Despite successful large laboratory studies, the progression of novel coronavirus disease 2019 (COVID-19) is still underway. As with a short time, COVID-19 escalated into a 'global pandemic', emphasized a special attention for ‘global data analysis’. Using a large global dataset (n=166), we demonstrate that COVID-19 distribution remained particularly unequal across the world's four income groups and global percentage of infectivity including deaths fairly suppressed from high (18.44% e.g. Estonia- 2385 deaths), upper middle (4.44% e.g. Mauritius- 934 deaths), lower middle (2.64% e.g. Timor Leste- 129 deaths) to low-income countries (0.23% e.g. Burundi- 38 deaths). All above reported 4 countries have almost similar population (1.2M-1.3M). Both deaths and infectivity differences between high and upper middle, or upper middle and lower middle, or lower middle and low provides fair visibility in unbiased analyses. Nonetheless, a significant linear relationship (r= 0.72 ± 0.02) over a long 18 months between GDP and COVID-19 infection by country entails risk of contracting COVID-19 (Mar 2020: t-test one-tail/two-tail p < 0.05, F-test one-tail p< 0.05, df= 165, F= 449.03, r2= 0.732, r2 aj= 0.731 and SS=63867700637). Our finding connects health areas that shape unequal distribution of COVID-19 through the resident functional alleles, for example HLA-A*01:01 and HLA-B*46:01 alleles for increased risk in high income countries. The evidence-based views laid foundation for unusual heterogenic immune responses among different human habitats. The ancient evolution theory by natural selection also underlies high susceptibility in high-income countries, due to no adaptive challenges for the lives and improved living standards over the years.