only cause mild respiratory diseases, all HCoVs can also induce severe illnesses. This particularly affects risk groups such as immunosuppressed patients, patients with previous pulmonary disease and infants, but rarely also patients without a specific risk profile”
“In addition to the typical clinical picture of an ARE, the endemic CoV can in rare cases also cause serious diseases of the lower respiratory tract such as pneumonia or bronchitis. This is more common in people with pre-existing cardiopulmonary or malignancies, immunosuppression, infants, and older adults”.
From the above, we get that SARS-CoV-2 is a virus that belongs to a family that has the following characters:
- There are 6 of them that infect humans.
- Four of them are widely circulated and cause what we call the common cold.
- all of them can induce severe illnesses, and particularly affects risk groups such as immunosuppressed patients.
- Two from this family (SARS & MERS) are believed to more severe and lethal.
So far, what we saw in the early three months of the declared outbreak of COVID19 share all of the above characteristics except being as severe as SARS and MERS.
So, what is the situation here? Why are we so worried about this specific strain of coronaviruses but not the others? Is there scientific evidence that causes this concern? Why did our government declare it a health emergency that needs a war scale response?
The official argument is that SARS-CoV-2 differs from the four harmless members of its family in its lethality which exceeds what we normally tolerate in every flu season whether a mild one or a severe one which contributes to thousands of deaths.
What was the scientific evidence that our government relied on for their risk assessment? Was their assessment scientifically valid? Has any new evidence emerged that reaffirm their risk assessment or refute it?
1.2. The Mortality Rate
The lethality of any disease is measured in medical science by what is known to the public as the mortality rate or the death rate. Again, what was the death rate that the government used to assess the severity of this virus?
The answer is none. Instead, they relied on, scientifically, criticized models.
But then what is the death rate for COVID19?
As I noted above, the death rate is a term known to the public. This term is understood to show the number of deaths among the people who got infected with the virus. It is important to understand that this term is not professional and that it can be confused with two distinguished epidemiological terms. Therefore, it is necessary to understand the scientific terms first before moving to another point.
1.2.1 IFR Vs. CFR
In epidemiology, there are different terms used that pertains to the death rate:
- Case Fatality Rate (CFR): is the number of deaths caused by the disease divided by the number of people who have tested positive for the disease. Usually, the people who seek the tests have the symptoms of the diseases or sick enough to go to a hospital. The CFR in some diseases, especially, highly infectious diseases, does NOT reflect the true lethality of the disease.
|Case Fatality Rate||Number of deaths|
|Number of who tested positive|
- Infection Fatality Rate (IFR): is the number of deaths caused by the disease divided by the number of all infected people whether they sought the test or not. The IFR always reflects the reality of the severity of the disease. The denominator of the IFR is usually bigger than the denominator of the CFR. The difference pertains to the infectivity of the virus and the samples of the test.
”Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%”.
“If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism”
|Infection Fatality Rate (IFR)||Number of deaths|
|Number of all infected people|
We now learned that in order to assess the risk of SARS-CoV-2, which is very infectious and a lot of the infected have no symptoms, we need to look at the IFR instead of the CFR.
1.2.2. COVID19 Mortality Rate (IFR)
Unfortunately, our government, media, and public health officials ignored talking about the Infection Fatality Rate and focused on the Case Fatality Rate knowing that it excludes asymptomatic people and the people who have not had the test that are the majority in our very case, you might want to ask why?
But, fortunately, scientists from around the world conducted studies with regards to COVID19 mortality. Yes, the majority of them are ignored and have not reached the public. It is beneficial to compare the COVID19 IFR to the seasonal flu IFR to better understand its severity. We know that the seasonal flu has an IFR of 0.1% in mild seasons and about 0.2%-0.5% in strong seasons. So, what is the COVID19 IFR? Is it different than the flu IFR?
The answer is, surprisingly, NO. Here is a list of more than 35 studies conducted worldwide:
- Wuhan, China. Published on Feb 12, 2020. (0.04%-0.12%).
- Guilan province, Iran. Published on May 1st, 2020. Rate (0.08%-0.12%)
- Heinsberg Cluster, Germany. May 5, 2020. Rate (Adj 0.27%)
- Santa Clara, CA, USA. Apr 30, 2020. Rate (0.17%)
- Denmark. Apr 28, 2020. Rate (0.08%).
- Dade County, Miami, USA. Apr 24, 2020. Rate (<0.18%).
- LA County, CA, USA. Apr 21, 2020. Rate (<0.2%)
- Global (23 studies). June 8, 2020. Rate (median 0.04%-0.25%)
- MLB employees, USA. May 10, 2020. Rate (0.00%).
- Aircraft carrier, France. May 10, 2020. Rate (0.00%).
- Aircraft carrier, USA. May 10, 2020. Rate (0.09%).
