Table 2.

Correlation results (Pearson correlation coefficient) between county-level SES and demographic variables and the indicator score for three dimensions of COVID risk perception (number of counties N = 1032)

Variable	Perceived susceptibility	Perceived severity	Negative emotion
GINI coefficient	−0.0069	−0.0906**	−0.0404
Median household income	0.0551	0.0941**	−0.0169
Percentage of being unemployed	−0.0362	−0.0233	0.0110
Percentage of no health insurance	−0.2040**	−0.1574**	−0.0707*
Percentage of living in poverty	−0.0860**	−0.1798**	−0.0335
Percentage of less high school	−0.1844**	−0.1727**	−0.0411
Percentage of African American	−0.1765**	−0.2002**	−0.2051**
Percentage of White	0.1570**	0.1428**	0.1809**
Percentage of Hispanic/Latino	−0.1240**	−0.0643*	0.0001
Percentage of Asian	0.0238	0.0236	−0.0117
Population density	0.0008	0.0130	−0.0129

Note: Only counties with more than 100 Twitter users who posted COVID-19 related tweets were selected, yielding 1,032 counties being included in the statistical analysis. The distribution of urbanization status of these counties was illustrated (Appendix Figure 1) and compared with the national level distribution in 2019 (Appendix Table 3).

^*p < 0.05

^**p < 0.01