Authors: Atsushi Nara*, San Diego State University
Topics: Spatial Analysis & Modeling, Temporal GIS, Geographic Information Science and Systems
Keywords: GIS, spatiotemporal, SafeGraph
Session Type: Virtual Paper
Start / End Time: 8:00 AM / 9:15 AM
Room: Virtual 8
Presentation File: No File Uploaded
The COVID-19 pandemic has made significant impacts on people’s everyday life. In particular, social distancing, a widely adopted strategy to slow COVID‑19 transmission by limiting contact between people, has changed human mobility and their behavior drastically. While public health social distancing-related interventions such as stay-at-home order, overnight curfew, facility closure, and lockdown restrict human movements in general, reopening decisions and non-uniform implementation of interventions can increase human movements and the risk of COVID-19 exposure unevenly in space and time. This paper will present a neighborhood-level spatiotemporal analysis to examine how human movements has changed across space over time in response to the crisis situation and how the mobility change has related to the COVID-19 epidemiology. This study uses cell-phone-based data and COVID-19 confirmed case data at a neighborhood scale in County of San Diego, CA.