Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries
Abstract
:1. Introduction
2. Literature Review
3. Model Specification and Data Sources
3.1. Model Specification
3.1.1. Causal Model and Its Structural Equation Form
- (1)
- Confounding factors Wc,t influence information variables Ic,t, government epidemic prevention policies Pc,t, human mobility behaviors Bc,t, and anti-epidemic outcomes Hc,t+l, as shown by the four purple directed lines in Figure 1.
- (2)
- Information variables Ic,t influence government epidemic prevention policies Pc,t, human mobility behaviors Bc,t, and anti-epidemic outcomes Hc,t+l, as shown by the three yellow directed lines in Figure 1.
- (3)
- As shown by the two green directed lines in Figure 1. Government epidemic prevention policies Pc,t not only directly affects human mobility behaviors Bc,t and anti-epidemic outcomes Hc,t+l, but also indirectly affects anti-epidemic outcomes through behavioral variables.
- (4)
- Human mobility behaviors Bc,t have a direct effect on the anti-epidemic outcomes Hc,t+l, as shown by the brown directed line in Figure 1.
3.1.2. SIRDS Epidemic Model
3.1.3. Counterfactual Policy Analysis
3.2. Data Source
4. Empirical Analysis
4.1. The Effect of Policies and Information on Behaviors
4.2. The Direct Effect of Policies, Behaviors, and Information on Cases and Deaths Growth
4.3. The Total Effect of Policies and Information on Cases and Deaths Growth When Causal Pathways Are Not Considered
4.4. The Direct, Indirect, and Total Effects of Government Epidemic Prevention Policies and Information on Anti-Epidemic Outcomes
5. Sensitivity Analysis
5.1. Excluding Special Samples and Changing Variables
- (1)
- Baseline model.
- (2)
- Exclude the United States from the sample because it was the developed country with the highest cumulative number of confirmed cases.
- (3)
- Exclude India from the sample because it was the developing country with the highest cumulative number of confirmed cases.
- (4)
- Add the democracy index to the regression variables.
- (5)
- Add the human freedom index to the regression variables.
- (6)
- Include all additional controls in (2)–(5).
- (7)
- Use the lagged terms of human behavioral variables as informative variables.
5.2. Changing Time Lag
6. Counterfactual Policy Analysis
6.1. Mandating Facial Coverings
6.2. Mandating Vaccination Policy
6.3. No Close Public Transport Policy
7. Discussion
8. Conclusions and Policy Implications
8.1. Conclusions
8.2. Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Country | Country | Country | Country |
---|---|---|---|
Angola | Fiji | Mali | Serbia |
Argentina | Finland | Malta | Singapore |
Australia | France | Mexico | Slovakia |
Austria | Gabon | Moldova | Slovenia |
Bahrain | Georgia | Mongolia | South Africa |
Bangladesh | Germany | Morocco | South Korea |
Barbados | Ghana | Mozambique | Spain |
Belarus | Greece | Myanmar | Sri Lanka |
Belgium | Guatemala | Namibia | Sweden |
