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. 2021 Jan 9;124:102955. doi: 10.1016/j.trc.2020.102955

Table 1.

Summary of Dependent and Independent Variables Used in the Models (From February 1st, 2020 to May 31st, 2020).

Variables Description Mean SD Min. Max.
Dependent Variables
Δ Trip per person Daily average number of trips per person compared with January 2020 (Mean: 3.326 SD:0.466) −0.209 0.405 −1.264 0.798
Δ Person-miles traveled Daily average person-miles traveled compared with January 2020 (Mean: 42.952 SD:10.572) −5.686 9.715 –32.060 31.399
Δ Proportion of staying home Daily average proportion of residents staying at home compared with January 2020 (Mean: 0.199 SD:0.055) 0.048 0.062 −0.088 0.229
Independent Variables
Policy Stay-at-home order Categorical Variables. 0: No Stay-at-home order (Reference); 1: Stay-at-home order issued without penalty or specifying enforcement (32.54%); 2: Stay-at-home order issued and enforced with a warning, and a possible fine for the repeated offense (29.35%); 3: Stay-at-home order issued and enforced with fines and possible jail time (28.55%). 0.000 3.000

FEMA If COVID-19 Emergency Declaration issued, 1; else 0. 0.277 0.448 0.000 1.000
Reopening order If (partial) reopening order is issued, 1; else 0 (Reference). 0.218 0.413 0.000 1.000
ARG If the Guideline for Opening Up America Again issued, 1; else 0. 0.361 0.480 0.000 1.000
COVID-19 New cases Daily number of newly confirmed COVID-19 cases in the county (1,000). 0.003 0.025 0.000 2.155
Sum cases Daily number of accumulated confirmed COVID-19 cases in the county (1,000). 0.127 1.154 0.000 77.925
Adj. new cases Daily number of newly confirmed COVID-19 cases in the adjacent counties (1,000). 0.020 0.089 0.000 4.462
Adj. sum cases Daily number of accumulated confirmed COVID-19 cases in adjacent counties (1,000). 0.803 4.878 0.000 200.167
National new cases Daily number of newly confirmed COVID-19 cases in the nation (1,000). 14.551 12.859 0.000 36.590
Temporal Week The day of the week, from 0 (Monday) to 6 (Sunday). 0.000 6.000
Weekend If the day is weekend, 1; else 0 (Reference). 0.290 0.454 0.000 1.000
Time Index The difference in the day from the current date to February 1st, 2020. 0.000 120.000
Socio-Demographic Population density Population density, in 103 persons/sq. mile. 0.233 0.945 0.000 25.591
Employment density Job density, in 103 jobs/sq. mile. 0.125 1.319 0.000 67.846
Male The proportion of males. 0.500 0.023 0.421 0.790
Age_0_24 The proportion of people aged between 0 and 24. 0.312 0.047 0.105 0.612
Age_25_40 The proportion of people aged between 25 and 40. 0.176 0.029 0.067 0.346
Age_40_65 The proportion of people aged between 40 and 65. 0.328 0.030 0.149 0.499
Race-White The proportion of White not Hispanic or Latino. 0.767 0.198 0.007 1.000
Race-Hispanics The proportion of White Hispanic or Latino. 0.066 0.112 0.000 0.944
Race-African American The proportion of African American. 0.093 0.147 0.000 0.874
Race-Asian The proportion of Asian. 0.013 0.023 0.000 0.359
Median income The median household income, in $103/household. 51.402 13.605 20.188 136.268
Army personnel The proportion of people in armed forces. 0.003 0.016 0.000 0.520
College students The proportion of residents enrolled in college or graduate school. 0.050 0.039 0.000 0.536
Incarcerated ratio The proportion of population incarcerated. 0.004 0.008 0.000 0.167
Political parties Democrats The proportion of Democrats in presidential candidate vote totals. 0.316 0.151 0.031 0.909
Republicans The proportion of Republicans in presidential candidate vote totals. 0.632 0.155 0.041 0.946
Non-voters The proportion of non-voters. 0.557 0.077 0.208 0.871
Industry (weighted by number of employees in each establishment) Agriculture The proportion of agriculture, forestry, fishing, hunting, mining, quarrying, oil and gas extraction, and construction sectors. 0.090 0.075 0.000 1.000
Retail The proportion of retail trade and wholesale trade sectors. 0.256 0.104 0.000 1.000
Educational The proportion of educational, professional, scientific, and technical services. 0.045 0.037 0.000 0.486
Finance The proportion of finance and insurance services. 0.053 0.031 0.000 0.500
Transportation The proportion of transportation and warehousing services. 0.064 0.049 0.000 1.000
Entertainment The proportion of arts, entertainment, and recreation services. 0.009 0.012 0.000 0.277
Accommodation The proportion of food and accommodation services 0.151 0.081 0.000 1.000
Health care The proportion of health care and social assistance services. 0.146 0.088 0.000 1.000
Manufacturing The proportion of manufacturing industry. 0.101 0.110 0.000 0.776
Weather Precipitation Daily precipitation, in mm. 3.363 8.532 0.000 197.900
Max. Temperature Daily maximum temperature, in Celsius. 16.516 8.968 –22.667 222.800
Min. Temperature Daily minimum temperature, in Celsius. 4.437 8.415 −36.700 27.250

a. Italic texts: excluded variables due to multicollinearity.

b. All analyses are based on contiguous United States (i.e. Hawaii and Alaska are excluded) from February 1st, 2020 to May 31st, 2020.

c. To address the low-sampling biases, only counties with at least 1% daily sampling ratio are included in this study.

d. The adjacent counties are calculated based on the queen relationship, i.e., the county share at least one border or one vertex is defined as an adjacent county.

e. Data source:

1. The county-level socio-demographics are obtained from the 2017 American Community Survey (ACS) 5-year estimates. The industry types are from the 2018 Annual Economic Surveys. The incarcerated data are from the Bureau of Justice Statistics (BJS). The 2018 election data are from the MIT election lab (Lab, 2018).

2. The weather conditions are obtained from the US National Weather Service Forecast Office.

3. The county-level policy information are collected from different government announcements (see (Sarah Mervosh, 2020; Yuriria Avila, 2020) for a summary).

4. The virus data are from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (CSSE, 2020).

f. On February 17th, 2020 (Washington's Birthday) and May 25th, 2020 (Memorial Day), abnormal data fluctuations are observed across the nation due to the holiday effects, we fix the outliers with linear interpolation.