Tag Archives: COVID

Nutball Leftists

These crazy statists are just not gonna give up the COVID fear-mongering. These people, and the imbeciles that legitimize them, are complete lunatics. If the outrageous response to a bad flu season is the benchmark, what will happen to our Dumfukistan if we were confronted with an actual existensial crisis? I shudder to think.

It also bears repeating that the absurd mask edicts and destructive lockdowns had zero positive impact on dampening the virus. Zero.

…and it is also worth noting that the vaccines do not prevent you from catching COVID, nor do they prevent you from giving it to others.

Karens in government seem to think that their personal fear and memory of trauma somehow justifies the revocation of everyone else’s liberty. They are deranged.

Real COVID Data, Presented Without Commentary

The predicted deaths is an estimate of weekly deaths based on linear regression of continuous time series and seasonality is derived by assigning each week to one of 13 periods. Actual data from 2015 through 2019 is used to determine the predicted totals.
The excess deaths in 2020 through 12/5 stands at 310,000 according to this model.

COVID Projections Using Population Density

COVID Projections:

When looking at COVID fatality data, 2 things jumped out at me. 1) correlation between state population density and deaths per capita and 2) the shape of the curve of fatalities. If you build a model that estimates per capita fatalities using pop density and weeks beyond peak fatality day, you get a very strong predictor (89% R^2).

The (linear) equation is:
Est fatalities per million = -56 + 14 * (weeks from peak) + .92 * (Pop Density)

Where there are large differences between estimated and actual, one could hypothesize that they are an indication of where that state is in the “curve” or lifecycle of the outbreak.

States that are the farthest along in the curve (expect declining fatality counts) are as follows:

States that are the furthest behind (expect rising fatality counts) are as follows: