January 31, 2021 | source
“A deadly combination of exponentially increased suicides, drug overdose, homicide, alcohol consumption, calorie consumption, delayed cancer screenings, spousal abuse, tuberculosis, and more is occurring. Researchers conclude this combination will outweigh deaths from COVID by multiples.
Data show very clearly that lockdowns have not only been completely ineffective, but they have been potentially as much as ten times more deadly than the coronavirus itself.
According to the UN there are 10,000 additional children dying a month during the lockdowns, and 550,000 additional children suffering malnutrition. There will also be 1.4 million additional people to die from untreated TB.
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.
How Deadly is the Virus?
Researchers have established that the effects of the worldwide lockdown will be far more deadly than the virus itself, but how deadly is the virus really?
According to all available data, the virus itself has an infection fatality rate that is either equivalent to, or far less than the influenza for most age groups.
The Infection Fatality Rate (IFR) is the total number of deaths divided by the total number of people that carry the infection, regardless of them having clinical symptoms or not. The IFR is the chance of death once you have the virus.
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?
Misclassification of COVID Fatalities?
A peer-reviewed study contends the Centers for Disease Control violated federal law by inflating Coronavirus fatality numbers exponentially.
The fatality figures were inflated by at least 1,600%, according to the study, titled “COVID-19 Data Collection, Comorbidity & Federal Law: A Historical Retrospective.”
The study noted that on March 24, the CDC published an alert instructing medical examiners, coroners and physicians to deemphasize underlying causes of death, also known as pre-existing conditions or comorbidities.
Many coroners have come forward to express their concern on how official are recording their covid deaths.
The Grand County, Colorado coroner is recently called attention to the way the state health department is classifying some deaths.
The coroner, Brenda Bock, says two of their five deaths related to COVID-19 were people who died of gunshot wounds.
“these two people had tested positive for COVID but that’s not what killed them,” she said. “The gunshot wound killed them.”
Bock said it’s simple in this case – the gunshot wound was the cause of death.
“I realize yes, you’re trying to keep count of the numbers, but you need to do it right, and these people did not die of COVID, they died of gunshot wounds and that’s how it needs to be listed,” she said.
The study also concludes that the CDC “illegally enacted new rules that violated federal law, which resulted in a 1,600% inflation of current COVID-19 fatality totals.”
Under the new rules, COVID-19 was to be listed in Part I of death certificates as a definitive cause of death, regardless of confirmatory evidence, rather than in Part II as a contributor to death in the presence of pre-existing conditions.
On its website, the CDC says, just 6% of the people counted as COVID-19 deaths died of COVID-19 alone.
The following are the top underlying medical conditions linked with COVID-19 deaths:
- Influenza and pneumonia
- Respiratory failure
- Hypertensive disease
- Vascular and unspecified dementia
- Cardiac Arrest
- Heart failure
- Renal failure
- Intentional and unintentional injury, poisoning and other adverse events
- Other medical conditions
The researchers estimated the COVID-19 recorded fatalities “are inflated nationwide by as much as 1600% above what they would be had the CDC used the 2003 handbooks,” said All Concerned Citizens in a statement on the study.
The ‘Worst Flu Season in Decades’
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 on Dr Fauci’s warning that the United States was “on track for the worst flu season in decades.”
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.”
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.
The 2017-2018 flu season was so bad, hospitals were treating patients in tents. No lockdown was ever considered at all, despite tens of thousands of deaths.
The 2017-2018 epidemic was sending people to hospitals and urgent-care centers in every state, and medical centers were responding with extraordinary measures: asking staff to work overtime, set up triage tents, restricting friends and family visits, and canceling elective surgeries.
“We are pretty much at capacity, and the volume is certainly different from previous flu seasons,” said Dr. Alfred Tallia, professor and chair of family medicine in New Brunswick, New Jersey at the time.
Why Are Lockdowns Still Ongoing?
They told us that lockdowns would only last two weeks, just to give hospitals time to manage capacity. It has now been almost a year.
Looking at what the science actually says, the only conclusion that makes sense is because mega corporations, monopolies, and Wall Street billionaires financially benefit to the tune of trillions of dollars. And it it those groups who have always funded the media, and decided which experts get to speak, what they can say, and which people set the standards.
The greatest wealth transfer in the history of America has occurred because of this.
Billionaires make appearances on corporate media telling people to be extremely afraid, and that we must shut down, because they benefit from the lockdown which cuts out their competition and helps them further monopolize.
The same people then make appearances on the same corporate media outlets they used to push for lockdowns, to short brick and mortar stores even further into the ground; by telling people those stocks are going to tank.
Hundreds of virologists, infectious disease experts, scientists, economists, and doctors who have talked about this—pushing back against the mainstream narrative— have been shut out of the conversation by big tech, big media, and mega corporations.
This is simply because their narrative—which is the scientifically correct one—interferes with the historic financial gain of Wall Street and mega corporations we’ve observed.
Many people acknowledge our healthcare system is corrupt—only out to make money at our expense—yet those same people continue to buy into all of what our healthcare and corporate system tells them about COVID.
If you say that you value science, and are against the corporate elite, but yet still disregard the scientific consensus, listening to what the TV people tell you; you are the foolish one, and are helping to spread the wealth gap between the top 1% and the rest of America.
Do Masks Work?
The science is also settled on this, and has been for a very long time. The vast majority of scientific studies done on the efficacy of masks in preventing the spread of respiratory viruses, show they do absolutely nothing to prevent the spread of respiratory viruses.
Covid-19 infections commonly occur via aerosolized particles not just droplets. Masks and air filters can remove very small particles, such as bacteria and viruses but a single coronavirus particle size ranges from 70–90 nm. This is one hundred times smaller than a tenth of a micron.
The renowned UK science journal, The Lancet published paper concluding that “Small aerosol particles smaller than 5 μm in aerodynamic size are most likely to remain” following filtering of the air.
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.”