Examining the Effects of Social and Economic Freedoms on the COVID-19 Pandemic

Aim: The goal of this study was to examine how social and economic freedoms, as well as related variables, impacted the COVID-19 pandemic, including governmental pandemic response and cases, deaths, and tests throughout 2020. Materials and Methods: To explore the effects of social and economic freedoms, gross domestic product (GDP), and other parameters on the COVID-19 pandemic, multiple datasets, including the Economic Freedom Index and the Human Freedom Index were used, along with COVID-19 data, to examine both direct and indirect relationships. The K-Means clustering algorithm was used for many analyses. Results: High economic and social freedoms were associated with increased numbers of COVID-19 cases and deaths throughout 2020. Countries within the highest category of economic freedoms reported their first COVID-19 case 44 days before and their


Introduction
On December 31, 2019, COVID-19 was first reported to the World Health Organization, and on March 11, 2020, COVID-19 was officially declared a global pandemic [1].
Since its late-2019 origination in China's Wuhan Province, the virus has infected well over 100 million people worldwide [2].
Despite the pandemic's foreseen long-lasting effects on global society, analysis of its spread is often focused on short-term individual government responses.Thus, the focus of this paper is to explore how pre-existing national social and economic freedoms and other related variables contributed to the virus' spread, widening the scope of inquiry.The Human Freedom Index, sponsored by the Cato Institute, one of the United States' most widely cited research organizations, the Economic Freedom Index, sponsored by the Wall Street Journal and the Heritage Organization, the world's most influential think tank, and datasets from OurWorldInData were used to examine the following hypotheses regarding the relationship between pre-existing national freedoms and the severity of the COVID-19 pandemic [3][4][5][6][7][8][9].
First, countries with greater economic freedoms were predicted to have higher and earlier COVID-19 case surges in the Spring of 2020, due to increased global exposure and dependency on trade, along with less willingness to impose economic shutdowns.Further expectations included that countries with significant social or human freedoms would be less likely to impose harsh restrictions on their populations due to higher freedom standards, and their populations would be less inclined to follow restrictions even when implemented, contributing to increased COVID-19 infection rates.Lastly, it was hypothesized that countries with higher GDPs, shown to be associated with higher economic freedoms, would be more likely to have the resources (monetary, scientific, etc.) to respond to the pandemic, namely treating infected individuals, minimizing the virus' fatality rate in their populations.November 30, 2020, while all other dates were chosen based on data availability and situational specificity.
For example, February 1, 2020 was deemed the starting date of the analysis on economic freedoms' relationship to the early pandemic, but that date does not represent the official beginning of "Spring 2020" due to a lack of data, namely in COVID-19-stringency scores.

Dataset descriptions
The Economic Freedom Index calculates economic freedom scores for each country in the world on an ascending 1-100 scale, with superscores calculated from over 30 wide-ranging features [5].Economic freedom superscores were used, along with specific selected features chosen by relevance to the COVID-19 pandemic.The Human Freedom Index calculates human freedom scores for each nation on an ascending 1-10 scale, computing superscores from well over 100 features [3].As with values from the economic freedom index, certain variables within the index were selected for additional analyses due to their relevance in influencing the pandemic.COVID-19 data consisted predominantly of confirmed and reported case counts, death counts, and testing information from the Global Data Change Lab in partnership with Oxford University [7][8][9].Despite their inclusion in the Economic Freedom Index, countries' individual Gross Domestic Product (GDP) values, represented in billions of U.S. dollars, were utilized distinctly in relevant analyses [5].
COVID-19 governmental response data was obtained from the OurWorldInData COVID-19 Stringency Index, with stringency superscores calculated from a collection of smaller governmental restriction parameters on an ascending 1-100 scale [9] were both used for each nation and sourced from OurWorldInData [9].

Research tools
The Python programming language and the Google Colaboratory IDE, were used for all data analyses.
Matplotlib and Microsoft Excel were used for the creation of tables and figures [16].

