Coronavirus (COVID-19) Spike in Georgia: An Epidemiologic Study of Data, Modelling, and Policy Implications to Understand the Gender-and RaceSpecific Variations |Biomedgrid

Objective: The purpose of this study was to investigate the gender-and race-specific predictive variations in COVID-19 cases and deaths in Georgia, USA. Methods: The data were extracted from the Georgia Department of Public Health (GDPH). Statistical methods, such as descriptive statistics, Artificial neural networks (ANN), and Bayesian approach, were utilized to analyze the data. Results: More Whites died from COVID-19 than African American/Blacks in Cobb, Hall, Gwinnett, and non-Georgia residents; however, more Blacks died in Dekalb and Fulton counties. The highest posterior mean for female deaths was obtained in Gwinnett County (77.17; 95% CI, 74.23–80.07) and for male deaths in Fulton County (73.48; 95% CI, 72.18–74.49). For overall race/ethnicity, Whites had the highest posterior mean for deaths (183.18; 95% CI, 128.29–238.27) compared with Blacks (162.48; 95% CI, 127.15– 197.42). Assessing the classification of the chronic medical conditions using ANN, Cobb and Hall Counties showed the highest mean AUC-ROC of the models (78% and 79%, respectively).