Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates: Early evidence from 1,165 metropolitan counties in the United States

Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis

The ongoing COVID-19 pandemic has created significant public health concerns that led the public and private sectors to impose stay-at-home and work-from-home policies. Although working from home has been a conventional albeit infrequent behavior, the prevalence of this option was significantly and rapidly accelerated during the pandemic. This study explored the impacts of working from home on activity-travel behavior during the pandemic. Both work and non-work activity participation declined during the pandemic but to what extent was this due to working from home? How did working from home affect other measures of travel such as person-miles traveled? We approached these questions by developing a Structural Regression model and using cross-sectional data for the early phase of the pandemic when the infection curve was flattened and activity-travel behavior became relatively stable following the drastic changes observed during the pandemic's initial shock. Combining U.S. county-level data from the Maryland Transportation Institute and Google Mobility Reports, we concluded that the proportion of people working from home directly depended on pandemic severity and associated public health policies as well as on a range of socio-economic characteristics. Working from home contributed to a reduction in workplace visits. It also reduced non-work activities but only via a reduction in non-work activities linked to work. Finally, a higher working from home proportion in a county corresponded to a reduction in average person-miles traveled. A higher degree of state government responses to containment and closure policies contributed to an increase in working from home, and decreases in workplace and non-workplace visits and person-miles traveled in a county. The results of this study provide important insights into changes in activity-travel behavior associated with working from home as a response strategy to major disruptions such as those imposed by a pandemic.

Structural modeling of COVID-19 spread in relation to human mobility

Human mobility is considered as one of the prominent non-pharmaceutical interventions to control the spread of the pandemic (positive effect from mobility to infection). Conversely, the spread of the pandemic triggered massive changes to people's daily schedules by limiting their movement (negative effect from infection to mobility). The purpose of this study is to investigate this bi-directional relationship between human mobility and COVID-19 spread across U.S. counties during the early phase of the pandemic when infection rates were stabilizing and activity-travel behavior reflected a fairly steady return to normal following the drastic changes observed during the pandemic's initial shock. In particular, we applied Structural Regression (SR) model to investigate a bi-directional relationship between COVID-19 infection rate and the degree of human mobility in a county in association with socio-demographic and location characteristics of that county, and state-wide COVID-19 policies. Combining U.S. county-level cross-sectional data from multiple sources, our model results suggested that during the study period, human mobility and infection rate in a county both influenced each other, but in an opposite direction. Metropolitan counties experienced higher infection and lower mobility than non-metropolitan counties in the early stage of the pandemic. Counties with highly infected neighboring counties and more external trips had a higher infection rate. During the study period, community mitigation strategies, such as stay at home order, emergency declaration, and non-essential business closure significantly reduced mobility whereas public mask mandate significantly reduced infection rates. The findings of this study will provide important insights to policy makers in understanding the two-way relationship between human mobility and COVID-19 spread and to derive mobility-driven policy actions accordingly.