Trust the Science: Lockdowns Are a Mistake

Americans cannot turn on the television these days without hearing the words “trust the science.” It’s on every channel and seeping from the mouths of nearly every politician and media pundit in the country. They tell America that there is a scientific “consensus” backing every part of their worldview, from coronavirus lockdowns and climate change, to gun control and even the Black Lives Matter riots.

The biggest issue many Americans have with the endless platitudes of these mainstream politicians and pundits is not one of politics but of the verifiably false declaration that “science” is on the same side as all their popular banalities.

On Coronavirus Lockdowns

The same pundits who claim to be proponents of the working and middle classes and who claim to want higher wages for American workers are also simultaneously ridiculing President Trump for telling Americans not to be fearful of the coronavirus. They are constantly reminding us that over 200,000 Americans have died from the virus, and that we shouldn’t even think about opening up the country until a vaccine has been widely distributed to the population. They say we need stricter shutdown measures, not more lenient policies regarding the coronavirus.

But is it saving lives they genuinely care about, or something else? What does the science actually say?

According to official CDC data, 231,000 Americans thus far have died from COVID-19, but how many already have and soon will die from the effects of the shutdown?

When the shutdowns in America began to exceed the 15-day timeline officials promised, many scientific researchers warned of other adverse consequences as unemployment began to rise dramatically. Researchers pointed to scientific meta-analysis suggesting that for every 1 percent of unemployment in the country, approximately 5,300 to 10,000 people would die from deaths of despair. These studies were largely ignored as the United States quickly surpassed the 20 percent unemployment mark as the lockdowns far surpassed the 15-day promised timeline.

Because these warnings were ignored by a small minority of agenda-driven scientists, we are seeing an exponential rise in deaths stemming from increased suicide, drug overdose, DUIs, alcohol consumption, tuberculosis infections, spousal abuse, and delayed cancer screenings.

Hospitals desperate to clear beds for the promised “surge” of COVID patients canceled virtually all screening procedures, including vital tests and operations, when the shutdowns began.

Scientists in the United Kingdom suggest there could be tens of thousands of extra deaths because of these delays.

Scientists examined data from eight hospital trusts and shared their findings.

The study, conducted by DATA-CAN, the Health Care Research Hub (HDR UK) for Cancer, found that there could be 35,000 additional cancer deaths within a year in the UK alone from the lockdown.

In the United States, overwhelming scientific evidence has found that COVID-19 lockdowns have shortened the lifespans of Americans far more than the virus itself.

According to the study, the coronavirus lockdowns are ten times more deadly to America than the actual COVID-19 virus itself, and have devastated long term financial and social stability.

Drawing on existing economic studies on the health effects of unemployment, the Revolver study sought to quantify the net damage of the lockdowns in terms of a metric known as “life-years” and compared that number to how many lives will have been saved by the lockdowns.

We found that an estimated 18.7 million life-years will be lost in the United States due to the COVID-19 lockdowns. Comparative data analysis between nations shows that the lockdowns in the United States likely had a minimal effect in saving life-years.

Almost 7,000 scientists, virologists, and infectious disease experts recently signed a declaration against lockdown measures, urging that citizens across the west should be able to get on with their lives as normal, and that lockdown rules in both the United States and the UK are causing “irreparable damage.”

Oxford University professor Dr. Sunetra Gupta was one of the authors of the open letter that was sent with the petition, along with Harvard University’s Dr. Martin Kulldorff and Stanford’s Dr. Jay Bhattacharya.

The declaration corresponds with other research that concludes lockdowns will “destroy at least seven times more years of human life” than they save.

Other studies find that debilitating stress and anxiety caused by the lockdown, including despair caused by job loss, could lead to a myriad of negative health issues that will take a far greater overall toll on human life than the number of lives saved by the shutdown.

Based on a broad array of scientific data, the anxiety created by reactions to Covid-19—such as stay-at-home orders, business shutdowns, media exaggerations, and legitimate concerns about the virus—will destroy at least seven times more years of human life than can possibly be saved by lockdowns to control the spread of the disease. This figure is a bare minimum, and the actual one is likely more than 90 times greater.

Scientific research has found that at least 16.8 percent of adults in the United States have suffered catastrophic mental harm.

Figures show that “anxiety from responses to Covid-19 has affected 42 million adults and will rob them of an average of 1.3 years of life, thus destroying 55.7 million years of life.”

This data compares with just “616,590 lives which ‘might’ be saved by the current lockdowns, which means that the current lockdowns can save no more than 7.4 million years of life.”

Gerd Muller, Germany’s minister of economic cooperation and development, has warned that the lockdown measures throughout the globe will end up killing more people than the coronavirus itself.

In an interview with a German newspaper, Muller warned that the response to the global pandemic has resulted in “one of the biggest” hunger and poverty crises in history.

A leaked study from the German Ministry of Interior revealed that the impact of the lockdown could end up killing more people than the coronavirus itself due to deaths of despair and victims of other serious illnesses suffering a delay in their treatment.

In the United States, scientific researchers have estimated that 1.5 million people could die from the effects of the continued American lockdowns.

How Deadly Is the Virus Really?

Researchers have established that the effects of worldwide lockdowns will be far more deadly than the virus itself, but how deadly is the virus really?

According to the United States’ Center for Disease Control (CDC), the updated age-group survival rates for COVID-19 happen to be: Ages 0-19 (99.997 percent); 20-49 (99.98 percent); 50-69 (99.5 percent); and 70+ (94.6 percent). The mortality rates are only slightly higher than the human toll from seasonal flu and, in fact, are lower than they are for many other ailments for the same age cohorts.

