Re: Trump Helpless As Fauci Admits He Made Up Tyrannical COVID Guidelines

In article <[email protected]>, [email protected] 
says...
> 
> >So much for follow the science.
> >He should be tried for treason.
> >
> 
> They should have left the decision making up to Republican politicians, 
> that way the trumper deaths would have been in the millions, not just 
> hundreds of thousands.   All patriots say that a good trumper is a dead 
> one.
> 
> Health Policy Open. 2023 Dec 15; 5: 100107.
> Published online 2023 Nov 11. doi: 10.1016/j.hpopen.2023.100107
> PMCID: PMC10684792
> PMID: 38034472
> The politics of COVID-19: Differences between U.S. red and blue states in 
> COVID-19 regulations and deaths
> C. Dominik Güss,a,? Lauren Boyd,a Kelly Perniciaro,b Danielle C. Free,b 
> J.R. Free,c and Ma. Teresa Tuasonb
> Author information Article notes Copyright and License information PMC 
> Disclaimer
> Go to:
> Highlights
> 
>     ?
>     Political party-affiliation has shaped response efforts to the COVID-19 
> pandemic.
>     ?
>     Red states had higher COVID-19 infection rates and deaths in 2021 
> compared to blue states.
>     ?
>     Red states implemented fewer political decisions to mitigate COVID-19 
> than blue states.
>     ?
>     Biological factors such as age and obesity predicted deaths only in red 
> states.
>     ?
>     Vaccination rates predicted fewer deaths in blue states.
> 
> Keywords: COVID-19, Policies, COVID deaths
> Go to:
> Abstract
> 
> The study investigated infection variables and control strategies in 2020 
> and 2021 and their influence on COVID-19 deaths in the United States, with 
> a particular focus on comparing red (Republican) and blue (Democratic) 
> states. The analysis reviewed cumulative COVID-19 deaths per 100,000 by 
> year, state political affiliation, and a priori latent factor groupings of 
> mitigation strategies (lockdown days in 2020, mask mandate days, 
> vaccination rates), social demographic variables (ethnicity, poverty rate), 
> and biological variables (median age, obesity). Analyses first identified 
> possible relationships between all assessed variables using K-means 
> clustering for red, blue, and purple states. Then, a series of regression 
> models were fit to assess the effects of mitigation strategies, social, and 
> biological factors specifically on COVID-19 deaths in red and blue states. 
> Results showed distinct differences in responding to COVID infections 
> between red states to blue states, particularly the red states lessor 
> adoption of mitigation factors leaving more sway on biological factors in 
> predicting deaths. Whereas in blue states, where mitigation factors were 
> more readily implemented, vaccinations had a more significant influence in 
> reducing the probability of infections ending in death. Overall, study 
> findings suggest politicalization of COVID-19 mitigation strategies played 
> a role in death rates across the United States.
> Keywords: COVID-19, Policies, COVID deaths
> Go to:
> 1. Introduction
> 
> The COVID-19 pandemic has had a profound and expansive impact on numerous 
> facets of human existence, resulting in millions of lives being lost and 
> countless others being changed forever. On the surface, the pandemic 
> initially presented as a significant public health crisis; however, 
> numerous disruptions to global operations including supply chain issues, 
> economic instability, workforce imbalances, and inconsistent government 
> response strategies amplified the difficulty of containing the disease. In 
> the first year of managing the disease, 2020, effort focused on limiting 
> exposure through social distancing, wearing masks, and mandatory lockdowns. 
> The second year, 2021, gave way to advancements in understanding the virus 
> and the development of several vaccines and antiviral options. On a global 
> level, COVID-19 has been handled with mixed results, but the following 
> study examines factors and outcomes exclusive to the United States COVID-19 
> landscape.
> 1.1. Sociopolitical and legislative influence
> 
> COVID-19 numbers in the United States surpassed all other reporting 
> countries for both cumulative cases and deaths, making its use of mass 
> behavioral mitigation measures of particular interest. While many nations 
> focused on a federal mandate process to manage their response to the 
> pandemic [1], [2], the United States adopted a jurisdictional state-based 
> approach. This approach created a unique Petri dish to examine a spectrum 
> of containment strategies across a multitude of demographic and 
> sociopolitical factors.
> 
> With the emergence of COVID-19 and each new viral variant, such as Delta 
> and Omicron, mass mitigation measures were reintroduced in varying 
> capacities and success rates to limit new exposures. The need for these 
> daily habit changes were justified based on historical precedent and modern 
> research related to epidemiology [3], but the efficacy of mass behavioral 
> changes was questioned by some scientists and sections of society [4]. 
> While skepticism, especially among the general public, can be 
> conspiratorial or bizarre in nature [5], [6], there is a genuine and 
> appropriate concern regarding the effectiveness of mass-behavioral methods 
> [7]. Analyzing state policies across 2020 and 2021, with a specific focus 
> on success in reducing the number of pandemic deaths, can provide valuable 
> insight on successful mass behavioral mitigation strategies and inform 
