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Figure S1. Relation Between Human Development Index and COVID-19 Deaths Per Million (Log)

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Figure S1. Relation Between Human Development Index and COVID-19 Deaths Per Million (Log) Figure S1. Relation between Human Development Index and COVID-19 deaths per million (log). BCG policy: current vaccination (dark blue), interrupted vaccination (blue), and never im- plemented BCG vaccination program (light blue). United States analyzed as states. Table S1 contains the summary of results between confounding variables and COVID-19 mortality. www.pnas.org/cgi/doi/10.1073/pnas.2008410117 Figure S2. BCG vaccination policies by world region. Percentage of countries by region in terms of their BCG policy: current vaccination (dark blue), interrupted vaccination (blue), and never implemented BCG vaccination program (light blue). North Ame=North America; Latin Ame=Latin America; M East & N-Afr=Middle East and North Africa; SubS-Afr=Sub Sahara Africa; Europe & Asia-C=Europe and Asia Central; S-Asia=South Asia; E-Asia=East Asia. United States analyzed as a country. Figure S3. Histogram o BCG vaccination policies and COVID-19. BCG policy denoting current vaccination (dark blue), interrupted vaccination (blue), and never implemented BCG vaccination program (light blue) and (log) total deaths per country per 1 M inhabitants. United States analyzed as a country. Figure S4. Multivariate model of COVID-19 mortality. We developed multiple linear regression models using (log) COVID-19 deaths accumulated during the first month of reported mortalities for all countries as dependent variable and the potential confounding variables and BCG data as the predictor variables. Statistic diagnostic metrics were used to determine the best variable combination and select the optimal model for COVID-19 death estimation. The regression model diagnostic procedure included the adjusted Bayesian information criterion (BIC) which measures model error adjusted by number of variables; adjusted r2, which measures the proportion of vari- ation in the dependent variable that is explained by the predictor variables adjusted by number of variables; and the Mallow’s Cp, which measures model error accounting for sample size, and number and collinearity of predictors. A. The adjusted r2 evaluation found that the best model should include two variables, population density and HDI (square). B. The BIC evaluation found HDI as the best variable for the model (square). C. The Mallow’s Cp evaluation also found that the best model should include density and HDI (square). D. Correlogram denoting high (narrow ellipsoid) or none (broad ellipsoid and yellow color) correlation. All correlations were positive (el- lipsoid direction to the right and blue color). The best variable combination was HDI and popula- tion density, which significantly predicted COVID-19 deaths/country/first month of mortality (r2=0.49, F(2,113)=55.57, p<0.001). HDI: Human Development Index; Pop Dens: Population den- sity; Urban %: Percentage urbanization; >65 yr: Population above >65 yrs (%); BCG %: Percent- age of population vaccinated annually using BCG; BCG Range: Number of years of BCG vac- cination program; BCG Index: Combination of