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The Water Cooler
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CDC admits death toll is inflated! Of 161,392 deaths ONLY 6% / 9,683 ARE DIRECTLY CAUSED BY COVID.
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<blockquote data-quote="_CY_" data-source="post: 3417695" data-attributes="member: 7629"><p><a href="https://www.rt.com/op-ed/500000-covid19-math-mistake-panic/" target="_blank"><img src="https://media.thedonald.win/preview/HEbnxHI0.png" alt="" class="fr-fic fr-dii fr-draggable " style="" /></a></p><p><a href="https://www.rt.com/op-ed/500000-covid19-math-mistake-panic/" target="_blank">The 1% blunder: How a simple but fatal math mistake by US Covid-19 experts caused the world to panic and order lockdowns | September 6, 2020 | RT </a>(<a href="http://www.rt.com" target="_blank">www.rt.com</a>) </p><p></p><p>They got their IFR and CFR mixed up and multiplied the likely impact of Covid by a factor of ten.</p><p></p><p>Here’s what the paper, <em>“Public health lessons learned from biases in coronavirus mortality overestimation”,</em><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9" target="_blank">says</a>: “<em>On March 11, 2020,... based on the data available at the time, Congress was informed that the estimated mortality rate for the coronavirus was ten-times higher than for seasonal influenza, which helped launch a campaign of social distancing, organizational and business lockdowns, and shelter-in-place orders.”</em></p><p><em></em></p><p><em>====== </em></p><p><em> <ul> <li data-xf-list-type="ul"><br /> <a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/accepted-manuscripts" target="_blank">Accepted manuscript</a> August 2020 , pp. 1-24</li> </ul><p><span style="font-size: 22px"><strong>Public health lessons learned from biases in coronavirus mortality overestimation</strong></span></em></p><p><em> <ul> <li data-xf-list-type="ul"><a href="https://www.cambridge.org/core/search?filters%5BauthorTerms%5D=Ronald%20B.%20Brown&eventCode=SE-AU" target="_blank">Ronald B. Brown</a> (a1) <a href="https://doi.org/10.1017/dmp.2020.298" target="_blank">https://doi.org/10.1017/dmp.2020.298</a></li> <li data-xf-list-type="ul">Published online by Cambridge University Press: 12 August 2020</li> </ul><p><a href="https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9#" target="_blank">https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9#</a></em></p><p><em></em></p><p><em><span style="font-size: 18px"><strong>Abstract</strong></span></em></p><p><em>In testimony before U.S. Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was ten-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.</em></p><p><em></em></p><p><em></em></p></blockquote><p></p>
[QUOTE="_CY_, post: 3417695, member: 7629"] [URL='https://www.rt.com/op-ed/500000-covid19-math-mistake-panic/'][IMG]https://media.thedonald.win/preview/HEbnxHI0.png[/IMG] The 1% blunder: How a simple but fatal math mistake by US Covid-19 experts caused the world to panic and order lockdowns | September 6, 2020 | RT [/URL]([URL="http://www.rt.com"]www.rt.com[/URL]) They got their IFR and CFR mixed up and multiplied the likely impact of Covid by a factor of ten. Here’s what the paper, [I]“Public health lessons learned from biases in coronavirus mortality overestimation”,[/I][URL='https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9']says[/URL]: “[I]On March 11, 2020,... based on the data available at the time, Congress was informed that the estimated mortality rate for the coronavirus was ten-times higher than for seasonal influenza, which helped launch a campaign of social distancing, organizational and business lockdowns, and shelter-in-place orders.” ====== [LIST] [URL='https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/accepted-manuscripts']Accepted manuscript[/URL] August 2020 , pp. 1-24 [/LIST] [SIZE=6][B]Public health lessons learned from biases in coronavirus mortality overestimation[/B][/SIZE] [LIST] [*][URL='https://www.cambridge.org/core/search?filters%5BauthorTerms%5D=Ronald%20B.%20Brown&eventCode=SE-AU']Ronald B. Brown[/URL] (a1) [URL]https://doi.org/10.1017/dmp.2020.298[/URL] [*]Published online by Cambridge University Press: 12 August 2020 [/LIST] [URL]https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/public-health-lessons-learned-from-biases-in-coronavirus-mortality-overestimation/7ACD87D8FD2237285EB667BB28DCC6E9#[/URL] [SIZE=5][B]Abstract[/B][/SIZE] In testimony before U.S. Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was ten-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission. [/I] [/QUOTE]
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CDC admits death toll is inflated! Of 161,392 deaths ONLY 6% / 9,683 ARE DIRECTLY CAUSED BY COVID.
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