A micro-level analysis of commuting and urban land using the Simpson's index and socio-demographic factors

This study explores the association between urban form, socio-demographics, and travel behavior for 1990, 2000, and 2010 in Shelby County, Tennessee, at a micro-level using U.S. Census tracts capturing active and passive transportation modes. We used bivariate correlations between land use and land cover mix (estimated separately by Simpson's index), population, race, age, education, and commuting modes. Major findings indicate that land use mix is positively related to public transportation use while the land cover mix is negatively related;the opposite is found for both diversity measures and working from home. Greater land cover diversity discourages walking and biking and encourages car commuting;Blacks are the majority who use public transportation;older travelers are more likely to use transportation alternatives;higher-educated people tend to work from home or commute by bike. This study helps city planners in designing sustainable cities and increasing active modes use. Understanding travel patterns may help policymakers to control local/regional problems like increasing traffic congestions and emissions due to a modal shift in commuting to a private car during a COVID-19 pandemic, as well as develop strategies for encouraging active modes and public transport use in the post-COVID-19 world.

Analysis of the COVID-19 impacts on employment and unemployment across the multi-dimensional social disadvantaged areas.

This is the study of economic impacts in the context of social disadvantage. It specifically considers economic conditions in regions with pre-existing inequalities and examines labor market outcomes in already socially vulnerable areas. The economic outcomes remain relatively unexplored by the studies on the COVID-19 impacts. To fill the gap, we study the relationship between the pandemic-caused economic recession and vulnerable communities in the unprecedented times. More marginalized regions may have broader economic damages related to the pandemic. First, based on a literature review, we delineate areas with high social disadvantage. These areas have multiple factors associated with various dimensions of vulnerability which existed pre-COVID-19. We term these places "multi-dimensional social disadvantaged areas". Second, we compare employment and unemployment rates between areas with high and low disadvantage. We integrate geospatial science with the exploration of social factors associated with disadvantage across counties in Tennessee which is part of coronavirus "red zone" states of the US southern Sunbelt region. We disagree with a misleading label of COVID-19 as the "great equalizer". During COVID-19, marginalized regions experience disproportionate economic impacts. The negative effect of social disadvantage on pandemic-caused economic outcomes is supported by several lines of evidence. We find that both urban and rural areas may be vulnerable to the broad social and economic damages. The study contributes to current research on economic impacts of the COVID-19 outbreak and social distributions of economic vulnerability. The results can help inform post-COVID recovery interventions strategies to reduce COVID-19-related economic vulnerability burdens.