Table 4.
Direct and total effects of variables on human mobility (N = 3,140).
| Structural model |
Unstandardized coefficient |
Standardized coefficient |
||
|---|---|---|---|---|
| Direct effect | Total effect | Direct effect | Total effect | |
| Outcome: Human Mobility | ||||
| Predictors | ||||
| COVID-19 infection rate | −0.005*** | −0.005*** | −0.388*** | −0.351*** |
| Socio-demographic Characteristics | ||||
| Age 18–24 years | −0.259*** | −0.265*** | −0.270*** | −0.276*** |
| Age 25–44 years | −0.498*** | −0.528*** | −0.495*** | −0.525*** |
| Age 45–64 years | −0.113*** | −0.095*** | −0.098*** | −0.083*** |
| Age 65 years and older | −0.203*** | −0.164*** | −0.285*** | −0.230*** |
| African-Americans | 0.029*** | 0.017*** | 0.126*** | 0.074*** |
| Male | 0.399*** | 0.423*** | 0.287*** | 0.304*** |
| People in labor force | 0.077*** | 0.070*** | 0.143*** | 0.129*** |
| HH with internet access | −0.088*** | −0.080*** | −0.234*** | −0.212*** |
| Location Characteristics | ||||
| Number of points of interest | −0.0001*** | −0.0001*** | −0.158*** | −0.143*** |
| Presence of airport | −0.015*** | −0.013*** | −0.156*** | −0.141*** |
| Metropolitan status | −0.007*** | −0.008*** | −0.096*** | −0.122*** |
| COVID-19 status | ||||
| a Susceptible Infected | --- | −1.290e-6 | --- | −0.053 |
| b Spatial effect | --- | −0.0002*** | --- | −0.110*** |
| COVID-19 policies | ||||
| Emergency declaration | −0.077*** | −0.070*** | −0.070*** | −0.063*** |
| Gathering restriction | −0.002 | −0.001 | −0.007 | −0.006 |
| Stay at home order | −0.044*** | −0.054*** | −0.220*** | −0.269*** |
| Non-essential business closure | −0.033** | −0.030** | −0.051** | −0.046** |
| Public mask mandate | --- | 0.002* | --- | 0.013* |
| Quarantine mandate | --- | −0.001 | --- | −0.005 |
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).