Cargando…
Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic
Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced fo...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508394/ https://www.ncbi.nlm.nih.gov/pubmed/32960932 http://dx.doi.org/10.1371/journal.pone.0239572 |
_version_ | 1783585412013359104 |
---|---|
author | Narayanan, Rajesh P. Nordlund, James Pace, R. Kelley Ratnadiwakara, Dimuthu |
author_facet | Narayanan, Rajesh P. Nordlund, James Pace, R. Kelley Ratnadiwakara, Dimuthu |
author_sort | Narayanan, Rajesh P. |
collection | PubMed |
description | Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced form models of social distancing as a function of county-level exogenous demographic variables and jurisdictional fixed effects for 49 states to assess the relative contributions of demographic and jurisdictional effects in explaining social distancing behavior. To allow for possible spatial aspects of a contagious disease, we also model the spillovers associated with demographic variables in surrounding counties as well as allow for disturbances that depend upon those in surrounding counties. We run our models weekly and examine the evolution of the estimated coefficients over time since the onset of the COVID-19 pandemic in the United States. These estimated coefficients express the revealed preferences of individuals who were able to and chose to stay at home to avoid the disease. Stay-at-home behavior measured using cell phone tracking data exhibits considerable cross-sectional variation, increasing over nine-fold from the end of January 2020 to the end of March 2020, and then decreasing by about 50% through mid-June 2020. Our estimation results show that demographic exogenous variables explain substantially more of this variation than predictions from jurisdictional fixed effects. Moreover, the explanations from demographic exogenous variables and jurisdictional fixed effects show an evolving correlation over the sample period, initially partially offsetting, and eventually reinforcing each other. Furthermore, the predicted social distance from demographic exogenous variables shows substantial spatial autoregressive dependence, indicating clustering in social distancing behavior. The increased variance of stay-at-home behavior coupled with the high level of spatial dependence can result in relatively intense hotspots and coldspots of social distance, which has implications for disease spread and mitigation. |
format | Online Article Text |
id | pubmed-7508394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75083942020-10-01 Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic Narayanan, Rajesh P. Nordlund, James Pace, R. Kelley Ratnadiwakara, Dimuthu PLoS One Research Article Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced form models of social distancing as a function of county-level exogenous demographic variables and jurisdictional fixed effects for 49 states to assess the relative contributions of demographic and jurisdictional effects in explaining social distancing behavior. To allow for possible spatial aspects of a contagious disease, we also model the spillovers associated with demographic variables in surrounding counties as well as allow for disturbances that depend upon those in surrounding counties. We run our models weekly and examine the evolution of the estimated coefficients over time since the onset of the COVID-19 pandemic in the United States. These estimated coefficients express the revealed preferences of individuals who were able to and chose to stay at home to avoid the disease. Stay-at-home behavior measured using cell phone tracking data exhibits considerable cross-sectional variation, increasing over nine-fold from the end of January 2020 to the end of March 2020, and then decreasing by about 50% through mid-June 2020. Our estimation results show that demographic exogenous variables explain substantially more of this variation than predictions from jurisdictional fixed effects. Moreover, the explanations from demographic exogenous variables and jurisdictional fixed effects show an evolving correlation over the sample period, initially partially offsetting, and eventually reinforcing each other. Furthermore, the predicted social distance from demographic exogenous variables shows substantial spatial autoregressive dependence, indicating clustering in social distancing behavior. The increased variance of stay-at-home behavior coupled with the high level of spatial dependence can result in relatively intense hotspots and coldspots of social distance, which has implications for disease spread and mitigation. Public Library of Science 2020-09-22 /pmc/articles/PMC7508394/ /pubmed/32960932 http://dx.doi.org/10.1371/journal.pone.0239572 Text en © 2020 Narayanan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Narayanan, Rajesh P. Nordlund, James Pace, R. Kelley Ratnadiwakara, Dimuthu Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title | Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title_full | Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title_fullStr | Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title_full_unstemmed | Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title_short | Demographic, jurisdictional, and spatial effects on social distancing in the United States during the COVID-19 pandemic |
title_sort | demographic, jurisdictional, and spatial effects on social distancing in the united states during the covid-19 pandemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508394/ https://www.ncbi.nlm.nih.gov/pubmed/32960932 http://dx.doi.org/10.1371/journal.pone.0239572 |
work_keys_str_mv | AT narayananrajeshp demographicjurisdictionalandspatialeffectsonsocialdistancingintheunitedstatesduringthecovid19pandemic AT nordlundjames demographicjurisdictionalandspatialeffectsonsocialdistancingintheunitedstatesduringthecovid19pandemic AT pacerkelley demographicjurisdictionalandspatialeffectsonsocialdistancingintheunitedstatesduringthecovid19pandemic AT ratnadiwakaradimuthu demographicjurisdictionalandspatialeffectsonsocialdistancingintheunitedstatesduringthecovid19pandemic |