Belize | Haiti | Nepal | Switzerland |
Benin | Honduras | Netherlands | Tajikistan |
Bolivia | Hungary | New Zealand | Tanzania |
Bosnia and Herzegovina | India | Nicaragua | Thailand |
Botswana | Indonesia | Niger | The Bahamas |
Brazil | Iraq | Nigeria | Togo |
Bulgaria | Ireland | Norway | Trinidad and Tobago |
Burkina Faso | Israel | Oman | Turkey |
Cambodia | Italy | Pakistan | Uganda |
Cameroon | Jamaica | Panama | Ukraine |
Canada | Japan | Papua New Guinea | United Arab Emirates |
Cape Verde | Jordan | Paraguay | United Kingdom |
Chile | Kazakhstan | Peru | United States |
Colombia | Kenya | Philippines | Uruguay |
Costa Rica | Kuwait | Poland | Venezuela |
Croatia | Kyrgyzstan | Portugal | Vietnam |
Czechia | Laos | Qatar | Yemen |
Denmark | Latvia | Romania | Zambia |
Ecuador | Lebanon | Russia | Zimbabwe |
Egypt | Lithuania | Rwanda | |
El Salvador | Luxembourg | Saudi Arabia | |
Estonia | Malaysia | Senegal |
(a) Cases as Information | Workplaces | Retail | Transit | Grocery |
school closing | −0.078 *** | −0.085 *** | −0.074 ** | −0.067 * |
(0.022) | (0.028) | (0.029) | (0.036) | |
cancel public events | 0.005 | −0.024 | −0.025 | −0.023 |
(0.020) | (0.026) | (0.027) | (0.031) | |
restrictions on gatherings | −0.056 *** | −0.045 | −0.051 | −0.040 |
(0.021) | (0.032) | (0.035) | (0.035) | |
close public transport | −0.033 *** | −0.068 *** | −0.053 *** | −0.042 *** |
(0.013) | (0.016) | (0.020) | (0.015) | |
stay at home requirements | −0.050 *** | −0.067 *** | −0.080 *** | −0.045 ** |
(0.010) | (0.016) | (0.024) | (0.018) | |
international travel controls | −0.023 | −0.017 | −0.052 ** | −0.0004 |
(0.024) | (0.029) | (0.024) | (0.027) | |
testing | −0.061 *** | −0.039 | −0.068 ** | −0.042 |
(0.017) | (0.030) | (0.032) | (0.033) | |
contact tracing | 0.031 * | 0.048 ** | −0.003 | 0.041 ** |
(0.018) | (0.020) | (0.022) | (0.019) | |
facial coverings | 0.077 *** | 0.100 *** | 0.095 *** | 0.088 *** |
(0.015) | (0.024) | (0.021) | (0.019) | |
vaccination | 0.011 | 0.002 | −0.016 | 0.020 |
(0.017) | (0.023) | (0.029) | (0.021) | |
dlogdc | 0.015 *** | 0.013 *** | 0.010 *** | 0.003 |
(0.002) | (0.003) | (0.003) | (0.003) | |
logdc | −0.009 *** | −0.014 *** | −0.003 | −0.002 |
(0.003) | (0.003) | (0.004) | (0.003) | |
country variables | YES | YES | YES | YES |
quarter × country variables | YES | YES | YES | YES |
observations | 44,891 | 44,891 | 44,891 | 44,891 |
adjusted R2 | 0.4043 | 0.5179 | 0.4641 | 0.3676 |
(b) Deaths as Information | Workplaces | Retail | Transit | Grocery |
school closing | −0.082 *** | −0.090 *** | −0.074 ** | −0.067 * |
(0.022) | (0.028) | (0.029) | (0.035) | |
cancel public events | 0.003 | −0.025 | −0.021 | −0.022 |
(0.021) | (0.026) | (0.027) | (0.030) | |
restrictions on gatherings | −0.063 *** | −0.054 * | −0.053 | −0.041 |
(0.021) | (0.032) | (0.035) | (0.035) | |
close public transport | −0.033 ** | −0.065 *** | −0.050 ** | −0.042 *** |