> early intervention protocol for future viral outbreaks.
> 
> In the United States, COVID-19 and efforts to quell the outbreak were 
> largely politicized (e.g., proposed bill against requiring the wearing of 
> masks, 117th Congress 2021?2022, as well as media coverage [8]). Federal 
> actions related to behavioral mitigation measures during the pandemic were 
> largely suggestive and mostly consisted of recommendations and guidelines 
> for social interactions [9], brief travel restrictions, or were exclusive 
> to federal employees [10]. Federal actions focused more on resource 
> production and economic stimulus than behavior efforts [11], [12]. Whereas, 
> states were responsible for outlining specifications of mask mandates, as 
> well as the degree and length of enforcement [13]. This begs the question 
> whether there is a divide between state political affiliations in terms of 
> COVID-19 deaths.
> 
> In general terms, a state?s legislative efforts are influenced by the 
> overall political affiliation of a state and its sitting governance. As 
> such, the dominant political affiliation for each state can be derived from 
> its gubernatorial party affiliation, state senate affiliation, and state 
> house of representative affiliation. Whether a state is blue or red may 
> influence the types of legislation instated, which in turn may affect the 
> overall spread of COVID-19. In essence, a state?s legislative measures on 
> COVID-19 and consequential changes in viral patterns, provide a natural 
> experiment to evaluate strategy efficacy. This study seeks to investigate 
> if a state?s political affiliation, herein labeled as republican-affiliated 
> (red) or democratic-affiliated (blue), plays a significant role in the 
> efficacy of mitigation measures and resulting number of COVID-19 deaths.
> 1.2. Pre-pandemic demographics
> 
> In a similar vein to a state?s political affiliation, a state?s demographic 
> context prior to the pandemic is likely to play a role in overall deaths 
> due to COVID-19. Assessments of at-risk groups have identified the elderly 
> and those with underlying health issues, especially those with diabetes or 
> obesity, as most likely to be both infected by and die due to complications 
> related to COVID-19 [14], [15].
> 
> Racial disparities in infections, deaths, and healthcare equity are of 
> utmost concern given the diverse demographics of the United States [16]. 
> Previous research conducted during the pandemic indicated that COVID-19 
> infections and deaths disproportionally affect racial and ethnic minorities 
> in the United States [17], [18]. The Center for Disease Control?s page on 
> ?Health Equity Considerations and Racial and Ethnic Minority Groups? 
> summarizes a number of studies to determine primary factors which likely 
> cause the observed racial and ethnic differences in COVID-19 cases: 
> discrimination, healthcare access, occupational hazards, exposure, and 
> socioeconomic gaps [19]. In further addressing healthcare access and usage 
> disparities, people of color are less likely to have received at least one 
> dose of a COVID-19 vaccine, compared to white counterparts [20].
> 1.3. Existing research
> 
> The academic community responded to the need for COVID-19 research; 
> however, this left some notable early deficiencies in the literature [21]. 
> Due to the breadth of pandemic factors, as well as the infeasibility of 
> traditional study methods while remaining socially distanced, early works 
> focused on opinion, single-state or single-behavior observations, sub-
> grouping populations across behaviors, or the efficacy of well-being 
> factors [22]. This pointed approach is evidenced by the targeted 
> examination of single-state/single-behavioral measure studies, such as 
> infection rates post-vaccination in Kentucky [23]; assessment of a single-
> state and efficacy of several mitigation measures, such as trends in 
> mitigation measures within Arizona [24]; and examination of a single-
> behavioral measure, such as mask adherence, across all states [25].
> 
> However, recent studies are branching out beyond direct examination of 
> COVID-19 medical consequences to review the nationwide aftermath of the 
> pandemic within constructs of mental wellness [26], economic infrastructure 
> [27], and the context of collateral health concerns such as post-pandemic 
> weight gain [28] and alcohol use [29]. Researchers are beginning to examine 
> the political polarization of COVID-19 preventative measures [30] and 
> treatments [31] but the majority of studies appear to be on a 
> representative subsect of the population. Few studies have examined larger 
> scale public data against political affiliations, health constructs, and 
> infection/death rates, but there have been notable exceptions, such as a 
> review of the relationship between partisan affiliations, obesity, and 
> death rates [32]. The imparting lesson being that health is a multifaceted 
> concept which must be analyzed through well-aimed examination of controlled 
> constructs and as the sum of its parts to derive genuine understanding of 
> complexities [33], [34], [35]. To this point, the current study accounts 
> for the majority of states and a dynamic assessment of variables to create 
> a more comprehensive picture of COVID-19 deaths in the US.

I made you forge me because I kicked your ass so bad.

-- 


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