Will the economic growth benefit public health? Health vulnerability, urbanization and COVID-19 in the USA

Abstract

Economic growth has a significant impact on health vulnerability primarily through the process of urbanization. This paper conducts a pioneer study by analyzing the impact of regional economic growth and urbanization on the public health vulnerability in the 51 states and territories of the USA from 2011 to 2018 with a fixed-effect panel data regression model. We construct an epidemiological vulnerability index (EVI) using regional smoking, diabetes, obesity, and hypertension, collect CDC social vulnerability index (SVI) as state-level public health vulnerability status, and use COVID-19 to test the actual effect of health vulnerability. The preliminary results show that higher regional economic growth is related to lower EVI and SVI, while urbanization is positively associated with regional health vulnerability and the severity of COVID-19 from case rate and death rate. Robustness check with unemployment shows the same result. We conclude that economic growth is related to lower public health vulnerability, and urbanization has negative public health benefits. Our finding indicates an urgent need to balance the externalities generated by economic development and urbanization trends on public health vulnerability by promoting reasonable medical resource distribution, health practices and safety, improving social and environmental justice, and other health management measures. Supplementary Information The online version contains supplementary material available at 10.1007/s00168-021-01103-9.

Does money buy health? evaluation of stock market performance and economic growth in the wake of the COVID-19 pandemic

“…Fiscal economic reforms, including financial reforms on long-term spending, improved healthcare outcomes, increased life satisfaction, and increased government trust [ 30 ]. The current literature is related to the vulnerability of the coronavirus to different sectors, including renewable energy [ 31 ], higher education [ 32 ], environmental quality [ 33 ], public health [ 34 ], SMEs [ 35 ], and the stock return of pharmaceutical companies [ 36 ]. These studies, in general, concluded that economic activity was mainly depressed during the wake of the COVID-19 pandemic; hence, it is imperative to minimize coronavirus cases to support growth-driven activities worldwide.…”

“…Second, reported death-to-total cases and recovered-to-total cases are used as mediating factors in financial modelling to assess how the investor’s confidence fluctuates with the increase and decrease of coronavirus cases. The earlier studies were unable to judge the investor’s confidence that changed with the greater frequency of pandemics in large settings of countries [ 34 , 54 , 55 ], and…”

The sources of the Kuznets relationship between the COVID-19 mortality rate and economic performance

“…Kentikelenis et al [ 14 ] and Vignier and Bouchaud [ 15 ] pointed out that travel and migration are particularly at risk of developing severe infectious diseases during the economic downturn. Fan et al [ 16 ] found that economic development reduces the COVID-19 vulnerability. Zilidis et al [ 17 ] suggested that economic crisis has a significant impact on the mortality rate of infectious diseases, but the impact varied by the type of infectious diseases.…”

“…Second, there have been several empirical investigations into the relationship between the infectious disease mortality rate and economic performance, such as Cutler et al [ 11 ]; Rechel et al [ 9 ]; Hunter et al [ 10 ]; and Fan et al [ 16 ]. While these studies have enriched our understanding of the association between infectious disease mortality rates and economic performance, the mechanism by which economic performance influences this relationship remains unclear.…”

“…This is because the number of mortalities is limited to non-negative integer values, positively skewed, and can have a zero count. Therefore, estimation with other regression techniques, such as ordinary least squares [ 11 , 16 , 21 , 22 ], generalized additive regression [ 10 ], and autoregressive integrated moving average model [ 17 ], are not appropriate to model this sort of data. Therefore, this study suggests using the negative binomial regression technique to address this problem and obtain a more accurate estimation.…”