(0.013) | (0.016) | (0.020) | (0.015) | |
stay at home requirements | −0.050 *** | −0.063 *** | −0.075 *** | −0.044 ** |
(0.010) | (0.016) | (0.024) | (0.018) | |
international travel controls | −0.033 | −0.028 | −0.058 ** | −0.003 |
(0.025) | (0.030) | (0.025) | (0.027) | |
testing | −0.075 *** | −0.061 ** | −0.071 ** | −0.045 |
(0.017) | (0.028) | (0.031) | (0.032) | |
contact tracing | 0.026 | 0.039 * | −0.005 | 0.039 ** |
(0.018) | (0.020) | (0.021) | (0.019) | |
facial coverings | 0.071 *** | 0.097 *** | 0.093 *** | 0.086 *** |
(0.015) | (0.023) | (0.020) | (0.019) | |
vaccination | 0.007 | 0.006 | −0.015 | 0.019 |
(0.017) | (0.023) | (0.029) | (0.022) | |
dlogdd | −0.0002 | −0.0005 | −0.003 | −0.003 * |
(0.002) | (0.002) | (0.002) | (0.002) | |
logdd | −0.009 *** | −0.015 *** | −0.006 | −0.003 |
(0.002) | (0.003) | (0.004) | (0.003) | |
country variables | YES | YES | YES | YES |
quarter × country variables | YES | YES | YES | YES |
observations | 44,891 | 44,891 | 44,891 | 44,891 |
adjusted R2 | 0.4017 | 0.5247 | 0.4666 | 0.3689 |
(a) Cases | dlogdc | (b) Deaths | dlogdd |
---|---|---|---|
lag(school closing, 14) | −0.233 *** | lag(school closing, 21) | −0.174 *** |
(0.060) | (0.059) | ||
lag(cancel public events, 14) | −0.093 * | lag(cancel public events, 21) | −0.079 * |
(0.048) | (0.048) | ||
lag(restrictions on gatherings, 14) | 0.023 | lag(restrictions on gatherings, 21) | −0.015 |
(0.042) | (0.036) | ||
lag(close public transport, 14) | 0.054 *** | lag(close public transport, 21) | 0.038 * |
(0.019) | (0.021) | ||
lag(stay at home requirements, 14) | 0.037 | lag(stay at home requirements, 21) | 0.023 |
(0.032) | (0.029) | ||
lag(international travel controls, 14) | −0.253 *** | lag(international travel controls, 21) | −0.336 *** |
(0.087) | (0.113) | ||
lag(testing, 14) | −0.235 * | lag(testing, 21) | −0.029 |
(0.139) | (0.106) | ||
lag(contact tracing, 14) | −0.082 * | lag(contact tracing, 21) | −0.027 |
(0.044) | (0.043) | ||
lag(facial coverings, 14) | −0.133 *** | lag(facial coverings, 21) | −0.126 *** |
(0.044) | (0.039) | ||
lag(vaccination, 14) | −0.158 *** | lag(vaccination, 21) | −0.144 *** |
(0.045) | (0.041) | ||
lag(workplaces, 14) | 0.474 *** | lag(workplaces, 21) | 0.399 *** |
(0.140) | (0.125) | ||
lag(retail, 14) | 0.168 | lag(retail, 21) | 0.079 |
(0.152) | (0.123) | ||
lag(transit, 14) | 0.148 | lag(transit, 21) | 0.246 ** |
(0.106) | (0.102) | ||
lag(grocery, 14) | −0.412 *** | lag(grocery, 21) | −0.323 *** |
(0.116) | (0.103) | ||
lag(dlogdc, 14) | 0.048 *** | lag(dlogdd, 21) | 0.050 *** |
(0.017) | (0.012) | ||
lag(logdc, 14) | −0.028 *** | lag(logdd, 21) | −0.021 *** |
(0.006) | (0.004) | ||
dlogtests | 0.019 ** | ||
(0.009) | |||
country variables | YES | country variables | YES |
quarter × country variables | YES | quarter × country variables | YES |
observations | 42,472 | observations | 42,350 |
adjusted R2 | 0.1082 | adjusted R2 | 0.0455 |
