If an intelligent being visited Earth from another planet/dimension, and looked only at the messages from our public health officials, governments, mainstream/legacy media, the masks everyone is wearing, the constant reminders of social distancing and social bubbles, and the censoring, ridicule, smear campaigns, “cancelling”, and darn near societal banishment of those who challenge any of the pandemic public health mandates (never mind those who choose not to get vaccinated), they would think there is an extinction level event type virus circulating around the Earth.
Or maybe, just maybe, a being with the ability of interplanetary/dimensional travel would possess that which is currently absent (or at least hiding) on much of planet Earth, critical thinking.
I may have already ruined the punchline of this article, but what follows is a review of the scientific evidence showing that the level of fear messaging and the COVID-19 public health measures do not match the real level of risk SARS-CoV-2 presents to us. In fact, it may be no more of a threat than seasonal influenza.
COVID-19 Risk Evaluation
Mortality
Early in the pandemic, based on data from China, it was thought that asymptomatic infections were rare, meaning that the case fatality rate (CFR) would be approximately the same as the infection fatality rate (IFR). As such, this early data put the case/infection fatality rate at 3.4% (1). Eventually, asymptomatic infection was discovered to occur more frequently than initially thought and the widely accepted IFR was determined to be approximately 0.9 – 1% (2). An IFR of 1%, in addition to an estimate that around 81% of the world’s population would be infected, led to the prediction that over 2 million deaths would occur in the United States and upwards of 50 million deaths worldwide (3, 4). Numbers such as these would have been comparable to the 1918 influenza pandemic. Although these are the models that governments worldwide based initial lockdown measures on, it is fortunate that these initial estimates were not accurate.
Such grave estimates were based on a modeling study by Imperial College and became the basis for the spread of COVID-19 fear messaging to the public from governments and media outlets worldwide. Such messaging was permitted even though the lead author of the study had previously made grossly inaccurate estimates about the mortality impact of the Bird Flu, Swine Flu, and Mad Cow Disease (5). As ongoing data and evidence emerged, the mortality and morbidity risk associated with COVID-19, for much of the population, was much less than originally thought and does not appear to warrant the degree of fear messaging that has continued throughout this pandemic.
While initial COVID-19 IFR estimates were as high as 3.4%, current evidence places the IFR somewhere between 0.15% and 0.09%, well within the IFR range of seasonal influenza (6, 7, 8, 9). While this is the IFR at a population level, we know that, as with many infectious diseases, the elderly are at a much greater risk of mortality from COVID-19 and the risk of mortality from COVID-19 differs by age group. Stratified by age group the IFRs are estimated to be: 0-19 years = 0.0027%, 20-29 years = 0.014%, 30-39 years = 0.031%, 40-49 years = 0.082%, 50-59 years = 0.27%, and 60-69 years = 0.59% (10). Additionally, for the elderly in community dwellings, the IFR is estimated to be 2.4% while the elderly in non-community dwellings is 5.5% (11). The elderly are classified as those above age 69 and IFR increases significantly in elderly groups containing a higher percentage of those over 85 years. Additionally, as with the rest of the population, other health factors such as obesity increase the mortality risk in the elderly demographic (12). To put these numbers into comparative context, even the common cold can have an IFR of up to 10% in care homes (13).
Another way to examine the mortality risk presented by COVID-19 is to look at age of death data. For instance, 76% of deaths to date in the United States have been in individuals over the age of 65 and 83% of deaths to date in Canada have been over the age of 70 (14, 15). Additionally, the average age of death from COVID-19 is approximately 75 years in the United States, only 3 years below the country’s average life expectancy (16). Approximately 81% of individuals who died of COVID-19 in Canada were residents of long-term care homes or senior homes (17). The United Kingdom has reported a median age of death of 83 years and a mean age of death of 80 years, while the country lists an average life expectancy between 79 and 83 years (18). The data are clear, age is the main risk factor when it comes to COVID-19 mortality, yet public health measures and fear messaging to the public do not match the data.
The above mortality numbers are generally calculated using widely accepted mortality data from the mentioned countries. However, there has been criticism regarding how these numbers are gathered, suggesting there has been an overestimation of the total deaths caused by COVID-19. Before RT-PCR testing was widely used, COVID-19 diagnosis did not require laboratory confirmation; the United States Center for Disease Control and Prevention (CDC) changed physician instructions for completing death certificates for COVID-19 only, downplaying the role of comorbid diagnosis; and RT-PCR reliability and accuracy has been consistently criticized regarding cycle threshold (19, 20, 21, 22, 23, 24). Based on the available evidence in 2020, a court in Portugal ruled that RT-PCR COVID-19 testing has up to a 97% false-positive rate above a cycle threshold of 35 and is not a suitable test for COVID-19 diagnosis (25). The available literature supports that RT-PCR tests lack suitability for accurate COVID-19 diagnosis 26 27 28 29 30 31. The (CDC) has also advised they will be removing emergency use authorization for RT-PCR as a diagnostic test for COVID-19 as of January 1, 2022 and laboratories must transition to FDA-approved tests (32).
Furthermore, court documents from Portugal indicate that it is possible that as of May 19, 2021, only 0.9% of officially tracked COVID-19 deaths were caused solely by COVID-19 (33). Additionally, the CDC states that only 5% of officially tracked COVID-19 deaths were solely caused by SARS-CoV-2 without any contributing factors such as comorbidities (34). Italy lists similar data with only 2.9% of COVID-19 deaths not having contributing comorbidities (35).
