Do regionally targeted lockdowns alter movement to non-lockdown regions? Evidence from Ontario, Canada. (January 2023)

• Record Type: Journal Article
• Authors: Long, Jed A.; Malekzadeh, Milad; Klar, Ben; Martin, Gina
• Is Part Of: Health & place. Volume 79(2023)
• Publication Date: 2023-01
• Subjects: Mobility -- Covid-19 -- Regional intervention -- Interrupted time-series -- Flows -- difference-in-difference; Health -- Social aspects -- Periodicals; Health services accessibility -- Periodicals; Public health -- Periodicals; Political planning -- Periodicals; Social medicine -- Periodicals; Epidemiology -- Periodicals; Health Policy -- Periodicals; Health Services Accessibility -- Periodicals; Public Health -- Periodicals; Public Policy -- Periodicals; Sociology, Medical -- Periodicals; Épidémiologie -- Périodiques; Politique sanitaire -- Périodiques; Santé, Services de -- Accessibilité -- Périodiques; Health services accessibility; Health -- Social aspects; Political planning; Public health; Social medicine; Periodicals; 613
• DOI: 10.1016/j.healthplace.2021.102668
• Languages: English
• ISSNs: 1353-8292

Abstract

Abstract: 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 interventions. 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. Highlights: Regionally targeted interventions were used in Ontario to stop spread of COVID-19. Flows are used measure the level of movement from one region to another. We use mobile phone data to measure flows during two public health interventions. We find that regionally targeted interventions had a neutral effect on flows from target regions. Flows were associated with distance to intervention boundary and socio-economic factors.