Relationships of total COVID-19 cases and deaths with ten demographic, economic and social indicators

Abstract

AbstractWe have used data for 45 countries with a population of over 30 millions in which 85.8% of the world’s population lives. The statistical relationships of total COVID-19 Cases and Deaths per million populations in these countries with 10 demographic, economic and social indicators (indices) were studied. These indicators are Life Expectancy, Median Age, Growth Rate, Population Density, GDP PPP per capita, Human Development Index (HDI), Gini index of income equality, Intelligence Quotient (IQ), Corruption Perceptions Index (CPI) and Democracy Index. Statistically significant relationships were found with all indicators excluding Gini index and Population Density. We have found that the closest is the relationship of Deaths per million population and total Cases per million population with correlation coefficient R = 0.926. Therefore, it is clear statistically that the more are Cases per million in a country the more are Deaths per million. This confirms the correctness of the timely and effective introduction of the necessary pandemic restrictions in the countries.It is interesting that the close correlations were found of Cases and Deaths per 1 million with a purely economic index like GDP PPP per capita, where R = 0.687 and R = 0.660, respectively. Even more close correlations were found of Cases and Deaths per 1 million with a composite index HDI, where the correlation coefficients reach 0.724 and 0.680, respectively. This paradoxical results show that the richest and well-being countries are most seriously affected by the COVID-19 pandemic. The most probable reason for this is the large percentage of aging population, comorbidity of population with severe chronic diseases and obesity in countries with high GDP and HDI. No less important reason appears the delayed and/or insufficiently effective pandemic restrictions in these countries, which have underestimated the danger of a pandemic in early stage.Other indicators (excluding Gini index and Population Density) also show statistically significant correlations with Cases and Deaths per 1 million with correlation coefficients from 0.432 to 0.634. The countries that deviates the most from the regression lines were shown. Surprisingly, there was no statistically significant correlation between Cases and Deaths with Population Density. The statistical significance of the found correlations determined using Student’s t-test was p < 0.0001. The countries that deviate the most from both sides of the regression line were shown. It has been shown that the correlations of COVID-19 cases and Deaths with the studied indicators decrease with time.