On more than one occasion I have commented that too many deaths have been attributed Covid-19 that were not in fact caused by Covid-19. Yes, some patients who have died had Covid and it contributed to their demises. There were others who tested positive for Covid but were not symptomatic and it had nothing to do with their passing. Then there were those who never tested positive for Covid but had it listed as cause of death on their death certificates. Many have castigated me for making such claims, but when I challenged them to prove my claims were unfounded, they couldn’t.
Now comes a piece from Johns Hopkins University by Genevieve Briand, assistant program director of the Applied Economics master’s degree program at Hopkins, where she delved into the effect of COVID-19 on U.S. deaths using data from the Centers for Disease Control and Prevention (CDC). The conclusion from her analysis?
Surprisingly, the deaths of older people stayed the same before and after COVID-19. Since COVID-19 mainly affects the elderly, experts expected an increase in the percentage of deaths in older age groups. However, this increase is not seen from the CDC data. In fact, the percentages of deaths among all age groups remain relatively the same.The linked piece includes the breakdown in deaths from 2014 to 2020. I have also included a link to a webinar covering this topic.
One thing I must mention about this is that JHU made the article by Dr. Briand “disappear”. The links to the article and webinar came from Archive.org. (I guess JHU hasn’t realized that “The Internet is Forever.”)
On Thursday, Johns Hopkins University explained that they deleted the article on the study because it “was being used to support false and dangerous inaccuracies about the impact of the pandemic.”When studies are retracted, there are usually detailed explanations for the retraction. But JHU’s ‘explanation’ was along the lines of “Though making clear the need for further research, we just didn’t like the conclusions reached, so we spiked the article.”
They did not, however, challenge the accuracy of the data or its conclusions. In other words, the article was deleted because it didn’t fit the proper narrative.