Clustering and data analysis
After preliminary data collection and exploration, clustering (isolating groups with similar traits) and specific statistical calculations were used for analyses.
Social and economic freedoms were clustered together and separately, primarily with the K-Means algorithm.For example, several different instances of the K-Means algorithm were used to obtain categories in Table 1, with placements based on either 1) a single K-Means model trained with both freedom indexes or 2) a K-Means model trained solely on economic or social freedom scores separately.
In clustering GDP values, uneven data distributions and lack of multiple features rendered K-Means ineffective and unnecessary in obtaining data for the first section of Table 2, "GDP vs. COVID-19 Impact", as well as the GDP-focused section of Table 5.Instead of K-Means, countries were ranked by GDP and then divided equally into four categories.
However, for the analysis included in the second half of

Early pandemic analyses
Economic freedoms were strongly associated with Note that the numbers of countries included in the analyses above reflect the available data.1).
This pattern of greater freedoms corresponding to higher COVID-19 cases and deaths can be seen across every category for each season throughout 2020.
Early in the pandemic COVID-19 testing was significantly higher in countries with the highest social and economic freedoms.However, this trend in testing based on overall freedoms was not seen as the This greater testing throughout 2020 may explain why third-freedom-category countries reported more cases on average during this time, but less deaths than second-freedom-category countries.Throughout the pandemic, average case and death curves for each freedom class show that the highest freedom category exhibited higher case and death counts on average than its lower category counterparts (Figure 1).

Additional effects of freedoms on COVID-19
Not

Population density, freedoms, and COVID-19
A strong association between freedoms and population density was also discovered, with highestfreedom-category countries reporting an average population density of 699 people/mile 2 , as opposed to the average population density value of 158 people/mile 2 in lowest-freedom-category countries (Table 4).Overall, it is clear that social and economic freedoms had both direct and indirect effects on the COVID-19 pandemic, with more pre-existing freedoms generally relating to a higher impact from COVID-19.Higher GDP and higher population density, both associated with more freedoms, were also seemingly associated with higher COVID-19 case counts and death counts, but comparatively low fatality rates.Capitalism and democracy, following the same freedom trends as above, also appeared to have been related to higher COVID-19 pandemic severity.Lastly, GDP and social and economic freedoms do not seem to be accelerating the vaccine distribution process, although it may be too early to tell.

Conclusions
In conclusion, countries with the highest economic pandemic continued in 2020.For instance, the thirdfreedom-category tested the most in the Fall of 2020, with 4.3 million tests/country on average, as opposed to 4.0 million in the first-freedom-category and 1.7 million in the second-freedom category.

Figure 1 :
Figure 1: COVID-19 Case and Death Curves Based on Freedoms.The number of days after March 1, 2020, were plotted on the x-axis, and, per the overall social and economic freedom classes, average COVID-19 cases and deaths were plotted on the y-axis.The color purple denotes the highest overall social and economic freedom class, red the second-highest, green the second-lowest, and blue the lowest.

Figure 2 :
Figure 2: COVID-19 Case and Death Curves Based on Social and Economic Systems.Each graph portrays the number of days after March 1, 2020, plotted on the x-axis and COVID-19 cases or deaths, respectively, plotted on the y-axis.Countries' economic systems were classified as either capitalist (denoted by red) or socialist (denoted by blue) and their social systems as either democracies (denoted by green) or dictatorships (denoted by purple).

