COVID-19 and urban exodus: diverging population redistribution patterns across countries from 2020 to 2022
Year: 2026
Type: article
Abstract: While widespread urbanisation continues, emerging trends of population redistribution away from highly urbanised areas have been observed in some countries, with important implications for infrastructure planning, resource allocation, and environmental risk assessment. However, few studies have examined this trend in a timely and spatially comprehensive manner across diverse national contexts, particularly in response to the turbulence in migration patterns caused by the COVID-19 pandemic. Here, we analyse spatial Facebook population data from 2020 to 2022 across 35 countries to characterise two forms of population redistribution: shifts between urban and rural areas, and changes along the urban density gradient. During the early response phase of the pandemic, broader country-level trends of urban-to-rural redistribution and intra-urban deconcentration were evident. However, 20% and 4.8% of these trends, respectively, were temporary and reversed during the later phase of the pandemic. The extent and direction of these patterns varied across countries and were negatively associated with the Human Development Index, suggesting that developed nations experienced greater urban depopulation and spatial deconcentration. Our findings reveal a potential misalignment between population redistribution and existing physical urban densities in certain countries, as densely built-up areas are experiencing outflows, highlighting the need for adaptive urban planning strategies to address evolving population dynamics and related sustainability challenges.
Source: npj Urban Sustainability
Institutions: University of Southampton, University of Milan
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,490
Awards: Collaborative Research: IHBEM: The fear of here: Integrating place-based travel behavior and detection into novel infectious disease models, G3555387431, The University of Southampton - to characterize the seasonality of the SARS-CoV2 virus is different setting around the world to best support mitigation efforts, G5197853511, G6112810876, The South Coast ESRC Doctoral Training Partnership, G8637937799, G8657463507, Human mobility models to forecast disease dynamics and the effectiveness of public health interventions
OpenAlex ID: W7128083515