Development of a COVID-19 Vulnerability Index (CVI) for the Counties and Residents of New Jersey, USA.

The coronavirus disease 2019, or COVID-19, has impacted countless aspects of everyday life since it was declared a global pandemic by the World Health Organization in March of 2020. From societal to economic impacts, COVID-19 and its variants will leave a lasting impact on our society and the world. During the height of the pandemic, it became increasingly evident that indices, such as the Center for Disease Control's (CDC) Social Vulnerability Index (SVI), were instrumental in predicting vulnerabilities within a community. The CDC's SVI provides important estimates on which communities will be more susceptible to 'hazard events' by compiling a variety of data from the U.S. Census and the American Community Survey. The CDC's SVI does not directly consider the susceptibility of a community to a global pandemic, such as the COVID-19 pandemic, due to the four themes and 15 factors that contribute to the index. Thus, the objective of this research is to develop a COVID-19 Vulnerability Index, or CVI, to evaluate a community's susceptibility to future pandemics. With 15 factors considered for CDC's SVI, 26 other factors were also considered for the development of the CVI that covered themes such as socioeconomic status, environmental factors, healthcare capacity, epidemiological factors, and disability. All factors were equally weighted to calculate the CVI based on New Jersey. The CVI was validated by comparing index results to real-world COVID-19 data from New Jersey's 21 counties and CDC's SVI. The results present a stronger positive linear relationship between the CVI and the New Jersey COVID-19 mortality/population and infection/population than there is with the SVI. The results of this study indicate that Essex County has the highest CVI, and Hunterdon County has the lowest CVI. This is due to factors such as disparity in wealth, population density, minority status, and housing conditions, as well as other factors that were used to compose the CVI. The implications of this research will provide a critical tool for decision makers to utilize in allocating resources should another global pandemic occur. This CVI, developed through this research, can be used at the county, state, and global levels to help measure the vulnerability to future pandemics.

Reevaluation of the global warming impacts of algae-derived biofuels to account for possible contributions of nitrous oxide.

The environmental impacts of algae biofuels have been evaluated by life-cycle assessment (LCA); however, these analyses have overlooked nitrous oxide (N2O), a potent greenhouse gas. A literature analysis was performed to estimate algal N2O emissions and assess the impacts of growth conditions on flux magnitudes. Nitrogen source and dissolved oxygen concentration were identified as possible key contributors; therefore, their individual and combined impacts were evaluated using bench-scale experiments. It was observed that maximum N2O emissions (77.5µg/galgae/day) occur under anoxic conditions with nitrite. Conversely, minimum emissions (6.25µg/galgae/day) occur under oxic conditions with nitrate. Aggregated N2O flux estimates were then incorporated into a LCA framework for algae biodiesel. Accounting for "low" N2O emissions mediated no significant increase (<1%) compared to existing GWP estimates; however, "high" N2O emissions mediate an increase of roughly 25%, potentially jeopardizing the anticipated economic and environmental performances of algae biofuels.