Thursday, July 30, 2020

UN: Lockdowns, School Closures Results In More Deaths Than CV In Children

UN Officials Cite Study That Finds Lockdowns, School Closures Killing More Kids Than COVID

UN officials have pointed to a study that reveals lockdowns and school closures are doing more harm to children than the coronavirus itself, with many more deaths expected to come from the reaction to the outbreak, rather than the pandemic itself.

In a presentation seeking extra funding for coronavirus efforts, UNICEF director Henrietta H Fore said Monday, “The repercussions of the pandemic are causing more harm to children than the disease itself.”

UNICEF nutrition program chief Victor Aguayo noted that the most harm is being done “by having schools closed, by having primary health care services disrupted, by having nutritional programs dysfunctional.”
The officials pointed to a study published in The Lancet that notes “physical distancing, school closures, trade restrictions, and country lockdowns” are worsening global child malnutrition.
The study estimates that an extra 6.7 million children will be at risk, and that lockdowns and other coronavirus responses could lead to more than 10,000 additional child deaths every month.
The UNICEF officials noted that would mean 128,000 more deaths among children within the next year.

The study complies research from the Washington-based International Food Policy Research Institute (IFPRI) and the Johns Hopkins Bloomberg School of Public Health.
It concludes that shut down strategies could lead to “life-long impacts on education, chronic disease risks, and overall human capital formation,” in addition to “intergenerational consequences for child growth and development.”
The estimates are said to “likely to be conservative, given that the duration of this crisis is unknown, and its full impacts on food, health, and social protection systems are yet to be realized.”
The study dovetails with other research that has concluded lockdowns will conservatively “destroy at least seven times more years of human life” than they save.
The German government has concluded that the impact of the country’s lockdown could end up killing more people than the coronavirus due to victims of other serious illnesses not receiving treatment.
As we have previously highlighted, in the UK there have already been up to 10,000 excess deaths as a result of seriously ill people avoiding hospitals due to COVID-19 or not having their hospital treatments cancelled.
A data analyst consortium in South Africa also found that the economic consequences of the country’s lockdown will lead to 29 times more people dying than the coronavirus itself.
Hundreds of doctors are also on record as opposing lockdown measures, warning that they will cause more death than the coronavirus itself.
While globalists have urged that lockdowns need to continue, medical and economic experts across the board in multiple countries are warning that the loss of life will be much greater than that caused directly by the virus itself, if lockdowns are not scrapped.

Fraud (from 14th century Latin) n – deceit, trickery, intentional perversion of truth in order to induce another to part with something of value or to surrender legal rights: and art of deceiving or misrepresenting; imposter, cheat, one who is not who that person pretends to be: something that is not what it appears to be

When lockdown was imposed, we were told we were facing a second Spanish flu pandemic (thought to have killed up to 50 million people); that hospitals would be overrun and there would be 500,000 deaths in the UK alone. This was a powerful and emotive narrative, but it was never true. Governments and an obedient media focused exclusively on Imperial College’s now discredited doomsday scenario built on a hypothetical, badly coded model5, ignoring its author’s history of failed doomsday predictions and the different views of other scientists.
Alternative evidence-based (i.e. theories based on facts) population samples already existed: the most prominent being the Diamond Princess Cruise Ship; which at the end of February accounted for over half of all confirmed infections outside of China. “Cruise ships are like an ideal experiment of a closed population”, according to Stamford Professor of Medicine John Ioannidis. “You know exactly who is there and at risk and you can measure everyone” .
Quarantined for over a month after a virus outbreak, the entire cruise ship ‘closed population’ of 3,711 passengers and crew, with an average age of 58,  were repeatedly tested. There were 705 cases (19% total infection rate) and six deaths (a Case Fatality Rate of just 1%) by the end of March (eventually 14 in total). This compared to 116 deaths that would have been predicted by the Imperial model).

Over half of the cruise ship cases were asymptomatic, at a time when the official “science” behind the lockdown, Prof. Neil Ferguson (UK), dismissed the lack of any evidence for a high proportion of cases so mild that they had no symptoms and Dr Anthony Fauci (US) had written in the New England Journal of Medicine that in the event of a high proportion of asymptomatic cases, the COVID mortality rate would ultimately be “akin to a severe seasonal influenza” (a statement which he now at least seems to have clearly forgotten in his enthusiasm for a vaccine solution).
The cruise ship deaths were exclusively amongst an over 70’s age cohort. Although the Diamond Princess sample size was small it remains the earliest and most accurate predictor of mortality, infection and asymptomatic cases. Extrapolating this data to the wider, younger population would logically lead to downward revision on the mortality risk and upwards revisions to the level of asymptomatic cases. COVID outbreaks aboard naval ships with younger populations confirmed this: only 1 death and 3 hospitalised cases out of 1,156 infections on the USS Theodore Roosevelt; zero deaths out of 1,046 confirmed cases on the Charles de Gaulle. Even in ships which could not carry out effective social distancing the virus mortality rate, whilst a serious public health risk, was certainly not the “Spanish flu”.
As more testing was carried out across population samples (and not just on the patients hospitalised) studies came to the same conclusion: the rate of infection was higher than thought with more harmless cases and therefore the ultimate mortality risk was much lower than originally claimed.  Despite this empirical evidence and the contrarian opinions of other expert epidemiologists which have since proven to be much more accurate, the Imperial College virus narrative of “the worst pandemic in 100 years”(Fig. 1) did not change: governments, the media and the official “science” doubled down on the “dialogue of doom”. Ferguson then broke his own lockdown in a tryst with his married lover and justified it by claiming he had antibody immunity (which given what we now know about decaying antibodies may not have been correct).
Fig 1. COVID-19 mortality in perspective

The population mortality risk of the virus was initially estimated at 3.8% by the WHO which had arrived at this number simply by dividing the number of Chinese deaths by the number of confirmed cases, ignoring the fact that only a small proportion of likely infected people had actually been tested; that asymptomatic cases were likely to be significantly underrepresented in testing and that the more serious cases were likely highly correlated to serious symptoms. This basic statistical error of simply dividing deaths by reported infections not only exaggerated the severity of the risk but led directly to policy error on hospital capacity and care home deaths.

Media reporting also intentionally failed to acknowledge that mortality risk was highly skewed to age (median mortality age of 8229) in order to scare the entire population into observing lockdown with falsely exaggerated media reports of young and healthy people dying from the virus. Mortality risk amongst the elderly was skewed to those with existing health issues (the presence of comorbidities) with Italy reporting that 96% of virus fatalities also suffered from other illnesses, but this did not fit the desired narrative. Whereas the Spanish flu in 1918 had disproportionately killed the young and  healthy – meaning that each death lost more years before predicted average mortality – COVID deaths on average occurred at or beyond average life expectancy, which was always consistent with a normal mortality risk curve, and seasonal non-pandemic coronavirus.

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