- Tennessee prison, USA. May 1st, 2020. Rate (0.00%)
- Health workers, Italy. Apr, 28, 2020. Rate (0.3%)
- Boston shelter, USA. Apr 17, 2020. Rate (0.00%)
- Repatriations, Greece. Apr 17, 2020. Rate (0.00%)
- NYC pregnant women, USA. Apr 13, 2020. Rate (0.00%)
- Diamond prince, USA. Mar 17, 2020. Rate (adj 0.125%).
- Global. May 5, 2020. Rate (0.17%).
- Global. Updated, Jun 15, 2020. Rate (0.00%-0.1%)
- CDC, Updated. Rate (avg 0.26%)
1.2.3. Other studies:
The following studies show the high prevalence of COVID19 infections, indicating a much lower IFR. It is worth noting that an immunological study of antibodies suggested that the prevalence of the serological studies should be multiplied by up to x4 which leads to even lower Infection Fatality Rate (IFR).
|1. Russia||June 10||14%||40x|
|2. Boston, USA||May 15||12.5%||8x|
|3. Czech Rep.||May 15||5%||10x|
|4. Indiana, USA||May 13||2.8%||11x|
|5. Madrid, Spain||May 13||5%11.3%||10x|
|6. UK||May 8||29%||200x|
|7. Geneva, Switzerland||May 6||9.7%||10x|
|8. Global||May 5|
|9. Kobe City, Japan||May 5||2.7%||396x|
|10. New York, USA||May 2||12.3%19.9%||8x10x|
|11. Spain||May 2||11.2%|
|12. Blood donors, Netherlands||April 29||2.7%9.5%|
|13. Northern, France||April 23||3%|
|14. Chelsea, MA, USA||April 19||32%||16x|
|15. Iceland||April 14||0.8%|
Conclusion: The overall Infection Fatality Rate (IFR) is similar to the burden of flu and flu-like diseases.
- I have not included models’ conclusions for their foundational dependence on presumptive premises. For instance, the Imperial College of London model assumed that there would be no herd immunity until reaching 70%-80% which is four times more than the actual herd immunity of coronaviruses. Also, their model is based on an age-related IFR (0.66%) of an early Chinese study that assumed the CFR instead of having clear data to extract the IFR and dismissed the majority of the asymptomatic infections.
- The death numbers are problematic in a number of countries including the US for their liberal approach of recording ‘death with COVID’ as ‘death from COVID’, as stated by Dr.Birx of the White House task force, CDC and others, which results in attributing deaths that were not caused by COVID to COVID. Some argued against the result of this approach but provided no evidence.
Now, why the government, media, and governmental health officials are still dismissing the above facts? Why they do not talk about the Infection Fatality Rate (IFR) when all of the studies talked about it? why are we still in a state of emergency after having the redundancy of scientific studies that concluded that the severity of COVID is way less than first assumed and falls within the range of flu seasons?
Those questions are not being answered with science, but with politics and propaganda.
Statistics can reflect scientific facts if done properly. Often, they can be tweaked toward a desired result by controlling the surveyed sample. Nevertheless, some samples cannot be twisted such as all causes of death numbers. Therefore, it is very significant to look at these numbers in the case of COVID to see if there are abnormal deaths numbers or not. Here we are going to look at different graphs and analyze them.
1.3.1 All Causes of Death (US.)
The chart shows the deaths of COVID and all causes of deaths in the US in 2020
The charts above show us that every winter the number of deaths from all causes increases. An abnormal death increase was seen late in the season which does not fit the pattern of the winter burden of the previous years for the following:
– It came late in the season.
– It was a sharp increase for a short period of time (3-4 weeks).
– The increase happened immediately after the lockdown.
– The death number was decreasing before the sudden increase after the lockdown.
– The total number of deaths is comparable to the previous years but a 5% increase is noticed this year.
As we have seen in section 1.2 above, the lethality of COVID19 is similar to or lower than the flu. Nevertheless, a sharp increase in all causes of deaths was noticed. The sharp increase and decrease of all causes of deaths do not match the declared burden of the spread of COVID19 because we now know, from different studies and reports, that the virus was circulating the globe since as early as last November but no abnormal death patterns were seen.
Furthermore, a comparison between all causes of deaths in different states shows that this abnormal increase resulted from only a few cities despite the comparable spread of COVID19 in others. It is also very clear that other western countries have the same abnormality and refer to the same findings.
The 5% sharp increase in all causes of death in the US is not due to the spread of COVID19.
(several plausible factors for this increase are present in the current discussion including fear, isolation, lockdowns and the use of ventilators).
 “Our early estimates suggest that the CFR of COVID-19 is lower than the previous coronavirus epidemics caused by SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV)” Early estimation of the case fatality rate of COVID-19 in mainland China.
