Cargando…

Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Venter, Zander S., Sadilek, Adam, Stanton, Charlotte, Barton, David N., Aunan, Kristin, Chowdhury, Sourangsu, Schneider, Aaron, Iacus, Stefano Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656877/
https://www.ncbi.nlm.nih.gov/pubmed/34886291
http://dx.doi.org/10.3390/ijerph182312567
_version_ 1784612387143286784
author Venter, Zander S.
Sadilek, Adam
Stanton, Charlotte
Barton, David N.
Aunan, Kristin
Chowdhury, Sourangsu
Schneider, Aaron
Iacus, Stefano Maria
author_facet Venter, Zander S.
Sadilek, Adam
Stanton, Charlotte
Barton, David N.
Aunan, Kristin
Chowdhury, Sourangsu
Schneider, Aaron
Iacus, Stefano Maria
author_sort Venter, Zander S.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8656877
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-86568772021-12-10 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 Int J Environ Res Public Health Article 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. MDPI 2021-11-29 /pmc/articles/PMC8656877/ /pubmed/34886291 http://dx.doi.org/10.3390/ijerph182312567 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Venter, Zander S.
Sadilek, Adam
Stanton, Charlotte
Barton, David N.
Aunan, Kristin
Chowdhury, Sourangsu
Schneider, Aaron
Iacus, Stefano Maria
Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title_full Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title_fullStr Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title_full_unstemmed Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title_short Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis
title_sort mobility in blue-green spaces does not predict covid-19 transmission: a global analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656877/
https://www.ncbi.nlm.nih.gov/pubmed/34886291
http://dx.doi.org/10.3390/ijerph182312567
work_keys_str_mv AT venterzanders mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT sadilekadam mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT stantoncharlotte mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT bartondavidn mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT aunankristin mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT chowdhurysourangsu mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT schneideraaron mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis
AT iacusstefanomaria mobilityinbluegreenspacesdoesnotpredictcovid19transmissionaglobalanalysis