Australian Citizens Party formerly Citizens Electoral Council

COVID-19 exposes flawed modelling

The failure to comprehend the garbage-in, garbage-out (GIGO) principle in COVID-19 modelling will cost many thousands of lives. Policymakers have relied on computer models from presumed scientific experts, but flawed assumptions have underpinned several such models. Real-world data from China and Italy, among other nations, should have initiated a radically different response, but the “experts” stuck to their models until reality intervened with pleas from doctors facing exponential increases in COVID-19 cases.

“I can’t help but feel angry that it has taken almost two months for politicians and even ‘experts’ to understand the scale of the danger from SARS-CoV-2”, said Richard Horton, editor-in-chief of esteemed British medical journal The Lancet, in a 17 March tweet. “Those dangers were clear from the very beginning.” Horton elaborated in a followup tweet: “Chinese clinicians and scientists—Chen Wang, George Gao, Chen Zhu, Bin Cao—did the world a great service by immediately sharing their data, warning the world that SARS-CoV-2 was a dangerous new virus. I’m appalled to say that western ‘experts’ failed to heed their warnings.”

Herd immunity

The United Kingdom’s reliance on flawed modelling led to the “herd immunity” policy which encouraged the spread of COVID-19 among younger people. Britain’s Chief Scientific Advisor Sir Patrick Vallance initiated the herd immunity policy. Another “expert” advocating herd immunity was Professor Peter Openshaw, past president of the British Society for Immunology and a Professor of Experimental Medicine at Imperial College London. In a 13 March statement Prof. Openshaw explained the theory: “Modelling studies show that, over time, we can expect 60-80 per cent of the population to be infected with SARS-CoV-2. Generating herd immunity in the population, and particularly in younger individuals who are less likely to experience serious disease, is one way to stop the disease spreading and provide indirect protection to older, more vulnerable groups.”

But the Imperial College COVID-19 Response Team modelling which underpinned the UK government’s herd immunity approach was based on pandemic influenza planning. The problem is that COVID-19 is very different to influenza. And by its own admission, the Imperial College team made all sorts of assumptions. For example, a 16 March paper states: “We assumed an incubation period of 5.1 days. Infectiousness is assumed to occur from 12 hours prior to the onset of symptoms for those that are symptomatic and from 4.6 days after infection in those that are asymptomatic with an infectiousness profile over time that results in a 6.5-day mean generation time.” (Emphasis added.) But an American Thoracic Society study on actual COVID-19 cases found that half of the patients they treated for mild symptoms still had the virus for up to eight days after symptoms disappeared.

“If you had mild respiratory symptoms from COVID-19 and were staying at home so as not to infect people, extend your quarantine for another two weeks after recovery to ensure that you don’t infect other people”, recommended corresponding author Lixin Xie, MD, a professor at the College of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing.

Professor Neil Ferguson and colleagues at Imperial College’s MRC Centre for Global Infectious Disease Analysis looked at the escalating crisis in Italy, crunched the numbers, and found that Britain’s herd immunity strategy would lead to 260,000 deaths. That would include deaths from other illnesses that the National Health Service (NHS) would be too hard-pressed to treat. The initial modelling at the Imperial College assumed that COVID-19 would be like an influenza pandemic. These models dramatically underestimated the demand for intensive care units (ICUs). Revised modelling by Prof. Ferguson’s team forced a rapid policy change.

The Oxford model

A recent model from Oxford University led by Professor Sunetra Gupta led to an outbreak of news headlines on 24 March, with the extraordinary claim that coronavirus could already have infected half the British population. “The new model from Oxford University suggests the virus was circulating in the UK by mid-January, around two weeks before the first reported case and a month before the first reported death”, reported the Daily Mail. “The modelling brings back into focus ‘herd immunity’, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected”, reported the Financial Times. One of the Oxford simulations suggested that 68 per cent of Britons would have been infected by 19 March. This scenario assumed the proportion of the population at risk of severe disease being distributed around 0.1 per cent.

One of the authors of the Oxford study, Paul Klenerman, called the figure of those it estimated to have already contracted the virus—68 per cent of the population—the most extreme result. He clarified to The Guardian: “There is another extreme which is that only a tiny proportion have been exposed”. Which goes to show, the GIGO principle in models cannot be overlooked!

Mass testing and hard data would verify the actual situation and assist us to eliminate SARS-CoV-2. Tests for current SARS-CoV-2 infection are important, but equally, antibody testing will be essential to verify the numbers of people who have previously contracted the virus. Antibodies specific to SARS-CoV-2 remain in the bloodstream to protect against further infection. Any models without such verifiable inputs risk a further disastrous policy response.

WTC 7 modelling reveals 9/11 truth

World Trade Centre Building 7
World Trade Centre Building 7

Flawed modelling by the US government in its analysis of the 9/11 terror attacks has been exposed in a University of Alaska Fairbanks report released on 25 March. A research team at the university’s engineering department has concluded that fire did not cause the collapse of World Trade Centre Building 7 (WTC 7) on 11 September 2001. Professor of Civil Engineering Dr J. Leroy Hulsey, who led the team, clearly demonstrated that the US government’s official version of the WTC 7 collapse is a scientific fraud, which leaves us with some very troubling questions about the entire 9/11 incident.

Flawed modelling by the US government’s National Institute of Standards and Technology (NIST) concluded in an August 2008 report that WTC 7 was the first tall building ever to collapse primarily due to fire. Thousands of professional architects and engineers have long expressed outrage over the NIST modelling, given all the available evidence indicates WTC 7 was taken down by controlled demolition. Architects & Engineers for 9/11 Truth (AE911Truth) funded Prof. Hulsey’s four-year study, which identifies numerous false assumptions NIST’s modelling.

Prof Hulsey’s 125-page Final Report, titled “A Structural Re-evaluation of the Collapse of World Trade Centre 7”, concluded “that the collapse of WTC 7 was a global failure involving the near-simultaneous failure of all columns in the building and not a progressive collapse involving the sequential failure of columns throughout the building”. Such a collapse will occur in a controlled demolition, but how could this have happened? WTC 7 was probably one of the most secure buildings in the USA, given the US Secret Service occupied floors 9-10; the Securities and Exchange Commission occupied floors 11-13; and the Department of Defence, Central Intelligence Agency (CIA), and Internal Revenue Service shared floor 25. Who were the terrorists that had access to WTC 7, and the extensive time and technology required to prepare it (and therefore likely the twin towers as well) for demolition?

By Jeremy Beck, Australian Alert Service 1 April 2020

Page last updated on 05 April 2020