Table 3.
Direct and total effects of variables on COVID infection rate (N = 3,140).
| Structural model |
Unstandardized coefficient |
Standardized coefficient |
||
|---|---|---|---|---|
| Direct effect | Total effect | Direct effect | Total effect | |
| Outcome: COVID-19 infection rate | ||||
| Predictors | ||||
| Human mobility | 20.116*** | 18.191*** | 0.273*** | 0.246*** |
| Socio-demographic characteristics | ||||
| Age 18–24 years | 6.388*** | 1.060 | 0.090*** | 0.015 |
| Age 25–44 years | 16.377*** | 5.752*** | 0.220*** | 0.077*** |
| Age 45–64 years | −1.437 | −3.358* | −0.017 | −0.039* |
| Age 65 years and older | −4.117** | −7.411*** | −0.078** | −0.141*** |
| African-Americans | 1.936*** | 2.275*** | 0.115*** | 0.135*** |
| Male | −13.115*** | −4.604** | −0.128*** | −0.045** |
| People in labor force | --- | 1.408*** | --- | 0.035*** |
| HH with internet access | --- | −1.607*** | --- | −0.058*** |
| Location characteristics | ||||
| Number of points of interest | --- | −0.002*** | --- | −0.039*** |
| Presence of airport | --- | −0.266*** | --- | −0.039*** |
| Metropolitan status | 0.500*** | 0.332*** | 0.099*** | 0.066*** |
| COVID-19 status | ||||
| a Susceptible Infected (SI) | 0.0003*** | 0.0002*** | 0.150*** | 0.136*** |
| b Spatial effect | 0.051*** | 0.046** | 0.314*** | 0.284** |
| COVID-19 policies | ||||
| Emergency declaration | --- | −1.406*** | --- | −0.017*** |
| Gathering restriction | --- | −0.029*** | --- | −0.002*** |
| Stay at home order | 2.942*** | 1.856*** | 0.198*** | 0.125*** |
| Non-essential business closure | --- | −0.606** | --- | −0.013** |
| Public mask mandate | −0.477* | −0.431* | −0.037* | −0.034* |
| Quarantine mandate | 0.145 | 0.132 | 0.013 | 0.012 |
Notes: --- denotes no direct connections. *, **, and *** indicate statistical significance at 10%, 5%, and 1% respectively.
All the COVID-19 policy variables represent the number of days from the first enactment of policies until May 1, 2020
a
Susceptible Infected (SI) = number of susceptible people (people who have not been infected with the virus yet) × number of currently infected people in that population (current active cases).
b
Spatial effect = number of average COVID-19 daily new cases per 100 K population in neighboring counties × average number of daily external trips by infectious persons from out of state or county (Imported cases)