Figure 3 :
Figure 3: World Maps of COVID-19 Cases and Deaths, and Social and Economic Freedoms.
Early in the pandemic, the spread of COVID-19 was faster to countries with higher economic freedoms likely due to greater activity in global trade.Similarly, these countries, due to their pre-existing economic freedoms, were less likely to suppress their internal economies and impose restrictions.Due to the frequent coexistence of high social freedoms and high economic freedoms, the populations of these same nations were less accustomed to and, as a result, less likely to follow governmental restrictions, when eventually implemented.Despite high-freedom countries' leniency in their COVID-19 responses, countries in the second-category of freedoms exhibited the most stringent responses to the pandemic, especially in Spring 2020, a discrepancy possibly explained by the direct relationship between freedoms and higher GDP.This relationship yields second-freedom-category countries with the resources necessary to impose restrictions and the relative inclination to do so.In contrast, countries in the lowest economic and social freedom categories may have had the political means to impose restrictions but simply did not have the monetary, human, or scientific resources to do so in an effective way.Furthermore, GDP undoubtedly played a major role in testing, with wealthier nations able to test their populations disproportionately more than poorer countries.Partly as a result of that increased testing, countries with higher GDP were able to confirm far more COVID-19 cases and deaths than lower GDP nations.Despite these increased case counts as a result of testing, countries with higher GDPs exhibited lower COVID-19 fatality rates, possibly due to their ability to more effectively diagnose and treat infected individuals and facilitate better access to healthcare.Strong relationships were also present between types of social and economic systems and the pandemic.Capitalist countries had more COVID-19 cases than socialist nations, most likely due to their economic freedoms and decreased inclination to restrict businesses or their populations.Despite this, socialist countries reported more deaths on average than capitalist countries, most likely due to having less economic freedom and, by extension, less GDP and resources, thus decreasing their ability to treat infected individuals.On average, democracies also reported more COVID-19 cases and deaths than dictatorships, likely due to their greater social freedoms and less political and economic isolation.However, pandemic misinformation and false reporting within dictatorships may have also played a role.Next, analyzing the relationship between economic and social freedoms and population density revealed that more freedoms often accompany higher population density.In turn, higher population density tended to lead to more COVID-19 cases and deaths, with a few exceptions.As explained earlier, these exceptions are potentially an effect of datapoint outliers, with high population density countries having lower net populations due to their smaller size (e.g.small European nations), and therefore less people to infect.On the other hand, large countries with urban centers leading to mass viral spread may have been classified as low density due to large swaths of sparsely populated land in other areas of the country (such as in the United States).Thus, only by removing the highest and lowest density classes does the trend of greater population density increasing COVID-19 cases and deaths reveal itself.Fatality rate increasing as population density decreased could be a result of reduced access to healthcare in more rural areas.Interestingly, high GDP category countries were shown to have the lowest average vaccine distribution scores, possibly as a result of greater populations and larger land-areas increasing logistical difficulties for distribution.Similarly, social and economic freedoms do not appear to be strong vaccination distribution success indicators other than lowest-freedom category nations having the worst distribution, most likely as a result of limited resources, as previously noted.However, as of the writing of this report, COVID-19 vaccines have not been available for a long enough period of time for appropriate assessments in many nations.These analyses of the effects of social and economic freedoms on the COVID-19 pandemic have several limitations.First, it should be conceded that an innumerable number of factors certainly influenced the COVID-19 pandemic in each individual nation, many of which were not analyzed in this study, while other variables could have been better controlled in the analyses (e.g.population).Another major limitation was that this article focused exclusively on revealing trends in the data, not necessarily explaining the causal relationship in these trends beyond speculation.Obviously, an immense variety of other factors could have also influenced the relationships J Psychiatry Psychiatric Disord 2021; 5 (6): 172-188 DOI: 10.26502/jppd.2572-519X0143Journal of Psychiatry and Psychiatric Disorders 187 found, including the susceptibility of certain populations to the virus, as well as access to healthcare, which clearly cannot be fully explained through the factors examined.Finally, it should also be noted that certain countries represented significant exceptions to the above trends, most notably China and the United States, possibly confounding some analyses.
and social freedoms were associated with increased numbers of COVID-19 cases and deaths throughout 2020.In addition, increased economic freedoms were associated with a more rapid speed of initial COVID-19 spread, and increased pre-existing social and economic freedoms were associated with less severe governmental restrictions due to the virus.With these relationships now determined, additional analyses should address the underlying question of how the enjoyment of freedoms can be balanced with the preservation of the population's safety to improve responses to future global pandemics or other catastrophes.

Table 1 :
Economic and Social Freedoms and the COVID-19 Pandemic.*

26502/jppd.2572-519X0143 Journal of Psychiatry and Psychiatric Disorders 179
controls.Despite this relationship between higher freedoms, decreased government response, and increased COVID-19 case counts, higher overall DOI: 10.*Category 1 represents greatest freedoms with descending freedoms to Category 4 representing the lowest level of freedom.**Gross Domestic Product in 2019.***Average COVID-19 fatality rate represents the sum of all of the fatality rates of the countries in a class divided by the number of countries in that class.Total fatality rate is defined as total COVID-19 deaths in all of the countries in a category divided by total COVID-19 cases in all of the countries in a category.

Table 3 :
The COVID-19 Pandemic by Economic and Governmental Systems.
*Category 1 represents highest GDP countries while Category 4 represents the lowest GDP countries.**Gross Domestic Product in 2019.

Table 5 :
Economic and Social Freedoms, Gross Domestic Product, and Vaccine Distribution Per Capita.* DOI: