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Showing posts from April, 2020

A Quick Review of Michael Moore's Planet of the Humans

Last night I watched the new Michael Moore film Planet of the Humans .  Here is a really quick overview / synopsis: Solar energy is not sustainable and not ‘green’. Wind energy is not sustainable and not ‘green’. Biomass energy (i.e. burning trees) is not sustainable and not even remotely ‘green’. Electric cars essentially run on coal, and are thus not sustainable and not ‘green’.  In addition the production of their batteries is extremely damaging to the environment and they only last a few years. The big ‘environmentalist’ groups are just corporatists who wrap themselves in a green smokescreen. Al Gore, Michael Bloomberg, Richard Branson and other eco-millionaires and eco-billionaires have corrupted the environmentalist movement to enhance their own personal wealth. Environmentalism has become a ‘religion’ that leftists have embraced in order to alleviate their own fears of death. Humans are the problem; we need to reduce the number of humans on the face of the earth and

Implementing a Trigger-Based Approach to Facilitate Local Management of Social Distancing Measures

Last week, I wrote about one of the most dramatic developments in the fight against COVID-19, the fact that Harvard University epidemiologists determined that continuing extreme social distancing measures into the summer months could actually result in more COVID-19 deaths than a ‘do nothing from the beginning’ alternative .  That finding is stunning in its implications.  Even more stunning is the fact that no one in the mainstream media has picked up on it and reported it.  I guess it simply does not match their narrative and thus needs to be ignored. The main takeaway of that particular result of the Harvard model is strikingly simple (to me, anyway):  Unless a given locality is facing an acute shortage of healthcare-related resources, they should STOP ALL GOVERNMENT-MANDATED SOCIAL-DISTANCING REQUIREMENTS IMMEDIATELY .   Then they should implement a trigger-based plan to appropriately adjust social-distancing measures over time, as warranted by demands on local healthcare resou

The Rationale for Stopping All Government-Mandated Social Distancing Immediately

Epidemiologists universally acknowledge that population immunity is the only way to defeat SARS-CoV2 (the virus that causes COVID-19); population immunity will develop once enough ‘healthy’ individuals have been exposed to and recover from the virus, or once a vaccine has been developed and widely administered . Whereas development of a safe and effective vaccine is at least several months away, and could take years , we need long periods of ‘incomplete’ or ‘partial’ social distancing (but with a tight focus on protecting the most vulnerable members of our society ). To put this all into perspective, in their recent SARS-CoV2 / COVID-19 prediction models, Harvard epidemiologists found that “ social distancing with 60% reduction in R0 … was so effective that virtually no population immunity was built ” (italics added, p. 5). In other words, strong social distancing measures (like those currently in place) are too effective -- no population immunity can be built while they are in e

BREAKING: Harvard Epidemiologists Find that Extreme Social Distancing Could Lead to More COVID-19 Deaths than the DO NOTHING Alternative

Harvard University epidemiologists published a fascinating article in Science magazine yesterday.  I am going to delay posting a deeper dive into the Imperial College and University of Washington models so that I can devote my time today to getting the word out about the implications of this  new Harvard model . Here is what the Harvard researchers did: They ‘calibrated’ their model using historical data (2014-2019) from two strains of the common cold in the U.S.  This makes a lot of sense, because the common cold is a type of coronavirus, so it is reasonable to expect similarities. They simulated outbreaks (i.e. infection peaks) based on a range of ‘effectiveness’ of various non-pharmaceutical interventions (NPIs).  Rather than complicate the model by trying to estimate the effectiveness of specific NPIs (such as school closures, stopping mass gatherings, etc.), they characterize the sum-total of all NPIs in effect at any given time.  The ranges of ‘effectiveness’ they sim

The Imperial College COVID-19 Model Predicted a 98% Reduction in COVID-19 Deaths WITHOUT Closing Non-Essential Businesses

When Oklahoma Governor Kevin Stitt announced on March 24 that he was issuing an order closing all non-essential businesses in 19 counties (which he subsequently extended to all 77 counties ), my heart sank.  I knew of no evidence supporting such a drastic move, and I was skeptical that any such evidence actually existed.  In other words, I was skeptical that such a move would significantly reduce the death toll from COVID-19 and I was certain that the fallout (in terms of actual harm caused to individual citizens) would be dramatic. As a very technical person who remains inherently skeptical of claims not supported by solid evidence and/or well-reasoned arguments, I took it upon myself to review a plethora of reports and data analyses regarding the spread of the deadly SARS-CoV2 virus (the virus that causes COVID-19).  In that respect, I strongly prefer going to the source documents written by acclaimed ‘experts’ rather than merely relying upon interpretations (or interpretatio