Glen Bishop

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The Irrationality of the Lockdowns

by Glen Bishop Much has been said on Lockdown Sceptics about how poor the SPI-M modelling has been – the naivety of the assumptions, how demonstrably ridiculous the projections were and are when compared to Florida, South Dakota and elsewhere, and how far we currently are below their most optimistic scenarios for deaths and hospitalisations. This is certainly true yet is merely semantics because imposing lockdowns and restrictions would still be irrational even if they were correct. Assuming the counterfactual to be true, i.e., Ferguson’s famous 500,000 deaths prediction in the 'do nothing' scenario, I will lay the case below as to why our Covid response has not been reasonable but hysterical, financially and in terms of cost to life, even if the Ferguson prediction were the reality that had been avoided.    Firstly, as of July 19th, the new prospective date for lockdowns end, the citizens of our glorious ‘free country’ will have been under house arrest or had to endure harsh restrictions for 483 days. What then is the gain from such a sacrifice? According to the Ferguson estimate, if 500,000 people would have died from Covid had these measures not been imposed, then a total of (500,000-128,000) 372,000 lives have been saved. Actuarial tables estimate an average number of years of life lost to a Covid death...

Not So SAGE After All: A Review of the Latest Models

by Glen Bishop The latest release of papers from SAGE, modelling the relaxation of restrictions, tells us more about the psychology and authoritarian tendencies of the power drunk cabal of scientists in SAGE than they do about the future trajectory of the pandemic. The overly pessimistic assumptions remain in the papers, such as Imperial's assumption that two doses of the AstraZeneca vaccine have only an 80% efficacy against death from coronavirus. Numerous studies have found the protection to be 90% or even 95%. This assumption alone, even if all else were perfect, could be causing a two to four-fold over estimation in deaths of those vaccinated. Despite this, the central modelling predictions from the three teams for deaths between now and June 2022 (under the current roadmap) are as follows: 7,500 (Warwick), 9,000 (Imperial) and 11,200 (LSHTM). As data savvy readers will know, these are far below the cumulative deaths in a bad flu season – for instance, the flu season of 2017-2018 cost 22,087 lives, according to PHE. A rational group of scientists would advise that risks are now within the normal accepted range and thus the end of restrictions is nigh and normal life will return. Unsurprisingly, that is not what these three modelling teams have done. Their models have failed to deliver the pessimism and danger craved...

SAGE Modelling From May Last Year Said Approach Recommended in Great Barrington Declaration Was Least Bad Alternative to Lockdown

by Glen Bishop In May last year, after the UK had been plunged into lockdown for the first time, the Warwick SAGE SPI-M team released a paper analysing the potential exit strategies and their projections for deaths under each scenario. Whether their projections were correct is debatable because of the vagueness of their assumptions, but more importantly the paper inadvertently highlights why lockdowns are farcical.    Below is the graph projecting the pandemic course under different scenarios of lifting lockdown last year. The graph is poorly labelled and hard to follow, so bear with this explanation. It models five scenarios of releasing lockdown, where restrictions are eased on the May 7th by varying degrees, from no release to full release at intervals of 25% i.e., 0%, 25%, 50%, 75% and 100%. With these levels of restrictions maintained until January 1st 2021, at which point, they are all released fully. The effect of this eventual release is shown in the ‘no controls’ side of the graph which is a continuation of the five same lines into 2021. As shown on the left-hand side representing 2020, the lines of 50%, 75% and 100% release of restrictions, projected an immediate resurgence in the virus with predictions of daily summer death tolls between 1000 and 4000 at their peaks. Clearly this did not happen...

Imperial College Modelling Falsely Assumes No Seasonality to COVID-19

by Glen Bishop Is this the source of Neil Ferguson's model assumptions? (Credit: Miriam Elia) How likely is it, that there is going to be a summer surge in SARS-CoV-2, a surge where hospitals have similar numbers of coronavirus admissions to what they saw in January? Pretty unlikely, I would have guessed. But doing the rounds in the news was a paper by the Imperial College modelling team projecting just that. It predicts, as a mid-range scenario, 130,000 more deaths, with a catastrophic summer surge even if restrictions are lifted at the current snail's pace and the vaccination programme goes well, at two million doses per week from February. As a maths student at Nottingham University, I have been reading through some of the modelling done for SAGE recently. Bad modelling at the beginning of a pandemic, particularly with a communist country withholding or obscuring crucial data, is understandable. What I did not understand was how predictions of scenarios worse than have occurred anywhere in the world keep being predicted for the UK. On reading the paper, I realised they are assuming there is absolutely no seasonality to SARS-CoV-2. This is fundamentally wrong. They are attributing all the reduction in R-value last spring to non-pharmaceutical interventions (NPIs) and none to seasonality, leading to assumptions that the base R-value in July...

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May 2024
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