No abstract

Substantial health disparities exist across race/ethnicity in the USA, with Black Americans often most affected. The current COVID-19 pandemic is no different. While there have been ample studies describing racial disparities in COVID-19 outcomes, relatively few have established an empirical link between these disparities and structural racism. Such empirical analyses are critically important to help defuse "victim-blaming" narratives about why minority communities have been badly hit by COVID-19. In this paper, we explore the empirical link between structural racism and disparities in county-level COVID-19 outcomes by county racial composition. Using negative binomial regression models, we examine how five measures of county-level residential segregation and racial disparities in socioeconomic outcomes as well as incarceration rates are associated with county-level COVID-19 outcomes. We find significant associations between higher levels of measured structural racism and higher rates of COVID-19 cases and deaths, even after adjusting for county-level population sociodemographic characteristics, measures of population health, access to healthcare, population density, and duration of the COVID-19 outbreak. One percentage point more Black residents predicted a 1.1% increase in county case rate. This association decreased to 0.4% when structural racism indicators were included in our model. Similarly, one percentage point more Black residents predicted a 1.8% increase in county death rates, which became non-significant after adjustment for structural racism. Our findings lend empirical support to the hypothesis that structural racism is an important driver of racial disparities in COVID-19 outcomes, and reinforce existing calls for action to address structural racism as a fundamental cause of health disparities.

No abstract

The transportation sector is now the primary contributor to greenhouse gas emissions in the USA. The Transportation Climate Initiative (TCI), a partnership of 12 states and the District of Columbia currently under development, would implement a cap-and-invest program to reduce transportation sector emissions across the Northeast and Mid-Atlantic region, including substantial investment in cycling and pedestrian infrastructure. Using outputs from an investment scenario model and the World Health Organization Health Economic Assessment Tool methodology, we estimate the mortality implications of increased active mobility and their monetized value for three different investment allocation scenarios considered by TCI policymakers. We conduct these analyses for all 378 counties in the TCI region. We find that even for the scenario with the smallest investment in active mobility, when it is fully implemented, TCI would result in hundreds of fewer deaths per year across the region, with monetized benefits in the billions of dollars annually. Under all scenarios considered, the monetized benefits from deaths avoided substantially exceed the direct infrastructure costs of investment. We conclude that investing proceeds in active mobility infrastructure is a cost-effective way of reducing mortality, especially in urban areas, providing a strong motivation for investment in modernization of the transportation system and further evidence of the health co-benefits of climate action.

Cities around the world are taking action to limit greenhouse gas emissions through ambitious climate targets and climate action plans. These strategies are likely to simultaneously improve local air quality, leading to public health and monetary co-benefits. We quantify and monetarily value the health impacts of eliminating emissions from the City of Boston, and in doing so, highlight the importance of considering health impacts alongside environmental impacts of local climate action. We simulated at a 4 km resolution how the elimination of anthropogenic emissions from the City of Boston would impact air quality within a 120 km by 120 km study domain. We then estimated how this change in air quality would impact a number of annual health outcomes, as well as the associated monetary savings. We found that eliminating anthropogenic emissions from Boston would result in a decline in PM2.5 concentration across the entire study region ranging from 8.5 µg m−3 in Boston to less than 1 µg m−3 elsewhere in the domain. In addition, we estimate that summer ozone would increase for the Greater Boston Area and areas west, and decrease elsewhere. The monetary impact of the change in air quality on health is estimated to be a $2.4 billion per year savings across the full domain and $1.7 billion within Suffolk County only, about 1.4% of the gross domestic product of the county. These monetary impacts are driven primarily by reduced incidence of mortality. We estimate that 288 deaths would be avoided per year across the study domain from eliminating Boston anthropogenic emissions, about six deaths avoided, annually, per 100 000 people. Within Suffolk County, we estimate that 47 deaths would be avoided per 100 000 people, around 16% of all-cause premature mortality. We also found a net decrease in cardiovascular and respiratory illness. Across the study domain, these health benefits would be disproportionately conferred upon people of color.