Cargando…

Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study

BACKGROUND: Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels o...

Descripción completa

Detalles Bibliográficos
Autores principales: Badr, Hamada S, Du, Hongru, Marshall, Maximilian, Dong, Ensheng, Squire, Marietta M, Gardner, Lauren M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329287/
https://www.ncbi.nlm.nih.gov/pubmed/32621869
http://dx.doi.org/10.1016/S1473-3099(20)30553-3
_version_ 1783552877517602816
author Badr, Hamada S
Du, Hongru
Marshall, Maximilian
Dong, Ensheng
Squire, Marietta M
Gardner, Lauren M
author_facet Badr, Hamada S
Du, Hongru
Marshall, Maximilian
Dong, Ensheng
Squire, Marietta M
Gardner, Lauren M
author_sort Badr, Hamada S
collection PubMed
description BACKGROUND: Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels of enforcement. The absence of a centralised policy and timeline combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the USA a challenge. METHODS: We used daily mobility data derived from aggregated and anonymised cell (mobile) phone data, provided by Teralytics (Zürich, Switzerland) from Jan 1 to April 20, 2020, to capture real-time trends in movement patterns for each US county, and used these data to generate a social distancing metric. We used epidemiological data to compute the COVID-19 growth rate ratio for a given county on a given day. Using these metrics, we evaluated how social distancing, measured by the relative change in mobility, affected the rate of new infections in the 25 counties in the USA with the highest number of confirmed cases on April 16, 2020, by fitting a statistical model for each county. FINDINGS: Our analysis revealed that mobility patterns are strongly correlated with decreased COVID-19 case growth rates for the most affected counties in the USA, with Pearson correlation coefficients above 0·7 for 20 of the 25 counties evaluated. Additionally, the effect of changes in mobility patterns, which dropped by 35–63% relative to the normal conditions, on COVID-19 transmission are not likely to be perceptible for 9–12 days, and potentially up to 3 weeks, which is consistent with the incubation time of severe acute respiratory syndrome coronavirus 2 plus additional time for reporting. We also show evidence that behavioural changes were already underway in many US counties days to weeks before state-level or local-level stay-at-home policies were implemented, implying that individuals anticipated public health directives where social distancing was adopted, despite a mixed political message. INTERPRETATION: This study strongly supports a role of social distancing as an effective way to mitigate COVID-19 transmission in the USA. Until a COVID-19 vaccine is widely available, social distancing will remain one of the primary measures to combat disease spread, and these findings should serve to support more timely policy making around social distancing in the USA in the future. FUNDING: None.
format Online
Article
Text
id pubmed-7329287
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-73292872020-07-02 Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study Badr, Hamada S Du, Hongru Marshall, Maximilian Dong, Ensheng Squire, Marietta M Gardner, Lauren M Lancet Infect Dis Articles BACKGROUND: Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels of enforcement. The absence of a centralised policy and timeline combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the USA a challenge. METHODS: We used daily mobility data derived from aggregated and anonymised cell (mobile) phone data, provided by Teralytics (Zürich, Switzerland) from Jan 1 to April 20, 2020, to capture real-time trends in movement patterns for each US county, and used these data to generate a social distancing metric. We used epidemiological data to compute the COVID-19 growth rate ratio for a given county on a given day. Using these metrics, we evaluated how social distancing, measured by the relative change in mobility, affected the rate of new infections in the 25 counties in the USA with the highest number of confirmed cases on April 16, 2020, by fitting a statistical model for each county. FINDINGS: Our analysis revealed that mobility patterns are strongly correlated with decreased COVID-19 case growth rates for the most affected counties in the USA, with Pearson correlation coefficients above 0·7 for 20 of the 25 counties evaluated. Additionally, the effect of changes in mobility patterns, which dropped by 35–63% relative to the normal conditions, on COVID-19 transmission are not likely to be perceptible for 9–12 days, and potentially up to 3 weeks, which is consistent with the incubation time of severe acute respiratory syndrome coronavirus 2 plus additional time for reporting. We also show evidence that behavioural changes were already underway in many US counties days to weeks before state-level or local-level stay-at-home policies were implemented, implying that individuals anticipated public health directives where social distancing was adopted, despite a mixed political message. INTERPRETATION: This study strongly supports a role of social distancing as an effective way to mitigate COVID-19 transmission in the USA. Until a COVID-19 vaccine is widely available, social distancing will remain one of the primary measures to combat disease spread, and these findings should serve to support more timely policy making around social distancing in the USA in the future. FUNDING: None. Elsevier Ltd. 2020-11 2020-07-01 /pmc/articles/PMC7329287/ /pubmed/32621869 http://dx.doi.org/10.1016/S1473-3099(20)30553-3 Text en © 2020 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 Articles
Badr, Hamada S
Du, Hongru
Marshall, Maximilian
Dong, Ensheng
Squire, Marietta M
Gardner, Lauren M
Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title_full Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title_fullStr Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title_full_unstemmed Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title_short Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study
title_sort association between mobility patterns and covid-19 transmission in the usa: a mathematical modelling study
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329287/
https://www.ncbi.nlm.nih.gov/pubmed/32621869
http://dx.doi.org/10.1016/S1473-3099(20)30553-3
work_keys_str_mv AT badrhamadas associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy
AT duhongru associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy
AT marshallmaximilian associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy
AT dongensheng associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy
AT squiremariettam associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy
AT gardnerlaurenm associationbetweenmobilitypatternsandcovid19transmissionintheusaamathematicalmodellingstudy