Stigma and health inequality experienced by ethnic minorities during the COVID-19 pandemic in a Chinese community: an implication to health policymakers.

Introduction: Ethnic minorities are considered one of the most vulnerable groups during the COVID-19 pandemic. However, the explanatory pathway of how their disadvantaged experiences during epidemics are related to the embedded and longstanding stigmas against them and how these embedded stigmas can affect their resilience in disease outbreaks are not well understood. This study investigated the experiences of ethnic minorities in the COVID-19 pandemic, and how their experiences were related to the embedded stigma toward them. Methods: This study adopted a qualitative approach, interviewed 25 individuals (13 women and 12 men) from ethnic minority groups residing in Hong Kong from August 2021 to February 2022 in a semi-structured format. Thematic analysis was conducted to analyze the data. Results: The participants were isolated and stereotyped as infectious during the COVID-19 pandemic at community and institutional levels. Their experiences did not occur suddenly during the pandemic but were embedded in the longstanding segregation and negative stereotypes toward ethnic minorities in different aspects of life before the pandemic. These negative stereotypes affected their resilience in living and coping with the pandemic. Conclusion: The participants' experiences during the COVID-19 pandemic were mostly disadvantageous and predominantly initiated by the mainstream stigmatization toward them by the local Chinese residents and government. Their disadvantaged experiences in the pandemic should be traced to the embedded social systems, imposing structural disparities for ethnic minorities when accessing social and medical resources during a pandemic. Because of the preexisting stigmatization and social seclusion of ethnic minorities in Hong Kong, the participants experienced health inequality, which stemmed from social inequality and the power differential between them and the Chinese locals. The disadvantaged situation of the participants negatively affected their resilience to the pandemic. To enable ethnic minorities better cope with future epidemics, merely providing assistance to them during an epidemic is barely adequate, but a more supportive and inclusive social system should be established for them in the long run.

Residential Segregation as a Barrier to Covid-19 Booster Coverage in Deep South

Background: Coronavirus disease 2019 (COVID-19) had been a stronger hit in Deep South compared with other developed regions in the United States, and vaccination remains a top priority for all eligible individuals. However, there are limited data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age group, which is of critical importance for future vaccine planning. Racial/ethnic disparities were found in the COVID-19 vaccination, but the vast majority of evidence was generated from studies at the individual level. There is an urgent need for evidence at the population level to reveal and evaluate the booster coverage in racial/ethnic minority communities, which could identify vulnerable communities and inform future healthcare policymaking and resource allocation. We evaluated county-level COVID-19 booster coverage by age group in the Deep South and examined its relationship with residential segregation. Method(s): We conducted an ecological study at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of five Deep South states from December 15, 2021 to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster coverage by age group (e.g., 12 to 17 years old, 18 to 64 years old, and at least 65 years old) by the end of the study period. We examined the longitudinal relationships between residential segregation, interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson mixed model. Result(s): As of October 19, 2022, among the 418 counties, the median percentage of booster coverage was 40% (interquartile range [IQR]: 37.8-43.0%). Compared with elders, youth and adults had lower percentages of booster uptake. There was geospatial heterogeneity in the COVID-19 booster coverage. Results of the Poisson mixed model found that as time increased, higher segregated counties had lower percentages of booster coverage. Such relationships were consistent across the age groups. Conclusion(s): The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccine planning should focus on youth and adults. Healthcare facilities and resources are needed in racial/ethnic minority communities. Residential segregation and COVID-19 booster coverage by age group in the 418 counties across the five Deep South states from December 15, 2021 to October 19, 2022.

A Scientometric Review of Residential Segregation Research: A CiteSpace-Based Visualization

Residential segregation (RS) is a global phenomenon that has become an enduring and important topic in international academic research. In this review, using RS as the search term, 2520 articles from the period 1928–2022 were retrieved from the Scopus database and were visually analyzed using CiteSpace software. The results revealed the following: (1) The United States and its institutions have made outstanding contributions to RS research, while various scholars (e.g., Johnston, Massey, Forrest, Poulsen, and Iceland) have laid the foundation for RS research. (2) Mainstream RS research originates from three fields—psychology, education, and social sciences—while the trend of multidisciplinary integration is constantly increasing. (3) The research hotspots of RS include racial difference, sociospatial behavior, income inequality, mixed income communities, guest worker minorities, typical district segregation, occupational segregation, health inequalities, metropolitan ghetto, and migrant–native differential mobility. Furthermore, (4) gentrification, spatial analysis, school segregation, health disparity, immigrant, and COVID-19 have become new themes and directions of RS research. Future research should pay more attention to the impact of multi-spatial scale changes on RS as well as propose theoretical explanations rooted in local contexts by integrating multidisciplinary theoretical knowledge. © 2022 by the authors.

