Racial Segregation, Testing Site Access, and COVID-19 Incidence Rate in Massachusetts, USA.

Tao Hu,Changzhen Wang,Xinyue Ye,Regina Liu,Han Yue,Bing She,Shuming Bao,Weihe Wendy Guan,Xinyan Zhu

doi:10.3390/ijerph17249528

Abstract

The U.S. has merely 4% of the world population, but contains 25% of the world’s COVID-19 cases. Since the COVID-19 outbreak in the U.S., Massachusetts has been leading other states in the total number of COVID-19 cases. Racial residential segregation is a fundamental cause of racial disparities in health. Moreover, disparities of access to health care have a large impact on COVID-19 cases. Thus, this study estimates racial segregation and disparities in testing site access and employs economic, demographic, and transportation variables at the city/town level in Massachusetts. Spatial regression models are applied to evaluate the relationships between COVID-19 incidence rate and related variables. This is the first study to apply spatial analysis methods across neighborhoods in the U.S. to examine the COVID-19 incidence rate. The findings are: (1) Residential segregations of Hispanic and Non-Hispanic Black/African Americans have a significantly positive association with COVID-19 incidence rate, indicating the higher susceptibility of COVID-19 infections among minority groups. (2) Non-Hispanic Black/African Americans have the shortest drive time to testing sites, followed by Hispanic, Non-Hispanic Asians, and Non-Hispanic Whites. The drive time to testing sites is significantly negatively associated with the COVID-19 incidence rate, implying the importance of the accessibility of testing sites by all populations. (3) Poverty rate and road density are significant explanatory variables. Importantly, overcrowding represented by more than one person per room is a significant variable found to be positively associated with COVID-19 incidence rate, suggesting the effectiveness of social distancing for reducing infection. (4) Different from the findings of previous studies, the elderly population rate is not statistically significantly correlated with the incidence rate because the elderly population in Massachusetts is less distributed in the hotspot regions of COVID-19 infections. The findings in this study provide useful insights for policymakers to propose new strategies to contain the COVID-19 transmissions in Massachusetts.

Highlights

Since its outbreak in January, the COVID-19 pandemic has severely impacted socioeconomic activities throughout the world
Results show that people who are Black, American Indian, or live in low-income households are more likely to have conditions associated with increased risk of illness from COVID-19, compared to those who are White or have a higher income, respectively
The COVID-19 incidence rate varies across different sociodemographic groups at the city/town level

Summary

Introduction

Since its outbreak in January, the COVID-19 pandemic has severely impacted socioeconomic activities throughout the world. The United States is the leading country with 2,671,220 confirmed cases and 127,858 deaths [1]. Social distancing is one of the most effective ways to reduce COVID-19 infection, but due to residential segregation—the separation of people based on income and/or race—some individuals from specific ethnic minority groups cannot practice social distancing. They are often found in overcrowded urban housing areas, which make physical distancing and self-isolation difficult. This leads to an increased risk for the spread of COVID-19 [2]. It is necessary to integrate social-economic information and disease statistics to help analyze and understand the spread of COVID-19

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