COVID-19: Lockdowns are Unscientific

8 min readNov 27, 2020

Canada, and more specifically the government of Ontario, has implemented non-evidence-based draconian lockdown measures that are not proportionate to the apparent danger presented by COVID-19. In this article I will present research from several authors, look at the data surrounding the impact of COVID-19 and take a look at the consequences of a forced lockdown. We’ll also explore the opinions of doctors and other professionals from around the world to see what they have to say about this situation.

Death Counts are Overestimated

COVID-19 death counts are overestimated. The demographics and conditions surrounding the deaths of individuals strongly suggest that many are dying from already existing serious underlying medical conditions and the appearance of a positive COVID-19 test is coincidental and trivial in the cause of their death. In some extreme cases, this leads to incidents such as that from Macomb County in Michigan, where an individual had died by suicide and a postmortem COVID-19 test was administered, which came back positive, and the death was marked as a COVID-19 death — despite the fact that COVID-19 clearly was not the cause of death.¹ Italy’s minister of health has been quoted saying “only 12 per cent of death certificates have shown a direct causality from coronavirus.”⁴ A United Kingdom government website displays the COVID-19 death count as “deaths of people who had had a positive test result for COVID-19 and died within 28 days of the first positive test” with no other investigation or criteria stated — a number that is misleadingly displayed by various other news outlets and websites.⁷ This same low standard of determining supposed COVID-19 deaths is used here in Ontario as well. A spokesperson from Ottawa Public Health has mentioned that the mortality data surrounding COVID-19 deaths “does not indicate if COVID-19 was the cause of death, and we can’t make that inference.”² Toronto’s associate medical officer of health, Dr. Vinita Dubey, has stated that “this means that individuals who have died with COVID-19, but not necessarily as a result of COVID-19, are all included in the case counts for COVID-19 deaths in Toronto.”² According to data from the New York State Department of Health, over 90% of deaths have at least 1 comorbidity, and the majority of deaths are from those aged 70 and up.³ Another study conducted by Italy’s national health authority has found that over 99% of Italy’s COVID-19 deaths included people who suffered from previous medical conditions.⁵ Another study conducted by several doctors in Italy investigated the characteristics of patients who died of COIVID-19. Based on their findings, they state that “case-fatality statistics in Italy are based on defining COVID-19–related deaths as those occurring in patients who test positive for SARS-CoV-2 via RT-PCR, independently from preexisting diseases that may have caused death.” Pre-existing conditions are never taken into account when making these determinations, despite the fact that patients had an average of 2.7 pre-existing conditions (almost half of all deaths included patients with at least 3 underlying conditions), and no clear criteria is available for determining real COVID-19 deaths. The authors further state that “electing to define death from COVID-19 in this way may have resulted in an overestimation of the case-fatality rate.”⁶

In many countries, the average age of COVID-19 victims is greater than the average life expectancy, while in others, it’s very close to the average life expectancy. In Scotland, for example, data from the National Records of Scotland (NRS) reveals the average age of COVID-19 victims to be 79 for males and 84 for females. However, the average life expectancy of males is 77, while for females it is 81, according to the same data from the NRS.⁸ In Canada, 96.7% of deaths include those over 60, with 70.9% being over 80 years old.⁹ The average age of COVID-19 victims is between 75.6 and 85.3 years of age, with Canada’s life expectancy at 82.4.¹⁰ ¹¹

A group of researchers from Stanford published a study investigating COVID-19, specifically its mortality risk for non-elderly individuals. They found that individuals under 65 years of age accounted for 4.5–11.2% of all COVID-19 deaths in Europe and Canada. They compare the risk of death from COVID to the risk of death from driving a car, specifically stating that “the COVID-19 mortality rate in people <65 years old during the period of fatalities from the epidemic was equivalent to the mortality rate from driving between 4 and 82 miles per day.”²⁴ They conclude their discussion by stating that “the vast majority of the population may be reassured that their risks are very low.” Based on their findings, they also state the following in their discussion:

“Long-term lockdowns may have major adverse consequences for health (suicides, domestic violence, worsening mental health, cardiovascular disease, loss of health insurance from unemployment, and famine, to name a few) and also creating new major issues for society at large. Lockdowns originally aimed to save the health care system, but as patients avoid coming to the hospitals for common, treatable problems, deaths may rise from non-treatment; also hospitals face an emerging crisis also leading to their demise. It is even argued that lockdowns may be even harmful as a response to COVID-19 itself, if they broaden rather than flatten the epidemic curve. Information from seroprevalence and universal screening studies suggest that the frequency of infections is much larger than the documented cases and thus the overall infection fatality rate is likely to be much lower than previously thought. It seems that the majority of infections are either asymptomatic or mildly symptomatic and thus do not come to medical attention. These data also suggest that the infection fatality rate may be close to that of a severe influenza season (<0.2%) when the health system does not collapse and when massive nosocomial infections and nursing home spread are averted.”

