The Failures of Pandemic Central Planning

Magness, Phillip W.

doi:10.2139/ssrn.3934452

Cited by 3 publications

(8 citation statements)

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“…Economists have not been the only intellectuals who failed to question the official narrative 7 . The epidemiological models that constituted the basis for the policy turned out to be inconsistent with reality, but their proponents continued to insist on their validity and reliability (Kuhbandner et al, 2022; Magness, 2021; Snowdon, 2022). Many academic privacy advocates have preferred to overlook the devastating impact of various anti‐pandemic technological means, and some even applauded the contact tracing initiatives launched by the tech giants (Sharon, 2021, p. 548).…”

Section: The Pandemic Crisis and The Philosophy Of Ordersmentioning

confidence: 99%

“…As Ioannidis (2021) puts it, “[m]any brilliant scientists were abused and received threats during the pandemic, intended to make them and their families miserable”. At the same time, lockdown proponents could pick up the elements of the narrative that were taken for granted to support their arguments and be accepted for publication with little scrutiny (Magness, 2021).…”

Section: The Pandemic Crisis and The Philosophy Of Ordersmentioning

confidence: 99%

“…While the main approach to combatting the pandemic has been through command‐and‐control systems, there is still room to argue that a liberal order could provide a better outcome (Boettke & Powell, 2021; Magness, 2021). Such an outcome would not necessarily be a perfect solution, but it could allow the preservation of a sufficient level of economic transactions and avoid serious harm to economic well‐being.…”

Section: Introductionmentioning

confidence: 99%

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Rethinking the pandemic narrative: An ordoliberal perspective

Trubnikov

2022

Economic Affairs

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This article analyses the Covid‐19 pandemic narrative through the lens of the ordoliberal concept of interdependence of orders. This approach explains why the measures adopted eschewed market‐based solutions and suggests what their real driving forces were. The ordoliberal approach asserts that the concentration of power problem is not only a direct outcome of the government response to the crisis, but is also the main cause of the ways chosen to deal with it. This power concentration reached very dangerous levels, which affected social, technological, political and even academic orders, forming the system of incentives that encouraged all crucial players to support the chosen methods.

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Section: The Pandemic Crisis and The Philosophy Of Ordersmentioning

confidence: 99%

Section: The Pandemic Crisis and The Philosophy Of Ordersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Rethinking the pandemic narrative: An ordoliberal perspective

Trubnikov

2022

Economic Affairs

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“…Many governments subsequently adopted aggressive pandemic policies. Examples of these policies, imposed as large-scale restrictions on people, included (Gostin et al 2020;Jenson 2020, Magness 2021): quarantine (stay-at-home) orders, masking orders in community settings, nighttime curfews, closures of schools, universities and many businesses, and bans on large gatherings. Mathematical modelling studies using simulated pandemic scenarios were used to justify durations of restrictions imposed on people, ranging from 2 weeks to months (CDC 2017, Jenson, 2020.…”

Section: Introductionmentioning

confidence: 99%

“…The termflatten the epidemic curvewas originally utilized by the US Centers of Disease Control for pandemic planning (CDC, 2007) to warrant use of targeted antiviral medications and nonpharmaceutical interventions (NPIs) to delay and flatten the epidemic peak. implemented by governments, however, were lengthy as public health official policy targets shifted (Magness 2021). In United States, political influence dominated both the initiation and ultimate duration of these restrictions (Kosnik & Bellas, 2020).…”

Section: Introductionmentioning

confidence: 99%

Reproducibility of Health Claims in Meta-Analysis Studies of COVID Quarantine (Stay-at-Home) Orders

Young¹,

Kindzierski²

2022

IJSP

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The coronavirus pandemic (COVID) has been an extraordinary test of modern government scientific procedures that inform and shape policy. Many governments implemented COVID quarantine (stay-at-home) orders on the notion that this nonpharmaceutical intervention would delay and flatten the epidemic peak and largely benefit public health outcomes. The overall research capacity response to COVID since late 2019 has been massive. Given a lack of research transparency, only a small fraction of published research has been judged by others to be reproducible before COVID. Independent evaluation of published meta-analysis on a common research question can be used to assess the reproducibility of a claim coming from that field of research. We used a p-value plotting statistical method to independently evaluate reproducibility of specific research claims made in four meta-analysis studies related to benefits/harms of COVID quarantine orders. Research claims that these meta-analyses covered included: mortality, mental health symptoms, incidence of domestic violence, and suicidal ideation (thoughts of killing yourself). Three of the four meta-analysis studies that we evaluated (mortality, mental health symptoms, incidence of domestic violence) raise further questions about benefits/harms of this form of intervention. The fourth meta-analysis study (suicidal ideation) is judged to be unreliable. Given lack of research transparency and irreproducibility of published research, independent evaluation of meta-analysis studies using p-value plotting is offered as a way to strengthen or refute (falsify) claims made in COVID research.

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Statistical Reproducibility of Meta-Analysis for Medical Mask Use in Community Settings to Prevent Airborne Respiratory Virus Infection

Young¹,

Kindzierski²

2023

IJSP

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Many US states, cities, and counties implemented public masking orders during the coronavirus (COVID) pandemic on the notion that this intervention would delay and flatten the epidemic peak and largely benefit public health outcomes. A p-value plot can provide insights into possible inappropriateness (incorrectness) of assumptions of a statistical model. It can be used to confirm, disprove, or identify ambiguity (uncertainty) in a meta-analytic finding and research claim. P-value plotting was used to evaluate statistical reproducibility of meta-analysis studies for disposable medical (surgical) mask use in community settings to prevent airborne respiratory virus infection. Eight studies (seven meta-analysis, one systematic review) published between 1 January 2020 and 7 December 2022 were evaluated. Base studies were randomized control trials with outcomes of medical diagnosis or laboratory-confirmed diagnosis of viral (Influenza or COVID) illness. Self-reported viral illness outcomes were excluded from the evaluation because of awareness bias. No evidence was observed for a medical mask benefit to prevent respiratory virus infection in six p-value plots (five meta-analysis and one systematic review). Research claims of no benefit in three meta-analysis and the systematic review were reproduced in p-value plots. Research claims of a benefit in two other meta-analysis were not reproduced in p-value plots suggesting irreproducibility of these claims. Insufficient data was available to construct p-value plots for two other meta-analysis because of over-reliance on self-reported outcomes. Independent findings of p-value plotting show that meta-analysis of existing randomized control trials fail to demonstrate a benefit of medical mask use in community settings to prevent airborne respiratory virus infection.

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The Failures of Pandemic Central Planning

Cited by 3 publications

References 0 publications

Rethinking the pandemic narrative: An ordoliberal perspective

Rethinking the pandemic narrative: An ordoliberal perspective

Reproducibility of Health Claims in Meta-Analysis Studies of COVID Quarantine (Stay-at-Home) Orders

Statistical Reproducibility of Meta-Analysis for Medical Mask Use in Community Settings to Prevent Airborne Respiratory Virus Infection

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