 “CDC estimates that the burden of illness during the 2017–2018 season was also high with an estimated 48.8 million people getting sick with influenza, 22.7 million people going to a health care provider, 959,000 hospitalizations, and 79,400 deaths from influenza.” https://www.cdc.gov/flu/about/burden/2017-2018/archive.htm#:~:text=CDC%20estimates%20that%20the%20burden,from%20influenza%20(Table%201).
 “We also found that most recent crude infection fatality ratio (IFR) and time-delay adjusted IFR is estimated to be 0.04% (95% CrI: 0.03-0.06%) and 0.12% (95%CrI: 0.08-0.17%), which is several orders of magnitude smaller than the crude CFR estimated at 4.19%” https://www.medrxiv.org/content/10.1101/2020.02.12.20022434v2.
 “This number corresponds to an infection fatality rate between 0.08-0.12% that is much lower than currently reported estimates of case fatality rate for COVID-19” https://www.medrxiv.org/content/10.1101/2020.04.26.20079244v1.full.pdf+html.
 Accordingly, the corrected higher infection rate reduced the IFR to an estimated 0.278% [0.228%; 0.351%] (Fig. 3C). https://www.medrxiv.org/content/10.1101/2020.05.04.20090076v2.full.pdf+html.
 “If our estimates of 54,000 infections represent the cumulative total on April 1, and we assume a 3 week lag from time of infection to death, up to April 2224, then 94 deaths out of 54,000 infections correspond to an infection fatality rate of 0.17% in Santa Clara County” https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v2.full.pdf+html
 “Using available data on fatalities and population numbers a combined IFR in patients younger than 70 is estimated at 82 per 100,000 (CI: 59-154) infections” https://www.medrxiv.org/content/10.1101/2020.04.24.20075291v1.
“ “The estimates also suggest that we might have to recalibrate disease prediction models and rethink public health strategies.” https://pressroom.usc.edu/preliminary-results-of-usc-la-county-covid-19-study-released/.
 “Infection fatality rates ranged from 0.02% to 0.86% (median 0.26%) and corrected values ranged from 0.02% to 0.78% (median 0.25%). Among people <70 years old, infection fatality rates ranged from 0.00% to 0.26% with median of 0.05% (corrected, 0.00-0.23% with median of 0.04%).” https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v2.
 “Our results suggest that the ascertainment rate of SARS-CoV-2 infection might be much lower than previously assumed, with a correspondingly lower infection fatality rate.4 At the same time, the extent of asymptomatic transmission is likely to make mitigation challenging without wide-ranging social distancing measures” https://academic.oup.com/jtm/article/27/3/taaa054/5820895.
 “Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/.
 “We also estimate that the median global initial reproduction number R0 is 3.3 (C.I (1.5, 8.3)) and the total infection fatality rate near the onset is 0.17% (C.I. (0.05%, 0.9%)).” https://www.medrxiv.org/content/10.1101/2020.04.29.20083485v1.
 This a huge collected Data, average around 0.1%. https://docs.google.com/spreadsheets/d/17Tf1Ln9VuE5ovpnhLRBJH-33L5KRaiB3NhvaiF3hWC0/edit#gid=0.
 The findings of this study are significant. https://onlinelibrary.wiley.com/doi/10.1111/ijcp.13528.
 The study compares the risk to driving cars per mileage. https://www.medrxiv.org/content/10.1101/2020.04.05.20054361v2.
“ The cumulative prevalence of SARS-CoV-2 infection was 11.2% (65/578, 95% CI: 8.9-14.1)” https://www.medrxiv.org/content/10.1101/2020.04.27.20082289v1.
 The discussion in the study seem to confuse the herd immunity concept of other disease with the herd immunity of the coronaviruses family that could be reached by 10%-20% prevalence. https://www.researchsquare.com/article/rs-25862/v1.
 The Chinese study used the data provided by the Imperial Collage itself among two others. Neil Ferguson who is the leading scientist at the IC also co-authored the Chinese study. The Imperial Collage receives funds from Bill Gates.
 “In cases where a definite diagnosis of COVID–19 cannot be made, but it is suspected or likely (e.g., the circumstances are compelling within a reasonable degree of certainty), it is acceptable to report COVID–19 on a death certificate as “probable” or “presumed.” In these instances, certifiers should use their best clinical judgement in determining if a COVID–19 infection was likely.” https://www.cdc.gov/nchs/data/nvss/vsrg/vsrg03-508.pdf
 Here is one example of anecdotal answers “ Experts say that COVID-19 deaths are likely not being overinflated”, for no evidence was provided, and the contrary is true. https://www.usatoday.com/story/news/factcheck/2020/04/17/fact-check-covid-19-death-toll-likely-undercounted-not-overcounted/2973481001/.