Racial and Ethnic Disparity During COVID-19 Pandemic in United Kingdom: A Spatial and Spatio-Temporal Analysis

Abstract

ABSTRACT The United Kingdom (UK) reported its first COVID-19 cases in late January 2020. As of 17th August 2020, the UK had reported 319,000 confirmed cases and 41,369 deaths from COVID-19. Individuals from minority racial and ethnic groups historically been victims of various forms of negligence and discrimination; accessing proper healthcare is one challenge, and this pandemic is no different. This thesis analysed COVID-19 data to explore ethnic and racial disparity in the UK. Analysis was performed to understand how COVID-19 cases spread at the regional level among different ethnic and racial groups. Spatial and spatio-temporal modelling were performed to understand the impact of ethnicity and race on COVID-19 cases using ordinary least squares (OLS) regression, geographic weighted regression (GWR), and spatio-temporal regression models. The findings show clear ethnic and racial effects on the clustering of COVID-19 cases in UK. Areas with Asian and Black populations were predicted to have higher numbers of COVID-19 cases than for the White population. These findings are important to understand the intensity of the pandemic in minority and neglected groups. Greater attention and resource allocation to the care of these groups in the UK is recommended.