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Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility
We explored the viability of using air quality as an alternative to aggregated location data from mobile phones in the two most populated cities in Uganda. We accessed air quality and Google mobility data collected from 15(th) February 2020 to 10(th) June 2021 and augmented them with mobility restri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751517/ https://www.ncbi.nlm.nih.gov/pubmed/36520281 http://dx.doi.org/10.1007/s11356-022-24605-1 |
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author | Galiwango, Ronald Bainomugisha, Engineer Kivunike, Florence Kateete, David Patrick Jjingo, Daudi |
author_facet | Galiwango, Ronald Bainomugisha, Engineer Kivunike, Florence Kateete, David Patrick Jjingo, Daudi |
author_sort | Galiwango, Ronald |
collection | PubMed |
description | We explored the viability of using air quality as an alternative to aggregated location data from mobile phones in the two most populated cities in Uganda. We accessed air quality and Google mobility data collected from 15(th) February 2020 to 10(th) June 2021 and augmented them with mobility restrictions implemented during the COVID-19 lockdown. We determined whether air quality data depicted similar patterns to mobility data before, during, and after the lockdown and determined associations between air quality and mobility by computing Pearson correlation coefficients ([Formula: see text] ), conducting multivariable regression with associated confidence intervals (CIs), and visualized the relationships using scatter plots. Residential mobility increased with the stringency of restrictions while both non-residential mobility and air pollution decreased with the stringency of restrictions. In Kampala, PM(2.5) was positively correlated with non-residential mobility and negatively correlated with residential mobility. Only correlations between PM(2.5) and movement in work and residential places were statistically significant in Wakiso. After controlling for stringency in restrictions, air quality in Kampala was independently correlated with movement in retail and recreation (− 0.55; 95% CI = − 1.01– − 0.10), parks (0.29; 95% CI = 0.03–0.54), transit stations (0.29; 95% CI = 0.16–0.42), work (− 0.25; 95% CI = − 0.43– − 0.08), and residential places (− 1.02; 95% CI = − 1.4– − 0.64). For Wakiso, only the correlation between air quality and residential mobility was statistically significant (− 0.99; 95% CI = − 1.34– − 0.65). These findings suggest that air quality is linked to mobility and thus could be used by public health programs in monitoring movement patterns and the spread of infectious diseases without compromising on individuals’ privacy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-24605-1. |
format | Online Article Text |
id | pubmed-9751517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-97515172022-12-15 Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility Galiwango, Ronald Bainomugisha, Engineer Kivunike, Florence Kateete, David Patrick Jjingo, Daudi Environ Sci Pollut Res Int Research Article We explored the viability of using air quality as an alternative to aggregated location data from mobile phones in the two most populated cities in Uganda. We accessed air quality and Google mobility data collected from 15(th) February 2020 to 10(th) June 2021 and augmented them with mobility restrictions implemented during the COVID-19 lockdown. We determined whether air quality data depicted similar patterns to mobility data before, during, and after the lockdown and determined associations between air quality and mobility by computing Pearson correlation coefficients ([Formula: see text] ), conducting multivariable regression with associated confidence intervals (CIs), and visualized the relationships using scatter plots. Residential mobility increased with the stringency of restrictions while both non-residential mobility and air pollution decreased with the stringency of restrictions. In Kampala, PM(2.5) was positively correlated with non-residential mobility and negatively correlated with residential mobility. Only correlations between PM(2.5) and movement in work and residential places were statistically significant in Wakiso. After controlling for stringency in restrictions, air quality in Kampala was independently correlated with movement in retail and recreation (− 0.55; 95% CI = − 1.01– − 0.10), parks (0.29; 95% CI = 0.03–0.54), transit stations (0.29; 95% CI = 0.16–0.42), work (− 0.25; 95% CI = − 0.43– − 0.08), and residential places (− 1.02; 95% CI = − 1.4– − 0.64). For Wakiso, only the correlation between air quality and residential mobility was statistically significant (− 0.99; 95% CI = − 1.34– − 0.65). These findings suggest that air quality is linked to mobility and thus could be used by public health programs in monitoring movement patterns and the spread of infectious diseases without compromising on individuals’ privacy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-24605-1. Springer Berlin Heidelberg 2022-12-15 2023 /pmc/articles/PMC9751517/ /pubmed/36520281 http://dx.doi.org/10.1007/s11356-022-24605-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Galiwango, Ronald Bainomugisha, Engineer Kivunike, Florence Kateete, David Patrick Jjingo, Daudi Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title | Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title_full | Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title_fullStr | Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title_full_unstemmed | Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title_short | Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
title_sort | air pollution and mobility patterns in two ugandan cities during covid-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751517/ https://www.ncbi.nlm.nih.gov/pubmed/36520281 http://dx.doi.org/10.1007/s11356-022-24605-1 |
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