Socioeconomic conditions and academic performance in higher education in Colombia during the pandemic

This article studies the relationship between the socioeconomic conditions of higher education students in Colombia and their academic performance during the pandemic. The household's socioeconomic conditions are approximated by the education level of the parents, their occupation and the possession of assets. A multiple regression model tests the effect of these variables on academic performance before and during the pandemic. Results suggest that before the pandemic, the mother's graduate education and household technology assets showed a positive impact on test score. Mixed effects of parents' occupations by gender were also found. During the pandemic, the effect of the mother's education remained the same, and the effect of technological assets, in-person education and high-quality accredited establishment increased.

Aggravated social segregation during the COVID-19 pandemic: Evidence from crowdsourced mobility data in twelve most populated U.S. metropolitan areas.

The notion of social segregation refers to the degrees of separation between socially different population groups. Many studies have examined spatial and residential separations among different socioeconomic or racial populations. However, with the advancement of transportation and communication technologies, people's activities and social interactions are no longer limited to their residential areas. Therefore, there is a growing necessity to investigate social segregation from a mobility perspective by analyzing people's mobility patterns. Taking advantage of crowdsourced mobility data derived from 45 million mobile devices, we innovatively quantify social segregation for the twelve most populated U.S. metropolitan statistical areas (MSAs). We analyze the mobility patterns between different communities within each MSA to assess their separations for two years. Meanwhile, we particularly explore the dynamics of social segregation impacted by the COVID-19 pandemic. The results demonstrate that New York and Washington D.C. are the most and least segregated MSA respectively among the twelve MSAs. Since the COVID-19 began, six of the twelve MSAs experienced a statistically significant increase in segregation. This study also shows that, within each MSA, the most and least vulnerable groups of communities are prone to interacting with their similar communities, indicating a higher degree of social segregation.

Health disparity research: The new frontier of research

In 2020, the AACR's U.S. Cancer Disparities Progress Report showed that the there is still a significant gap in cancer incidence and mortality between white Americans and other racial and ethnic groups. That's not because the science hasn't progressed or because people of color are biologically predisposed to cancer. It's because the systems and structures put in place decades ago continue to harm the health of racial and ethnic minorities. Red-lining in the 1930s created segregated housing, and then the creation of the national highway system decimated majority-Black neighborhoods, leaving them treeless, polluted, and lacking healthy food and medical facilities. As a result, people living in these neighborhoods are more likely to get cancer and also more likely to die from it. So, when COVID-19 hit, many of us were not surprised that communities of color were disproportionately affected. And the current situation with COVID-19 vaccines is a great demonstration that while science is necessary for improving health, it's not sufficient. Those amazingly effective vaccines can't keep hospitals from being overwhelmed if a large chunk of the population won't get the shot, just as advances in cancer screening and treatment can't end disparities if they're predominantly going to wealthy white people. This realization has been one of our blind spots as scientists and physicians. Not only must work toward equitable access to care, but we must also work on building trust in medicine, which we do by demonstrating that we're trustworthy. There's a science to it, though we're going to have to allow for greater flexibility and messiness than we're accustomed to.

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA.

INTRODUCTION: This study's objective was to examine the association of the percentage of county population residing in concentrated disadvantage and Black-concentrated census tracts with county-level confirmed COVID-19 deaths in the USA, concentrated disadvantage and Black concentration at census tract-level measure socioeconomic segregation and racial segregation, respectively. METHODS: We performed secondary data analysis using tract (N = 73,056) and county (N = 3142) level data from the US Census Bureau and other sources for the USA. Confirmed COVID-19 deaths per 100,000 population was our outcome measure. We performed mixed-effect negative binomial regression to examine the association of county population's percentage residing in concentrated disadvantage and Black-concentrated tracts with COVID-19 deaths while controlling for several other characteristics. RESULTS: For every 10% increase in the percentage of county population residing in concentrated disadvantage and Black-concentrated tracts, the rate for confirmed COVID-19 deaths per 100,000 population increases by a factor of 1.14 (mortality rate ratio [MMR] = 1.14; 95% confidence interval [CI]:1.11, 1.18) and 1.11 (MMR = 1.11; 95% CI:1.08, 1.14), respectively. These relations stayed significant in all models in further sensitivity analyses. Moreover, a joint increase in the percentage of county population residing in racial and socioeconomic segregation was associated with a much greater increase in COVID-19 deaths. CONCLUSIONS: It appears that people living in socioeconomically and racially segregated neighborhoods may be disproportionately impacted by COVID-19 deaths. Future multilevel and longitudinal studies with data at both individual and aggregated tract level can help isolate the potential impacts of the individual-level characteristics and neighborhood-level socioeconomic and racial segregation with more precision and confidence.