A report in The Federalist argues that poorly-sourced data and incorrect statistical analysis may be influencing U.S. state and local officials. The Federalist cites Jessica Hamzelou of New Scientist who reports on systematic errors that researchers and scientists have found with the modeling COVID Act Now relies on.

Statements made by media, state governors, local leaders, county judges, and more show they are relying on the same source. It’s an online mapping tool called COVID Act Now.

COVID Act Now identifies itself as a tool “built to enable political leaders to quickly make decisions in their Coronavirus response informed by best available data and modeling.”

If COVID Act Now’s suggested measures are not accepted, the tool predicts a “catastrophic forecast for each [U.S.] state.”

COVID Act Now’s predictions have “already fallen short,” The Federalist reports, but this hasn’t prevented officials from sourcing COVID Act Now:

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.”

Michigan Gov. Gretchen Whitmer cited COVID Act Now when telling her state they would exceed 7 million cases in Michigan, with 1 million hospitalized and 460,000 deaths if the state did nothing.

A local CBS report in Georgia featured an Emory University professor urging Gov. Brian Kemp with the same “point of no return” language and COVID Act Now models.

In particular, Jessica Hamzelou at New Scientist says there are systematic errors that researchers and scientists have found with the modeling COVID Act Now relies on:

Chen Shen at the New England Complex Systems Institute, a research group in Cambridge, Massachusetts, and his colleagues argue that the Imperial team’s model is flawed, and contains ‘incorrect assumptions’. They point out that the Imperial team’s model doesn’t account for the availability of tests, or the possibility of ‘super-spreader events’ at gatherings, and has other issues.

COVID Act Now has “Known Limitations” of their model:

Many of the inputs into this model (hospitalization rate, hospitalization rate) are based on early estimates that are likely to be wrong.

Demographics, populations, and hospital bed counts are outdated. Demographics for the USA as a whole are used, rather than specific to each state.

The model does not adjust for the population density, culturally-determined interaction frequency and closeness, humidity, temperature, etc in calculating R0.

This is not a node-based analysis, and thus assumes everyone spreads the disease at the same rate. In practice, there are some folks who are ‘super-spreaders,’ and others who are almost isolated.

More from The Federalist:

So why is the organization or seemingly innocent online mapping tool using inaccurate algorithms to scaremonger leaders into tanking the economy? Politics, of course.

Founders of the site include Democratic Rep. Jonathan Kreiss-Tomkins and three Silicon Valley tech workers and Democratic activists — Zachary Rosen, Max Henderson, and Igor Kofman — who are all also donors to various Democratic campaigns and political organizations since 2016. Henderson and Kofman donated to the Hillary Clinton campaign in 2016, while Rosen donated to the Democratic National Committee, recently resigned Democratic Rep. Katie Hill, and other Democratic candidates. Prior to building the COVID Act Now website, Kofman created an online game designed to raise $1 million for the eventual 2020 Democratic candidate and defeat President Trump. The game’s website is now defunct.

Perhaps the goal of COVID Act Now was never to provide accurate information, but to scare citizens and government officials into to implementing rash and draconian measures. The creators even admit as much with the caveat that “this model is designed to drive fast action, not predict the future.”

They generated this model under the guise of protecting communities from overrun hospitals, a trend that is not on track to happen as they predicted. Not only is the data false, and looking more incorrect with each passing day, but the website is optimized for a disinformation campaign.

We are committed to truth and accuracy in all of our articles. Submit a correction.