percentage of population vaccinated annually us- ing BCG and number of years of BCG vaccination program by country. Supplementary Table S1. Correlation analyses between social variables and COVID-19 mortality. Analyses included the United States as a single country (Coarse analysis (United States as a Country)) and by state (Coarse analysis (United States as states)), because some of its states are larger than many European, Asian, and Latin American countries. Anal- yses were conducted globally before and after controlling for confounding variables (Refined analysis (Controlling Confounding Variables)). Mortality values are based on original num- bers by country and corrected by the country’s population and by the time of the epidemic to al- low standardized evaluations. Significant analysis (p<0.05) are denoted in red. DF= degrees of freedom, R2= correlation coefficient, AIC=Akaike’s information criteria. Note that association de- creases considerably after accounting for controlling variables. Pop Dens: Population Density (inhabitants/km2); Urban (%): Percentage of population in urban areas; HDI: Human Develop- ment Index; >65 years: Percentage of population that is >65 year-old. Independent Vari- P- Dependent Variable DF R2 AIC able Value Coarse analysis (United States as states) Deaths/1 M (Total) Pop Dens 1 0.001 0.588 2914.320 Days to 0.1 Death/1 M Pop Dens 1 0.001 0.625 1279.182 Days to 1 Death/1 M Pop Dens 1 0.007 0.304 1206.722 Deaths/day/1 M (mean) Pop Dens 1 0.004 0.385 1056.207 Deaths/day/1 M (median) Pop Dens 1 0.000 0.939 915.769 Deaths/day/1 M (max) Pop Dens 1 0.029 0.015 1764.574 Deaths/1 M/week 3 (Total) Pop Dens 1 0.012 0.142 1756.090 Deaths/1 M/week 3 (median) Pop Dens 1 0.000 0.929 787.638 Deaths/1 M/week 3 (mean) Pop Dens 1 0.012 0.142 1063.340 Deaths/1 M/week 3 (max) Pop Dens 1 0.060 0.001 1451.154 Deaths/1 M/month 1 (Total) Pop Dens 1 0.002 0.596 1499.382 Deaths/1 M/month 1 (median) Pop Dens 1 0.001 0.735 511.885 Deaths/1 M/month 1 (mean) Pop Dens 1 0.002 0.597 655.847 Deaths/1 M/month 1 (max) Pop Dens 1 0.003 0.526 1075.932 Deaths/1 M log (Total) Pop Dens 1 0.005 0.311 898.985 Deaths/day/1 M log (mean) Pop Dens 1 0.007 0.249 872.667 Deaths/day/1 M log (median) Pop Dens 1 0.006 0.402 472.296 Deaths/day/1 M log (max) Pop Dens 1 0.016 0.073 836.233 Deaths/1 M/week 3 log (Total) Pop Dens 1 0.012 0.176 678.003 Deaths/1 M/week 3 log (median) Pop Dens 1 0.009 0.313 456.243 Deaths/1 M/week 3 log (mean) Pop Dens 1 0.012 0.177 676.995 Deaths/1 M/week 3 log (max) Pop Dens 1 0.026 0.043 646.020 Deaths/1 M/month 1 log (Total) Pop Dens 1 0.001 0.788 532.055 Deaths/1 M/month 1 log (median) Pop Dens 1 0.010 0.348 368.584 Deaths/1 M/month 1 log (mean) Pop Dens 1 0.001 0.780 531.682 Deaths/1 M/month 1 log (max) Pop Dens 1 0.000 0.831 507.402 Deaths/1 M (Total) Urban (%) 1 0.099 0.000 2925.364 Days to 0.1 Death/1 M Urban (%) 1 0.074 0.000 1309.837 Days to 1 Death/1 M Urban (%) 1 0.000 0.783 1200.273 Deaths/day/1 M (mean) Urban (%) 1 0.099 0.000 1040.405 Deaths/day/1 M (median) Urban (%) 1 0.076 0.000 903.314 Deaths/day/1 M (max) Urban (%) 1 0.070 0.000 1763.694 Deaths/1 M/week 3 (Total) Urban (%) 1 0.065 0.001 1764.073 Deaths/1 M/week 3 (median) Urban (%) 1 0.067 0.000 782.223 Deaths/1 M/week 3 (mean) Urban (%) 1 0.065 0.001 1063.541 Deaths/1 M/week 