Ethnics and economics in COVID-19: Meta-regression of data from countries in the New York metropolitan area

Ethnics and economics may affect prevalence and case fatality of Coronavirus disease 2019 (COVID-19). To determine whether COVID-19 prevalence and fatality are modulated by ethnics and economics, meta-regression of data from the countries in the New York metropolitan area were herein conducted. We selected 31 countries in the New York metropolitan area. 1) Prevalence and case-fatality rates of confirmed COVID-19 cases on May 20, 2020 and 2) income and poverty estimates were obtained in each country. We performed random-effects meta-regression using OpenMetaAnalys. The covariates included 1) black (%), 2) Hispanic or Latino (%), 3) poverty rates (%), and 4) median household income ($). Statistically significant (P < .05) covariates in the univariable model were together entered into the multivariable model. A slope (coefficient) of the univariable meta-regression line for COVID-19 prevalence was not significant for household income (P = .639), whereas the coefficient was significantly positive for black (coefficient, 0.021; P = .015), Hispanic/Latino (0.033; P < .001), and poverty (0.039; P = .02), which indicated that COVID-19 prevalence increased significantly as black, Hispanic/Latino, and poverty increased. The multivariable model revealed that the slope was significantly positive for only Hispanic/Latino (P < .001). The coefficient in the univariable model for COVID-19 fatality, however, was not significant for all the covariate. In conclusion, black, Hispanic/Latino, and poverty (not household income), especially Hispanic/Latino independently, may be associated with COVID-19 prevalence. There may be no association of black, Hispanic/Latino, poverty, and household income with COVID-19 fatality.