All these factors imply an overestimation of mortality numbers. Some research implies that the impact of these factors not only supports an IFR in the range of seasonal influenza but also a total death toll in the range of seasonal influenza (36).
Finally, regarding mortality risk, a recent systemic review and meta-analysis concluded that vitamin D levels of 30 ng/mL significantly reduce COVID-19 mortality, and levels of 50 ng/ml can theoretically reduce COVID-19 mortality to zero (37). This study suggests that even without pharmaceutical treatment, a reduction of IFR to statistically zero could be achieved simply through vitamin D3 supplementation.
Morbidity
In determining the risk presented by SARS-CoV-2, we must also look at morbidity along with mortality. Based on the available literature, it is difficult to estimate the infection hospitalization rate (IHR) with similar accuracy to the IFR. In the early stages of the pandemic, it was suggested that 10% of identified cases would need hospitalization (38). However, there is a difference between the case hospitalization rate and IHR, as we have already determined with mortality numbers. Based on studies performing RT-PCR tests on groups of people using multiple different selection criteria, the IHR lands somewhere between 0.09% and 15% (39, 40, 41). However, based on study designs, these numbers can not truly be viewed as IHR but rather some unknown combination of IHR and case hospitalization rate. The CDC currently estimates the total number of infections (including asymptomatic unconfirmed infection) in the United States to be 120,259,370 and the confirmed number of hospitalizations to be 6,156,065 equaling an IHR of 5.12% (42).
Nevertheless, there is concern regarding the accuracy of hospitalization numbers. COVID-19 screening is a common practice in healthcare facilities during the pandemic (43). Such practices involve COVID-19 testing upon admission to a healthcare facility for any reason. Understandably, such screening may identify possibly infectious individuals and limit facility outbreaks; however, it also identifies mild to moderate, and asymptomatic cases that would not require hospitalization for COVID-19 symptoms. Thus, it is suggested that official hospitalization numbers are overestimated. It’s estimated that before widespread vaccination, 36% of hospitalizations were for mild or asymptomatic infections and since widespread vaccination began, 48% of hospitalizations were for mild or asymptomatic infections (44). This data indicates that between 36% and 48% of COVID-19 hospitalizations were not hospitalized for COVID-19 symptoms and were likely counted as COVID-19 hospitalizations based on COVID-19 screening practices while being admitted for other reasons. This disparity is even greater for COVID-19 hospitalizations in pediatric populations. Multiple studies reveal that only 7.7% to 14% of COVID-19 pediatric hospitalizations had significant symptoms (45, 46, 47). This data indicates that for between 92.3% and 86% of documented pediatric hospitalizations, the patients were admitted for something other than COVID-19 symptoms and the hospitalizations were only officially tracked because of healthcare facility screening practices. Given these findings, and the RT-PCR false positive rate previously noted, the IHR of 0.09-15% noted above should be significantly reduced, possibly by more than half.
So-called “Long COVID-19” is also frequently noted as a consideration regarding COVID-19 morbidity risk. However, a recent study using a control group and 26,823 participants found that the belief of previously having COVID-19 was associated with having all persistent symptoms of Long COVID-19 but serological confirmation and physician diagnosis of actually having COVID-19 was only associated with one Long COVID-19 symptom, anosmia (loss of smell) (48). Symptoms associated with Long COVID-19 are quite common in the general population and it is difficult to determine causation from previous COVID-19 infection. By using a control group, this paper highlights that these symptoms may not be related to actual COVID-19 infection and therefore, Long COVID-19 is significantly less of a concern than originally thought. This does not mean Long COVID-19 doesn’t exist, it just suggests it’s not as common as we have been told.
Comorbidities
It is also well known that comorbidities significantly increase the risk of morbidity and mortality posed by COVID-19. The above-outlined data showing that the risk from COVID-19 is comparable to seasonal influenza does not consider the full contribution of comorbid conditions. It is well documented that, next to age, comorbid conditions are the highest risk factor for poor COVID-19 outcomes. The CDC states that at least 2.9 comorbidities are present in those listed as COVID-19 deaths and 94% of COVID-19 coded deaths have additional causes listed on the death certificate (49). A recent peer-reviewed study out of the United Kingdom, with a sample size of 6.9 million people, indicates that for those under the age of 60 years, obesity alone accounts for up to 74% of the risk of hospitalization, 85% of the risk of intensive care unit (ICU) admission, and 90% of the risk of death (50). In addition to obesity, other comorbidities that increase the risk of poor COVID-19 outcomes include diabetes, cardiovascular disease, chronic obstructive pulmonary disease, and cancer (51). Therefore, in addition to COVID-19 risk being comparable to seasonal influenza, those that do have poor outcomes from COVID-19 are highly likely to be immunocompromised due to obesity, comorbidities, increased age, or a combination of all three.
The information presented above is not meant to dismiss any risk that SARS-CoV-2 presents. However, our public health responses and messaging to the public must match the actual risk determined by high-quality data and quickly adapt as new information is gathered. At this time the level of fear messaging to the public and the severity of public health measures, do not appear to match the true level of risk presented by SARS-CoV-2.