Testing is not Effective

If an individual tests positive for COVID-19, that does not necessarily indicate they are infectious — in fact, it does not necessarily indicate that they are positive for COVID-19, either. A group of scientists from Tongji Medical College conducted a study in which false-positive tests were suspected in their study of 70 COVID-19 patients, stating that they “found that 15 (21.4%) patients experienced a ‘turn positive’ of nucleic acid detection by RT‐PCR test for SARS‐CoV‐2 after two consecutive negative results.”¹² Another group of researchers from China conducted a study of 610 hospitalized COVID-19 cases. They reported “a potentially high false negative rate of real‐time reverse‐transcriptase polymerase chain reaction (RT‐PCR) testing for SARS‐CoV‐2” along with finding that “RT‐PCR results from several tests at different points were variable from the same patients during the course of diagnosis and treatment.” Furthermore, the researchers also found that at least 18 patients tested positive for COVID-19 after receiving 2 consecutive negative results.¹³ This research lines up with results from individuals who are tested multiple times, the most famous one being that from Elon Musk:

Nevertheless, in the case of a positive COVID-19 result, you may not necessarily be infectious. A French COVID-19 study found that PCR tests with a cycle threshold (Ct) of 25 correlated to 70% of patients remaining positive in culture. At Ct = 30, the value dropped to only 20%. At Ct = 35, less than 3% of cultures were positive (i.e. the probability of culturing the virus, or the chance of it being replication competent, declines to less than 3%).¹⁴ In Ontario, the Ct value cutoff used for a positive result is between 38 and 45.¹⁵ A study conducted by several Italian researchers states that high cycle thresholds (between 34 and 39) indicate a very low residual viral load that is not able to infect cultured cells.¹⁶ Furthermore, because of the mounting evidence against the reliability of PCR testing, the Portuguese Court of Appeals has recently deemed PCR tests unreliable.¹⁷ We can only hope that Ontario follows suit, taking into consideration the evidence that sheds light on the true effectiveness of these tests .

Another point to consider is the effect of asymptomatic or pre-symptomatic individuals. A recent study published in The Lancet, which is among the world’s oldest and best-known general medical journals, investigates viral load dynamics and duration.¹⁸ The researchers found that “although modelling studies estimated potential viral load peak before symptom onset — we did not identify any study that confirms pre-symptomatic viral load peak.” Suggesting that pre-symptomatic patients are much less infectious during that time. The study continues by stating “the highest viral loads were reported soon after or at the time of symptom onset, or at day 3–5 of illness, followed by a consistent decline.” Another study by Chinese researchers confirms that “virus cultures were negative for all asymptomatic positive and repositive cases, indicating no ‘viable virus’ in positive cases detected in this study.”¹⁹

Lockdowns are Unscientific

Anti-lockdown sentiment is growing among medical experts and professionals, and for good reason. A French study of 160 countries found no association between the stringency of government lockdowns and restrictions and COVID-19 mortality.²⁰ This sentiment is even encouraged by the World Health Organization. Dr David Nabarro, the WHO’s Special Envoy on COVID-19, has stated “we in the World Health Organization do not advocate lockdowns as the primary means of control of this virus.”²¹ Among those that are calling for the end of lockdowns include Dr. Martin Kulldorff, professor of medicine at Harvard University, Dr. Lisa White, professor of modelling and epidemiology, Dr. Salmaan Keshavjee, professor of Global Health and Social Medicine at Harvard Medical School, and many more.²² Dr Kulldorff has stated that “it is lockdowns that now present the greatest threat to population health.”²³

COVID-19 case counts are not a reliable indicator for determining the severity of this disease, and it certainly is not enough to justify the lockdown measures put in place. These case counts, along with the supposed death counts, are based upon shaky methodology and without enough supporting evidence to justify a lockdown.

We need a better approach to handling the COVID-19 situation. One that does not involve marginalizing people, taking innocent lives, shutting down small businesses, causing mental health issues, spreading fear, or ruining people’s livelihoods (visit https://collateralglobal.org to see a complete list of studies documenting the collateral effects of lockdown). Lockdowns are anti-scientific, anti-public health, and anti-democratic. The evidence does not support a mass lockdown as a sustainable and responsible solution to this problem. We need to end the non-evidence-based draconian lockdown measures that are not proportionate to the apparent danger presented by COVID-19.

COVID-19: Lockdowns are Unscientific

Written by Attila Komaromi