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Comparing community mobility reduction between first and second COVID-19 waves

BACKGROUND: In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mo...

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Autores principales: Cavalcante da Silva, Gabriela, Monteiro de Almeida, Fernanda, Oliveira, Sabrina, Wanner, Elizabeth F., Bezerra, Leonardo C.T., Takahashi, Ricardo H.C., Lima, Luciana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759400/
https://www.ncbi.nlm.nih.gov/pubmed/36570325
http://dx.doi.org/10.1016/j.tranpol.2021.08.004
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author Cavalcante da Silva, Gabriela
Monteiro de Almeida, Fernanda
Oliveira, Sabrina
Wanner, Elizabeth F.
Bezerra, Leonardo C.T.
Takahashi, Ricardo H.C.
Lima, Luciana
author_facet Cavalcante da Silva, Gabriela
Monteiro de Almeida, Fernanda
Oliveira, Sabrina
Wanner, Elizabeth F.
Bezerra, Leonardo C.T.
Takahashi, Ricardo H.C.
Lima, Luciana
author_sort Cavalcante da Silva, Gabriela
collection PubMed
description BACKGROUND: In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mobility from the different lockdown periods for each locality selected, simultaneously considering multiple place categories provided in CMR. In addition, our analysis comprises a 56-day lockdown period for each locality and COVID-19 wave, which we analyze both as 56-day periods and as 14-day consecutive windows. METHODS: We use locality-wise calibrated CMR data, which we process through seasonal-trend decomposition by LOESS (STL) to isolate trend from seasonal and noise effects. We scale trend data to draw Pareto-compliant conclusions using radar charts. For each temporal granularity considered, data for a given place category is aggregated using the area under the curve (AUC) approach. RESULTS: In general, reduction rates observed during the first wave were much higher than during the second. Alarmingly, December holiday season mobility in some of the localities reached pre-pandemic levels for some of the place categories reported. Manaus was the only locality where second wave mobility was nearly as reduced as during the first wave, likely due to the P1 variant outbreak and oxygen supply crisis.
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spelling pubmed-97594002022-12-19 Comparing community mobility reduction between first and second COVID-19 waves Cavalcante da Silva, Gabriela Monteiro de Almeida, Fernanda Oliveira, Sabrina Wanner, Elizabeth F. Bezerra, Leonardo C.T. Takahashi, Ricardo H.C. Lima, Luciana Transp Policy (Oxf) Article BACKGROUND: In this paper, we conduct a mobility reduction rate comparison between the first and second COVID-19 waves in several localities from America and Europe using Google community mobility reports (CMR) data. Through multi-dimensional visualization, we are able to compare the reduction in mobility from the different lockdown periods for each locality selected, simultaneously considering multiple place categories provided in CMR. In addition, our analysis comprises a 56-day lockdown period for each locality and COVID-19 wave, which we analyze both as 56-day periods and as 14-day consecutive windows. METHODS: We use locality-wise calibrated CMR data, which we process through seasonal-trend decomposition by LOESS (STL) to isolate trend from seasonal and noise effects. We scale trend data to draw Pareto-compliant conclusions using radar charts. For each temporal granularity considered, data for a given place category is aggregated using the area under the curve (AUC) approach. RESULTS: In general, reduction rates observed during the first wave were much higher than during the second. Alarmingly, December holiday season mobility in some of the localities reached pre-pandemic levels for some of the place categories reported. Manaus was the only locality where second wave mobility was nearly as reduced as during the first wave, likely due to the P1 variant outbreak and oxygen supply crisis. Elsevier Ltd. 2021-10 2021-08-25 /pmc/articles/PMC9759400/ /pubmed/36570325 http://dx.doi.org/10.1016/j.tranpol.2021.08.004 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Cavalcante da Silva, Gabriela
Monteiro de Almeida, Fernanda
Oliveira, Sabrina
Wanner, Elizabeth F.
Bezerra, Leonardo C.T.
Takahashi, Ricardo H.C.
Lima, Luciana
Comparing community mobility reduction between first and second COVID-19 waves
title Comparing community mobility reduction between first and second COVID-19 waves
title_full Comparing community mobility reduction between first and second COVID-19 waves
title_fullStr Comparing community mobility reduction between first and second COVID-19 waves
title_full_unstemmed Comparing community mobility reduction between first and second COVID-19 waves
title_short Comparing community mobility reduction between first and second COVID-19 waves
title_sort comparing community mobility reduction between first and second covid-19 waves
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759400/
https://www.ncbi.nlm.nih.gov/pubmed/36570325
http://dx.doi.org/10.1016/j.tranpol.2021.08.004
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