(a) Cases | dlogdc | (b) Deaths | dlogdd |
---|---|---|---|
lag(school closing, 14) | −0.268 *** | lag(school closing, 21) | −0.217 *** |
(0.066) | (0.065) | ||
lag(cancel public events, 14) | −0.084 * | lag(cancel public events, 21) | −0.075 |
(0.051) | (0.051) | ||
lag(restrictions on gatherings, 14) | −0.0005 | lag(restrictions on gatherings, 21) | −0.044 |
(0.045) | (0.039) | ||
lag(close public transport, 14) | 0.038 * | lag(close public transport, 21) | 0.023 |
(0.020) | (0.022) | ||
lag(stay at home requirements, 14) | 0.010 | lag(stay at home requirements, 21) | −0.007 |
(0.031) | (0.028) | ||
lag(international travel controls, 14) | −0.271 *** | lag(international travel controls, 21) | −0.362 *** |
(0.093) | (0.119) | ||
lag(testing, 14) | −0.261 * | lag(testing, 21) | −0.066 |
(0.143) | (0.109) | ||
lag(contact tracing, 14) | −0.078 * | lag(contact tracing, 21) | −0.028 |
(0.043) | (0.045) | ||
lag(facial coverings, 14) | −0.115 ** | lag(facial coverings, 21) | −0.111 *** |
(0.046) | (0.040) | ||
lag(vaccination, 14) | −0.171 *** | lag(vaccination, 21) | −0.155 *** |
(0.044) | (0.042) | ||
lag(dlogdc, 14) | 0.057 *** | lag(dlogdd, 21) | 0.052 *** |
(0.017) | (0.012) | ||
lag(logdc, 14) | −0.035 *** | lag(logdd, 21) | −0.026 *** |
(0.006) | (0.004) | ||
dlogtests | 0.019 ** | ||
(0.009) | |||
country variables | YES | country variables | YES |
quarter × country variables | YES | quarter × country variables | YES |
observations | 42,472 | observations | 42,350 |
adjusted R2 | 0.1025 | adjusted R2 | 0.0417 |
(a) Cases | Direct Effect | Indirect Effect | Total Effect | Average | Difference | |
Considering Causal Pathways | Not Considering Causal Pathways | |||||
school closing | −0.233 *** | −0.035 ** | −0.268 *** | −0.268 *** | −0.268 *** | 0.000 |
(0.059) | (0.014) | (0.064) | (0.065) | (0.064) | (0.005) | |
cancel public events | −0.093 * | 0.004 | −0.089 * | −0.084 * | −0.087 * | −0.005 |
(0.048) | (0.012) | (0.051) | (0.051) | (0.051) | (0.005) | |
restrictions on gatherings | 0.023 | −0.025 ** | −0.002 | −0.000 | −0.001 | −0.002 |
(0.042) | (0.012) | (0.045) | (0.045) | (0.045) | (0.005) | |
close public transport | 0.054 *** | −0.018 * | 0.036 * | 0.038 * | 0.037 * | −0.001 |
(0.019) | (0.010) | (0.021) | (0.021) | (0.021) | (0.003) | |
stay at home requirements | 0.037 | −0.028 *** | 0.009 | 0.010 | 0.009 | −0.002 |
(0.032) | (0.009) | (0.030) | (0.030) | (0.030) | (0.003) | |
international travel controls | −0.253 *** | −0.021 | −0.274 *** | −0.271 *** | −0.273 *** | −0.003 |
(0.087) | (0.014) | (0.095) | (0.093) | (0.094) | (0.005) | |
testing | −0.235 * | −0.028 ** | −0.263 * | −0.261 * | −0.262 * | −0.002 |
(0.136) | (0.011) | (0.140) | (0.140) | (0.140) | (0.006) | |
contact tracing | −0.082 * | 0.005 | −0.077 * | −0.078 * | −0.077 * | 0.001 |
(0.043) | (0.011) | (0.043) | (0.042) | (0.042) | (0.004) | |
facial coverings | −0.133 *** | 0.032 *** | −0.102 ** | −0.115 ** | −0.108 ** | 0.013 *** |
