期刊
HEALTH & PLACE
卷 79, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.healthplace.2021.102668
关键词
Mobility; Covid-19; Regional intervention; Interrupted time -series; Flows; difference -in -difference
Regionally targeted interventions have been used by governments to slow the spread of COVID-19, but their effectiveness in areas with free movement is uncertain. This study uses mobile-phone network mobility data to test two hypotheses and analyzes regionally targeted interventions in Ontario, Canada. The findings suggest that these interventions had no significant effect on inter-regional mobility and that mobility was influenced by socio-economic factors and distance to the intervention region's boundary. These findings are important for guiding the design of regionally targeted interventions based on observed mobility patterns.
Regionally targeted interventions are being used by governments to slow the spread of COVID-19. In areas where free movement is not being actively restricted, there is uncertainty about how effective such regionally targeted interventions are due to the free movement of people between regions. We use mobile-phone network mobility data to test two hypotheses: 1) do regions targeted by exhibit increased outflows into other regions and 2) do regions targeted by interventions increase outflows specifically into areas with lesser restrictions. Our analysis focuses on two well-defined regionally targeted interventions in Ontario, Canada the first intervention as the first wave subsided (July 17, 2020) and the second intervention as we entered into new restrictions during the onset of the second wave (November 23, 2020). We use a difference-in-difference model to investigate hypothesis 1 and an interrupted time series model to investigate hypothesis 2, controlling for spatial effects (using a spatial -error model) in both cases. Our findings suggest that there that the regionally targeted interventions had a neutral effect (or no effect) on inter-regional mobility, with no significant differences associated with the in-terventions. We also found that overall inter-regional mobility was associated with socio-economic factors and the distance to the boundary of the intervention region. These findings are important as they should guide how governments design regionally targeted interventions (from a geographical perspective) considering observed patterns of mobility.
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