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

Remo DiSalvatore, Sarah K. Bauer, Jeong Eun Ahn () and Kauser Jahan
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Remo DiSalvatore: Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, USA
Sarah K. Bauer: Department of Environmental and Civil Engineering, Mercer University, Macon, GA 31207, USA
Jeong Eun Ahn: Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, USA
Kauser Jahan: Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, USA

IJERPH, 2023, vol. 20, issue 13, 1-15

Abstract: 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.

Keywords: COVID-19; index; virology; pandemic; vulnerability; public health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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