Table 3 of the CDC’s data on deaths between February 2 and August 22, shows that only 6 percent of the 161,392 reported COVID deaths were listed as COVID-19 alone. All other U.S. deaths had on average, 2.6 additional medical conditions including influenza and cardiac arrest. Other conditions included sepsis, diabetes, renal failure, and Alzheimer’s disease.

Are they including all of the normal yearly influenza deaths in the COVID-19 death totals?

During the beginning of the year, nearly all major media outlets reported that the world was in store for possibly the worst flu season on record. On January 3, CNN reported that the United States was “on track for the worst flu season in decades.”

During the same month, Time covered Fauci’s appearance on CNN where he stated that “the current flu season is on track to be one of the worst in years.”

While Fauci was warning about one of the deadliest flu seasons in decades, the rest of the media were telling Americans not to worry about Coronavirus, and that the flu would be far more deadly this year. The Los Angeles Times advised not to fear the Coronavirus, because ”for Americans the flu is a much bigger threat and more widespread.” In early February, USA Today wrote that “the coronavirus is scary, but the flu is deadlier and more widespread.” During the same time, the Washington Post declared “Get a Grippe America, the Flu is a Much Bigger Threat Than Coronavirus.”

This was of course back when most of the media were still referring to the virus as the “Chinese virus,” up until President Trump decided to use the term. Then everyone from the New York City health commissioner to House Speaker Nancy Pelosi (D-Calif.) made trips into Chinatown to roll in the Chinese new year, and rebuke Trump’s “xenophobic” description of the virus.

But how did the United States go from the start of the “worst flu season in decades,” to influenza cases and deaths nosediving by 98 percent across the globe?

The explanation that cases of influenza nosedived simply because much of the world’s population are now donning masks, while at the same time cases of the coronavirus surge, is completely inconsistent and a nonsensical conclusion, to say the least.

This is especially true when you consider the fact that all the best scientific analyses show that masks are ineffective at preventing the spread of influenza, or any other respiratory illness.

The Actual Science Behind the Masks

The randomized clinical trial (RCT) is recognized as the most credible research design for clinical investigation. The goal of the RCT is to achieve valid comparison of the effects of an investigational treatment or treatments with the control treatment (standard of care) in the target patient population. Bias can be reduced by concealing the randomization sequence from the investigators at the time of obtaining consent from potential trial participants. Allocation concealment is a very simple maneuver that can be incorporated in the design of any trial and that can always be implemented.

This means that the only way to remove bias from scientific research in the medical field is with randomized clinical trials. Contrary to popular belief, every single RCT ever performed on mask usage and prevention of infection for laboratory-confirmed influenza, the common cold, or other respiratory viruses shows that masks are ineffective.

There is a sum total of zero randomized clinical trials showing that masks prevent any of the aforementioned illnesses. As you read through the following trial summaries and their conclusions, recall the damage we have already knowingly inflicted upon the population, and the health risks of the shutdowns that we have already consciously accepted in our quest to “trust the science.”

Jacobs, J. L. et al. (2009) “Use of surgical face masks to reduce the incidence of the common cold among health care workers in Japan: A randomized controlled trial,” American Journal of Infection Control, Volume 37, Issue 5, 417–419.

N95-masked health-care workers (HCW) were significantly more likely to experience headaches. Face mask use in HCW was not demonstrated to provide benefit in terms of cold symptoms or getting colds.

Radonovich, L.J. et al. (2019) “N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel: A Randomized Clinical Trial,” JAMA. 2019; 322(9): 824–833.

“Among 2862 randomized participants, 2371 completed the study and accounted for 5180 HCW-seasons. … Among outpatient health care personnel, N95 respirators vs medical masks as worn by participants in this trial resulted in no significant difference in the incidence of laboratory-confirmed influenza.

Long, Y. et al. (2020) “Effectiveness of N95 respirators versus surgical masks against influenza: A systematic review and meta-analysis,” J Evid Based Med. 2020; 1–9.  

“A total of six RCTs involving 9,171 participants were included. There were no statistically significant differences in preventing laboratory-confirmed influenza, laboratory-confirmed respiratory viral infections, laboratory-confirmed respiratory infection, and influenza-like illness using N95 respirators and surgical masks. Meta-analysis indicated a protective effect of N95 respirators against laboratory-confirmed bacterial colonization (RR = 0.58, 95% CI 0.43-0.78). The use of N95 respirators compared with surgical masks is not associated with a lower risk of laboratory-confirmed influenza.”

Cowling, B. et al. (2010) “Face masks to prevent transmission of influenza virus: A systematic review,” Epidemiology and Infection, 138(4), 449-456.

None of the studies reviewed showed a benefit from wearing a mask, in either HCW or community members in households (H). See summary Tables 1 and 2 therein.

Bin-Reza et al. (2012) “The use of masks and respirators to prevent transmission of influenza: a systematic review of the scientific evidence,” Influenza and Other Respiratory Viruses 6(4), 257–267.

There were 17 eligible studies. … None of the studies established a conclusive relationship between mask/respirator use and protection against influenza infection.”

Smith, J.D. et al. (2016) “Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis,” CMAJ Mar 2016

“We identified six clinical studies … . In the meta-analysis of the clinical studies, we found no significant difference between N95 respirators and surgical masks in associated risk of (a) laboratory-confirmed respiratory infection, (b) influenza-like illness, or (c) reported work-place absenteeism.”

Offeddu, V. et al. (2017) “Effectiveness of Masks and Respirators Against Respiratory Infections in Healthcare Workers: A Systematic Review and Meta-Analysis,” Clinical Infectious Diseases, Volume 65, Issue 11, 1 December 2017, pages 1934–1942,

“Self-reported assessment of clinical outcomes was prone to bias. Evidence of a protective effect of masks or respirators against verified respiratory infection (VRI) was not statistically significant.

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