Media Hoaxes: No, Sturgis Was Not A ‘Superspreader Event,” And No, It Did Not Cost ‘Public Health $12.2 Billion’

Gov. Kristi Noem: “This report isn’t science; it’s fiction. Under the guise of academic research, this report is nothing short of an attack on those who exercised their personal freedom to attend Sturgis” The post Media Hoaxes: No, Sturgis Was Not A ‘Superspreader Event,” And No, It Did Not Cost ‘Public Health .2 Billion’ first appeared on Le·gal In·sur·rec·tion .

Source: Media Hoaxes: No, Sturgis Was Not A ‘Superspreader Event,” And No, It Did Not Cost ‘Public Health $12.2 Billion’

The Pandemic is Winding Down

This is a nice, well-sourced piece in The American Thinker

In contrast to the Covid19 attributed deaths, the number for deaths from all causes is a hard number.  The deaths from all causes number exposes the current mass panic as an historical aberration and confirms the evidence that the mass panic has been engineered by politicians and a biased medical establishment.

The Covid-19 Pandemic is Ending

The 11 year weekly deaths from all causes graph (here and below,) shows that the 2020 flu season was about normal until it spiked for eight weeks in April and May due to Covid19 (CDC data here and here).  The April high of 78,000 was significantly higher than the previous multi-year high of 67,000 in 2018, but just as in previous years, the temporary spike rapidly declined toward baseline.

The 11 year baseline increased from about 45,000 in 2009 to about 51,000 in 2019, generally as a result of increasing population.  After this year’s April spike to 78,000, the current weekly all causes deaths number is down to 55,000, about 4,000 higher than the projected baseline.  We are at week 32 of the year, and flu season is about to kick in.  What does this mean regarding the Covid19 epidemic?

Testing Targets and Intensifies Social Distancing on the Infectious

I’ve been pounding on the need for fast, frequent testing but it’s clear from some of the comments to The Beginning of the End that I have failed to convey some fundamental points. A seemingly sophisticated objection is to note that given background prevalence rates even a fairly specific test will result in a high fraction of false positives among those who test positive. (This is the standard Bayesian doctor puzzle .) It’s nice to see people doing the Bayes calculation but some of them are then drawing the wrong conclusion.

Source: Testing Targets and Intensifies Social Distancing on the Infectious

Ten Million Cases

A post on the Book of Feces Faces was lamenting that we’re up to ten million cases of Covid-19. Just for perspective, the CDC estimates that during the 2018-2019 season, the US had some 35.5 million cases of the flu. Of these, 16.5 million people went to a health care provider for their illness, 490,600 were hospitalized, and 34,200 died.

So worldwide, we have just over 10 million cases of Covid-10. Of these, nearly 503,000 have died. In the USA, we’ve had 2.6 million cases, and 128 thousand deaths. So there are a lot fewer cases, but it does seem to have a higher mortality rate.

I still wonder what the reaction would have been had the news presented daily counts of the numbers of cases and deaths from flu two years ago.