African Americans and COVID-19: Beliefs, behaviors and vulnerability to infection

COVID-19-Related Financial Hardship Is Associated With Depression and Anxiety in Substance Use Treatment Across Gender and Racial Groups

ABSTRACT

Many individuals lost their employment during the COVID-19 pandemic and experienced financial hardship. These experiences may increase risk for co-occurring conditions, including substance use disorders (SUDs) and related symptoms of depression and anxiety. This study aimed to examine the associations between COVID-19-related financial hardship and/or job loss and co-occurring symptoms, across gender and racial groups. Respondents (N = 3493) included individuals entering SUD treatment in the United States in March-October of 2020. Results demonstrated that COVID-19-related financial hardship and unemployment in the household was associated with greater depression and anxiety severity among people in SUD treatment (p's < 0.05). Our findings highlight financial hardship and loss of employment as risk factors for co-occurring depression and anxiety. However, additive effects between marginalized identity status and COVID-19 economic hardship on co-occurring symptoms were not observed.

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.

Environmental Health Literacy as Knowing, Feeling, and Believing: Analyzing Linkages between Race, Ethnicity, and Socioeconomic Status and Willingness to Engage in Protective Behaviors against Health Threats

This study investigates the relationships between environmental health literacy, the characteristics of people (race, ethnicity, and socioeconomic status) associated with health disparities, and people's willingness to engage in protective behaviors against environmental health threats. Environmental health literacy is a framework for capturing the continuum between the knowledge of environmental impacts on public health, and the skills and decisions needed to take health-protective actions. We pay particular attention to three dimensions of environmental health literacy: factual knowledge (knowing the facts), knowledge sufficiency (feeling ready to decide what to do), and response efficacy (believing that protective behaviors work). In June 2020, we collected survey data from North Carolina residents on two topics: the viral infection COVID-19 and industrial contaminants called per- and polyfluoroalkyl substances (PFAS). We used their responses to test stepwise regression models with willingness to engage in protective behaviors as a dependent variable and other characteristics as independent variables, including environmental health literacy. For both topics, our results indicated that no disparities emerged according to socioeconomic factors (level of education, household income, or renting one's residence). We observed disparities in willingness according to race, comparing Black to White participants, but not when comparing White to American Indian, Alaska Native, Asian, Native Hawaiian, or Pacific Islander participants nor Hispanic to non-Hispanic participants. The disparities in willingness between Black and White participants persisted until we introduced the variables of environmental health literacy, when the difference between these groups was no longer significant in the final regression models. The findings suggest that focusing on environmental health literacy could bridge a gap in willingness to protect oneself based on factors such as race/ethnicity and socioeconomic status, which have been identified in the environmental health literature as resulting in health disparities.