Your browser doesn't support javascript.
loading
Racial segregation, testing sites access, and COVID-19 incidence rate in Massachusetts, USA
Tao Hu; Han Yue; Changzhen Wang; Bing She; Xinyue Ye; Regina Liu; Xinyan Zhu; Shuming Bao.
Affiliation
  • Tao Hu; Center for Geographic Analysis, Harvard University
  • Han Yue; Geocomputation Center for Social Science, Wuhan University
  • Changzhen Wang; Department of Geography and Anthropology, Louisiana State University
  • Bing She; University of Michigan, Ann Arbor
  • Xinyue Ye; Department of Landscape Architecture and Urban Planning, Texas A&M University
  • Regina Liu; Department of Biology, Mercer University
  • Xinyan Zhu; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University
  • Shuming Bao; China Data Institute, Ann Arbor
Preprint in English | medRxiv | ID: ppmedrxiv-20146787
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See journal article
ABSTRACT
The U.S. has merely 4% of the world population but 25% of the worlds COVID-19 cases. Massachusetts has been in the leading position of total cases since the outbreak in the U.S. 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 sites 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 COIVD-19 infections among minority; 2) The Black has the shortest drive time to testing sites, followed by Hispanic, Asian, and Whites. The drive time to testing sites is significantly negatively associated with the COVID-19 incidence rate, implying the importance of testing location being accessed 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 previous studies, elderly population rate is not statistically significant with incidence rate because the elderly population in Massachusetts is less distributed in the hot spot 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.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study Language: English Year: 2020 Document type: Preprint
...