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Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis.
Venter, Zander S; Sadilek, Adam; Stanton, Charlotte; Barton, David N; Aunan, Kristin; Chowdhury, Sourangsu; Schneider, Aaron; Iacus, Stefano Maria.
Afiliación
  • Venter ZS; Norwegian Institute for Nature Research-NINA, Sognsveien 68, 0855 Oslo, Norway.
  • Sadilek A; Google, Mountain View, CA 94043, USA.
  • Stanton C; Google, Mountain View, CA 94043, USA.
  • Barton DN; Norwegian Institute for Nature Research-NINA, Sognsveien 68, 0855 Oslo, Norway.
  • Aunan K; CICERO Center for International Climate Research, P.O. Box 1129 Blindern, N318 Oslo, Norway.
  • Chowdhury S; Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, 55128 Mainz, Germany.
  • Schneider A; Google, Mountain View, CA 94043, USA.
  • Iacus SM; European Commission, Joint Research Centre, 21027 Ispra, Italy.
Article en En | MEDLINE | ID: mdl-34886291
ABSTRACT
Mobility restrictions during the COVID-19 pandemic ostensibly prevented the public from transmitting the disease in public places, but they also hampered outdoor recreation, despite the importance of blue-green spaces (e.g., parks and natural areas) for physical and mental health. We assess whether restrictions on human movement, particularly in blue-green spaces, affected the transmission of COVID-19. Our assessment uses a spatially resolved dataset of COVID-19 case numbers for 848 administrative units across 153 countries during the first year of the pandemic (February 2020 to February 2021). We measure mobility in blue-green spaces with planetary-scale aggregate and anonymized mobility flows derived from mobile phone tracking data. We then use machine learning forecast models and linear mixed-effects models to explore predictors of COVID-19 growth rates. After controlling for a number of environmental factors, we find no evidence that increased visits to blue-green space increase COVID-19 transmission. By contrast, increases in the total mobility and relaxation of other non-pharmaceutical interventions such as containment and closure policies predict greater transmission. Ultraviolet radiation stands out as the strongest environmental mitigant of COVID-19 spread, while temperature, humidity, wind speed, and ambient air pollution have little to no effect. Taken together, our analyses produce little evidence to support public health policies that restrict citizens from outdoor mobility in blue-green spaces, which corroborates experimental studies showing low risk of outdoor COVID-19 transmission. However, we acknowledge and discuss some of the challenges of big data approaches to ecological regression analyses such as this, and outline promising directions and opportunities for future research.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2021 Tipo del documento: Article País de afiliación: Noruega

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2021 Tipo del documento: Article País de afiliación: Noruega