3 (max) Urban (%) 1 0.054 0.002 1466.704 Deaths/1 M/month 1 (Total) Urban (%) 1 0.104 0.000 1508.242 Deaths/1 M/month 1 (median) Urban (%) 1 0.065 0.004 510.036 Deaths/1 M/month 1 (mean) Urban (%) 1 0.104 0.000 651.121 Deaths/1 M/month 1 (max) Urban (%) 1 0.088 0.001 1080.245 Deaths/1 M log (Total) Urban (%) 1 0.254 0.000 847.856 Deaths/day/1 M log (mean) Urban (%) 1 0.231 0.000 829.093 Deaths/day/1 M log (median) Urban (%) 1 0.153 0.000 453.241 Deaths/day/1 M log (max) Urban (%) 1 0.218 0.000 795.271 Deaths/1 M/week 3 log (Total) Urban (%) 1 0.238 0.000 652.232 Deaths/1 M/week 3 log (median) Urban (%) 1 0.194 0.000 432.300 Deaths/1 M/week 3 log (mean) Urban (%) 1 0.238 0.000 651.372 Deaths/1 M/week 3 log (max) Urban (%) 1 0.231 0.000 621.102 Deaths/1 M/month 1 log (Total) Urban (%) 1 0.248 0.000 515.794 Deaths/1 M/month 1 log (median) Urban (%) 1 0.211 0.000 347.252 Deaths/1 M/month 1 log (mean) Urban (%) 1 0.246 0.000 515.835 Deaths/1 M/month 1 log (max) Urban (%) 1 0.250 0.000 487.056 Deaths/1 M (Total) HDI 1 0.123 0.000 2659.118 Days to 0.1 Death/1 M HDI 1 0.117 0.000 1212.673 Days to 1 Death/1 M HDI 1 0.082 0.000 1124.599 Deaths/day/1 M (mean) HDI 1 0.125 0.000 921.263 Deaths/day/1 M (median) HDI 1 0.101 0.000 844.645 Deaths/day/1 M (max) HDI 1 0.095 0.000 1537.169 Deaths/1 M/week 3 (Total) HDI 1 0.108 0.000 1423.723 Deaths/1 M/week 3 (median) HDI 1 0.107 0.000 729.857 Deaths/1 M/week 3 (mean) HDI 1 0.108 0.000 773.760 Deaths/1 M/week 3 (max) HDI 1 0.108 0.000 1005.717 Deaths/1 M/month 1 (Total) HDI 1 0.114 0.000 1342.062 Deaths/1 M/month 1 (median) HDI 1 0.080 0.002 479.930 Deaths/1 M/month 1 (mean) HDI 1 0.114 0.000 546.087 Deaths/1 M/month 1 (max) HDI 1 0.134 0.000 854.510 Deaths/1 M log (Total) HDI 1 0.623 0.000 649.287 Deaths/day/1 M log (mean) HDI 1 0.606 0.000 637.164 Deaths/day/1 M log (median) HDI 1 0.434 0.000 381.678 Deaths/day/1 M log (max) HDI 1 0.546 0.000 626.506 Deaths/1 M/week 3 log (Total) HDI 1 0.505 0.000 527.312 Deaths/1 M/week 3 log (median) HDI 1 0.514 0.000 344.079 Deaths/1 M/week 3 log (mean) HDI 1 0.511 0.000 524.324 Deaths/1 M/week 3 log (max) HDI 1 0.485 0.000 499.179 Deaths/1 M/month 1 log (Total) HDI 1 0.538 0.000 422.392 Deaths/1 M/month 1 log (median) HDI 1 0.503 0.000 284.851 Deaths/1 M/month 1 log (mean) HDI 1 0.543 0.000 420.793 Deaths/1 M/month 1 log (max) HDI 1 0.535 0.000 393.861 Deaths/1 M (Total) >65 yrs 1 0.128 0.000 2708.633 Days to 0.1 Death/1 M >65 yrs 1 0.046 0.003 1280.570 Days to 1 Death/1 M >65 yrs 1 0.028 0.036 1150.943 Deaths/day/1 M (mean) >65 yrs 1 0.109 0.000 935.356 Deaths/day/1 M (median) >65 yrs 1 0.106 0.000 846.402 Deaths/day/1 M (max) >65 yrs 1 0.060 0.001 1596.830 Deaths/1 M/week 3 (Total) >65 yrs 1 0.089 0.000 1444.094 Deaths/1 M/week 3 (median) >65 yrs 1 0.083 0.000 728.648 Deaths/1 M/week 3 (mean) >65 yrs 1 0.089 0.000 763.002 Deaths/1 M/week 3 (max) >65 yrs 1 0.099 0.000 983.317 Deaths/1 M/month 1 (Total) >65 yrs 1 0.072 0.003 1370.980 Deaths/1 M/month 1 (median) >65 yrs 1 0.054 0.010 449.527 Deaths/1 M/month 1 (mean) >65 yrs 1 0.072 0.003 534.213 Deaths/1 M/month 1 (max) >65 yrs 1 0.068 0.003 875.041 Deaths/1 M log (Total) >65 yrs 1 0.520 0.000 731.014 Deaths/day/1 M log (mean) >65 yrs 1 0.496 0.000 714.728 Deaths/day/1 M log (median)
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