Inaccurate Virus Models Are Panicking Officials Into Ill-Advised Lockdowns By Madeline Osburn for The Federalist
GNN Note – Bad information makes people more anxious while truthful, clear information relieves people – even if the information is hard to hear. The lies and propaganda are, literally, killing us and the satanic globalist know and understand this – look at what the Koreans did to American soldiers during the Korean War.
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How a handful of Democratic activists created alarming, but bogus data sets to scare local and state officials into making rash, economy-killing mandates.
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As U.S. state and local officials halt the economy and quarantine their communities over the Wuhan virus crisis, one would hope our leaders were making such major decisions based on well-sourced data and statistical analysis. That is not the case.
A scan of statements made by media, state governors, local leaders, county judges, and more show many relying on the same source, an online mapping tool called COVID Act Now. The website says it is “built to enable political leaders to quickly make decisions in their Coronavirus response informed by best available data and modeling.”
An interactive map provides users a catastrophic forecast for each state, should they wait to implement COVID Act Now’s suggested strict measures to “flatten the curve.” But a closer look at how many of COVID Act Now’s predictions have already fallen short, and how they became a ubiquitous resource across the country overnight, suggests something more sinister.
When Dallas County Judge Clay Jenkins announced a shelter-in-place order on Dallas County Sunday, he displayed COVID Act Now graphs with predictive outcomes after three months if certain drastic measures are taken. The NBC Dallas affiliate also embedded the COVID Act Now models in their story on the mandate.
The headline of an NBC Oregon affiliate featured COVID Act Now data, and a headline blaring, “Coronavirus model sees Oregon hospitals overwhelmed by mid-April.” Both The Oregonian and The East Oregonian also published stories featuring the widely shared data predicting a “point of no return.”
