Abstract

Background: Shortly after the detection of the COVID virus in January 2020 the US Government introduced and enforced a series of restrictions to protect the elderly from a “deadly virus” and the “pandemic of the century”. Persons who disagreed were silenced and punished.

Objective: In the 15^th month of COVID epidemic (April 2021), we have access to sufficient statistical data and methods to better understand the nature, origin of the COVID pandemic. It is now possible to reliably evaluate the effectiveness of the restrictions and the human factors/driving forces behind this drastic limitation of our natural freedom in this country.

Methods: Publicly available epidemiological and population parameters were collected and analyzed using the ‘political score’ and ‘restriction ranking’ of 50 states and evaluated by simple and usual statistical methods, mainly correlation analyses.

1. The Political Score of the States (D/R) is the ratio of the number of citizens who self-identified as democrats (D) or republicans (R). The political scores of the 50 states altogether defined a wide, continuous scale, the political scale, that could be used to measure (and statistically evaluate) the effect of politics of a state on the numerical parameters of that state, including population and epidemiologic parameters.
2. The COVID Restriction Score of the States were created to rank the states from 1-50, there 1 is the lowest number of restrictions and 50 is the highest number of restrictions applied by the States. It was based on 13 different key metrics.

Results: This study revealed, that 1) restrictions reduced the number of viral infections, but 2) they totally failed to reduce the number of supposedly COVID related deaths, expressed as mortality, 3) they increased (SIC!) the lethality of coronavirus. The grade of restrictions were/are strongly associated to the 4) left/right political ratio of the States, there States with more democrat citizens practiced more restrictions. It was found that race, religion and Medicare/healthcare spending have significant influence on politic as well as on the grade of restriction orders. Factors moving States toward the political left and harder COVID restrictions have 5) larger ‘non-white’ population, 6) larger number of ‘non-protestant’ believers, 7) larger Jewish population, and 8) more generous Medicare/healthcare spending. It was not possible to see any influence of the size of the 9) senior (65+) population [i.e. those who are allegedly the most vulnerable and are mostly in need of protective restrictions] neither on the States politic nor on the restrictions.

Conclusion: The degree of restrictions enforced by different states ware not primarily determined by biological or epidemiological factors (like number of elderly, say 65+ in the state) but by social, political influences instead. Political (a), religious (b) ethnic (c) and economic (d) forces represented the decisive forces on the state’s restrictive orders and not the convincing evidence of the potentially harmful effects of the COVID infection and the well-founded adequacy of the defense against it.