Time series cross-correlation between home range and number of infected people during the medium-term of the COVID-19 pandemic in a suburban city

Abstract

Control of human mobility is among the most effective measures to prevent the spread of coronavirus disease 2019 (COVID-19). This study aims to clarify the correlation between home range and the number of people infected with SARS-CoV-2 during the medium-term of the COVID-19 pandemic in Ibaraki City. Home ranges are analyzed by the Minimum Convex Polygon method using mobile phone GPS location history data. We analyzed the time series cross-correlation between home range lengths and the number of infected people. Results reveal a slight positive correlation between home range and the number of infected people after one week during the medium-term of the COVID-19 pandemic. Regarding home range length, the cross-correlation coefficient is 0.4030 even at a lag level of six weeks, which has the most significant coefficient. Thus, a decrease in home range is only one of the indirect factors contributing toward a reduction in the number of infected people. This study makes a significant contribution to the literature by evaluating key public health challenges from the perspective of controliing the spread of the COVID-19 infectuion. Its findings has implications for policy makers, practitioners, and urban scientists seeking to promote urban sustainability.

Human Mobility and Medical Costs of Lifestyle-related Diseases during the COVID-19 Pandemic

“…Based on the target values, governments could take measures other than restricting human mobility of walking and public transit. Restricting human mobility had a slight positive correlation with the number of infected people during the medium-term COVID-19 pandemic [34]. In addition to controlling human mobility, restrictions on wearing face masks might also have impacted the infection rate.…”