(0.042) | (0.011) | (0.044) | (0.044) | (0.044) | (0.005) | |
vaccination | −0.158 *** | −0.005 | −0.163 *** | −0.171 *** | −0.167 *** | 0.008 |
(0.044) | (0.010) | (0.044) | (0.043) | (0.043) | (0.008) | |
dlogdc | 0.048 *** | 0.010 *** | 0.057 *** | 0.057 *** | 0.057 *** | −0.000 |
(0.016) | (0.002) | (0.017) | (0.017) | (0.017) | (0.001) | |
logdc | −0.028 *** | −0.006 *** | −0.034 *** | −0.035 *** | −0.034 *** | 0.001 |
(0.006) | (0.002) | (0.006) | (0.006) | (0.006) | (0.001) | |
(b) Deaths | Direct Effect | Indirect Effect | Total Effect | Average | Difference | |
Considering Causal Pathways | Not Considering Causal Pathways | |||||
school closing | −0.174 *** | −0.036 *** | −0.210 *** | −0.217 *** | −0.214 *** | 0.007 |
(0.059) | (0.013) | (0.063) | (0.064) | (0.064) | (0.006) | |
cancel public events | −0.079 * | 0.001 | −0.078 | −0.075 | −0.077 | −0.003 |
(0.045) | (0.012) | (0.048) | (0.049) | (0.048) | (0.005) | |
restrictions on gatherings | −0.015 | −0.029 ** | −0.044 | −0.044 | −0.044 | 0.000 |
(0.037) | (0.012) | (0.040) | (0.040) | (0.040) | (0.005) | |
close public transport | 0.038 * | −0.017 * | 0.021 | 0.023 | 0.022 | −0.001 |
(0.022) | (0.009) | (0.023) | (0.023) | (0.023) | (0.002) | |
stay at home requirements | 0.023 | −0.029 *** | −0.007 | −0.007 | −0.007 | 0.000 |
(0.029) | (0.009) | (0.028) | (0.028) | (0.028) | (0.003) | |
international travel controls | −0.336 *** | −0.029 ** | −0.365 *** | −0.362 *** | −0.363 *** | −0.003 |
(0.113) | (0.013) | (0.119) | (0.118) | (0.119) | (0.005) | |
testing | −0.029 | −0.037 *** | −0.066 | −0.066 | −0.066 | −0.000 |
(0.103) | (0.010) | (0.106) | (0.107) | (0.106) | (0.007) | |
contact tracing | −0.027 | −0.001 | −0.028 | −0.028 | −0.028 | 0.001 |
(0.042) | (0.009) | (0.043) | (0.043) | (0.043) | (0.004) | |
facial coverings | −0.126 *** | 0.031 *** | −0.095 ** | −0.111 *** | −0.103 *** | 0.017 *** |
(0.039) | (0.011) | (0.040) | (0.041) | (0.040) | (0.006) | |
vaccination | −0.144 *** | −0.007 | −0.150 *** | −0.155 *** | −0.153 *** | 0.005 |
(0.041) | (0.010) | (0.042) | (0.041) | (0.041) | (0.009) | |
dlogdd | 0.050 *** | 0.0004 | 0.050 *** | 0.052 *** | 0.051 *** | −0.002 ** |
(0.012) | (0.001) | (0.012) | (0.012) | (0.012) | (0.001) | |
logdd | −0.021 *** | −0.005 *** | −0.026 *** | −0.026 *** | −0.026 *** | 0.001 |
(0.004) | (0.002) | (0.004) | (0.004) | (0.004) | (0.001) |
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Wang, F.; Ge, X.; Huang, D. Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries. Sustainability 2022, 14, 3694. https://doi.org/10.3390/su14063694
Wang F, Ge X, Huang D. Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries. Sustainability. 2022; 14(6):3694. https://doi.org/10.3390/su14063694
Chicago/Turabian StyleWang, Feng, Xing Ge, and Danwen Huang. 2022. "Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries" Sustainability 14, no. 6: 3694. https://doi.org/10.3390/su14063694