Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference

Xiao Huang, Yang Xu, Rui Liu, Siqin Wang, Sicheng Wang, Mengxi Zhang, Yuhao Kang, Zhe Zhang, Song Gao, Bo Zhao, Zhenlong Li

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this study, we aim to reveal hidden patterns and confounders associated with policy implementation and adherence by investigating the home-dwelling stages from a data-driven perspective via Bayesian inference with weakly informative priors and by examining how home-dwelling stages in the USA varied geographically, using fine-grained, spatial-explicit home-dwelling time records from a multi-scale perspective. At the U.S. national level, two changepoints are identified, with the former corresponding to March 22, 2020 (9 days after the White House declared the National Emergency on March 13) and the latter corresponding to May 17, 2020. Inspections at U.S. state and county level reveal notable spatial disparity in home-dwelling stage-related variables. A pilot study in the Atlanta Metropolitan area at the Census Tract level reveals that the self-quarantine duration and increase in home-dwelling time are strongly correlated with the median household income, echoing existing efforts that document the economic inequity exposed by the U.S. stay-at-home orders. To our best knowledge, our work marks a pioneering effort to explore multi-scale home-dwelling patterns in the USA from a purely data-driven perspective and in a statistically robust manner.

Original languageEnglish (US)
Pages (from-to)1939-1961
Number of pages23
JournalTransactions in GIS
Volume26
Issue number4
DOIs
StatePublished - Jun 2022

All Science Journal Classification (ASJC) codes

  • General Earth and Planetary Sciences

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