Economic and social factors affecting the epidemiological process of the SARS-CoV-2 coronavirus

Abstract

Summary
 Aim. Analyze the impact of several economic and social factors on the course of the COVID-19 pandemic, comparing the latest statistics in large and representative samples. Assess the factors inhibiting the negative consequences of the infectious process of the SARS-CoV-2 virus.
 
 Materials and methods. To create this review, the required academic and media publications also statistical data were found on the Internet for the selected keywords, both for a single tag and in various combinations of them. Population statistics have been created on the base of data available on the Internet.
 
 Results and discussion. The relationship between economic or social factors and the impacts of the 15-month COVID-19 pandemic in different regions was investigated using a variety of available statistics for five continents and 53 countries. A positive relationship was found between the consequences of the SARS-CoV-2 epidemic and GDP per capita or the type of human diet with correlation coefficients in the range of 0.48-0.87. The development of the viral epidemic demonstrates a less clear correlation on population density from r = -0.68 to r = -0.16, depending on the selected group of countries. For island nations, geographic isolation was the dominant defense against SARS-CoV-2 infection.
 
 Conclusions. An analytical and quantitative study of economic or social aspects and numerous statistics on the spread of the COVID-19 pandemic, carried out on large representative samples, showed that, the productive infection and pathogenicity of SARS-CoV-2, critically increase with an excessive amount of consumed proteins and fats. To successfully control of the progression COVID-19 disease, the WHO guidelines for the amount of macronutrients consumed should be followed. This cost-effective approach will reduce health care expenditures in all countries during the epidemic.

The development and outcomes of the COVID-19 disease correlate with the type of nutrition

“…A similar trend was found in statistical populations of continents [28]. Africa is characterized by a low standard of living: GDP is 32 times, consumption of highcalorie foods is 2.2 times, protein intake is 1.6 times lower than in NA [6,30-31], and the infection rate was 18 times, and the level of mortality rate was 22 times lower [6,15,28]. This difference for NA and Asia was less contrasting (Fig.…”

“…The elevated mortality rate among high incomed patients suffering from COVID-19 has been unexpectedly recognized [12,29]. A similar trend was found in statistical populations of continents [28]. Africa is characterized by a low standard of living: GDP is 32 times, consumption of highcalorie foods is 2.2 times, protein intake is 1.6 times lower than in NA [6,30-31], and the infection rate was 18 times, and the level of mortality rate was 22 times lower [6,15,28].…”

“…This difference for NA and Asia was less contrasting (Fig. 1), but also significant; accordingly, the infection fatality rate (IFR) and rate of prevalence (RPr) were several times lower in Asia, than in NA [28]. The influence of socio-economic factors on the pathogenesis of the virus was investigated and it was shown that the level of consumption of fats and total protein can be a reliable factor influencing the pathogenesis of the SARS-CoV-2 virus [28].…”

“…These data may differ by a factor of a hundred or a thousand, which is why some publications question the fact that statistical information on epidemiological processes from different countries was absolutely reliable [25]. Despite the opinion that the analysis of a large database has its drawbacks, which are especially evident with a heterogeneous sample [26], for greater reliability, the influence of socio-economic factors on the course and outcomes of the SARS-CoV-2 coronavirus was analyzed using a large number of representative statistics and a long study period [27][28][29].…”

“…Decisions about the course of each epidemic are based on an analysis of statistics on circulating infection in the population over the time period described. Epidemiologists, infectious disease specialists, clinicians and other experts analyze primarily the risks of an epidemic (pandemic) and their factors [5,[8][9][10][11][12][13][14][15][16][17][27][28][29]. The following available sources differentiate or assess risk factors for severity or mortality from COVID-19 [5,7].…”