About this scholarly article

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology by Ye, Wen (author);Gao, Song (author) is a scholarly article available to read on EtoBox.

It has been well-established that human mobility has an inseparable relationship with COVID-19 infections. As social-distancing and stay-at-home orders lifted and data availability increased, our knowledge on how human behaviors including mobility and close interpersonal contacts associate with the pandemic progression also needs to stay updated. In this paper, we examine the relationship of COVID-19 daily transmissibility measured by the total confirmed cases and the effective reproduction number (R t ) with the two indices that provide human behavior insights: Cuebiq Mobility Index (CMI) and Cuebiq Contact Index (CCI). The correlations between each index and COVID-19 infections are evaluated using the Maximal Information Coefficient (MIC) which is powerful in capturing complex relationships. Moreover, the study period is segmented into three periods by Bayesian Change Point Detection to examine temporal heterogeneity and the mainland US states are grouped into three distinct clusters using the KShape clustering algorithm to further examine spatial heterogeneity. The CCI and CMI exhibited very different patterns and we found significant temporal and spatial heterogeneities among t

Author

Ye, Wen (author);Gao, Song (author)

Publisher

ACM

Published

2022

Language

EN