Analyzing Spatial-Temporal Impacts of Neighborhood Socioeconomic Status Variables on COVID-19 Outbreaks as Potential Social Determinants of Health

Abstract

The COVID-19 pandemic is not only a medical disease outbreak but also a social inequality and health disparity problem. This study analyzed dynamic temporal and spatial associations between confirmed COVID-19 cases and socioeconomic status (SES) variables at the neighborhood level with three case studies to (1) analyze five temporal stages in the County of San Diego, California; (2) compare six U.S. metropolitan areas; and (3) compare SES associations across two spatial scales (counties and zip code units). We identified eleven SES variables as potential contributors to the social determinants of health that influence COVID-19 outbreaks and showed how their correlation coefficients vary over five phases. We found that changes in COVID-19 hot spots and clusters are minimal across the five stages. The consistent spatial patterns through the five outbreak periods imply that the place effects associated with fundamental health disparity factors are persistent and not easily changed. The impact of COVID-19 on SES varies in different local contexts. We also found that Hispanic populations, uninsured groups, Spanish-speaking families, those with less than a ninth-grade education level, and high household densities strongly correlated with COVID-19 cases in all six metropolitan areas. We did not find high scale dependency in SES association patterns between county and zip code spatial units, but analysis at a finer level can provide more association patterns.

COVID-19不仅是疾病的一次爆发, 也是社会不平等和健康差异的问题。本文分析了COVID-19确诊病例与社区水平的社会经济地位因素的动态时空关联。本文研究三个案例：（1）分析了美国加利福尼亚州圣地亚哥县的五个时间段, （2）比较了美国六个大都市区, （3）比较了两个空间尺度（县和邮政编码）的社会经济地位关系。我们确定了11个社会经济地位因素, 作为影响健康的社会因素。这些社会经济地位因素影响了COVID-19的爆发, 展示了它们的相关系数在五个阶段的变化情况。我们发现, COVID-19热点区和聚合区在五个阶段中的变化最小。空间模式在五个爆发期的一致性, 揭示了与健康差异因素相关的地方效应, 是持久的、不易改变的。COVID-19对社会经济地位的影响因地而异。我们还发现, 在六个大都市区, 拉美裔人口、无保险群体、西班牙语家庭、低于九年教育水平的家庭、高密度家庭, 与COVID-19病例密切相关。我们没有发现县和邮政编码空间单元之间在社会经济地位关联模式上的高度依赖性, 但更精细的分析可以揭示更多的关联模式。

La pandemia del COVID-19 no solo ha sido un brote de enfermedad médica sino también un problema de desigualdad social y disparidad sanitaria. El presente estudio analizó las asociaciones dinámicas temporales y espaciales entre los casos confirmados de COVID-19 y las variables referidas al estatus socioeconómico (SES), a nivel de vecindario, en tres estudios de caso para (1) analizar cinco etapas temporales en el condado de San Diego, California; (2) comparar seis áreas metropolitanas de EE.UU.; y (3) comparar las asociaciones del SES a través de dos escalas espaciales (condados y unidades de código zip). Identificamos once variables SES como potenciales contribuyentes a los determinantes sociales de salud que influyen en los brotes del COVID-19, y mostramos cómo varían estos coeficientes de correlación a lo largo de cinco fases. Hallamos que los cambios en los puntos calientes y conglomerados del COVID-19 son mínimos a través de las cinco fases. Los patrones espaciales consistentes a través de cinco períodos del brote de contagio implican que los efectos de lugar asociados con los factores fundamentales de disparidad sanitaria son persistentes y no fáciles de modificar. El impacto del COVID-19 sobre el SES varía en los diferentes contextos locales. Descubrimos además que las poblaciones hispánicas, los grupos sin seguro, las familias hispanohablantes, las personas con niveles educativos por debajo del grado noveno y las altas densidades de hogares están fuertemente correlacionados con los casos de COVID-19 en todas las seis áreas metropolitanas. No se encontró una alta dependencia de escalas en los patrones de asociación del SES entre las unidades espaciales de condado y código zip, pero el análisis a un nivel más fino puede proveer más patrones de asociación.

Key Words:

• COVID-19
• GIS
• health disparity
• social determinants of health
• spatial analysis

关键词:

• COVID-19
• 地理信息系统
• 健康差异
• 健康的社会决定因素
• 空间分析。

Palabras clave:

• análisis espacial
• COVID-19
• determinantes sociales de la salud
• disparidad sanitaria
• SIG

Acknowledgments

Thanks to the staff and epidemiologists in the County of San Diego, Health and Human Services Agency, Public Health Services, Epidemiology and Immunization Services Branch, and Community Health Statistics Unit for the creation of the public COVID-19 data sharing Web site and review suggestions. Thanks for insightful comments and suggestions from anonymous reviewers and Dr. Ling Bian.

Additional information

Notes on contributors

Ming-Hsiang Tsou

MING-HSIANG TSOU is a Professor in the Department of Geography, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. He is also the Director of the Center for Human Dynamics in the Mobile Age. His research interests are in human dynamics, social media, big data, visualization, Internet mapping, Web GIS, mobile GIS, cartography, and K–12 GIS education.

Jian Xu

JIAN XU is a Joint Doctoral Program Student in Geographic Information Science in the Department of Geography, San Diego State University, San Diego, CA 92182, and the University of California, Santa Barbara. E-mail: [email protected]. His research focuses on big data and social media analytics.

Chii-Dean Lin

CHII-DEAN LIN is a Professor and Associate Chair in Statistics in the Department of Mathematics & Statistics, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. His research areas include statistical computing, longitudinal data analysis, spatial-temporal statistics, mixed modeling, statistical methodologies in clinical trials, and global optimization.

Morgan Daniels

MORGAN DANIELS is a Master’s Student in Statistics in the Department of Mathematics & Statistics, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. Her research focuses on spatial-temporal statistics.

Jessica Embury

JESSICA EMBURY is a Master’s Student in the Department of Geography Geographic Information Science program, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. Her research focuses on spatial modeling and geocomputation as applied to the study of human dynamics and mobility, social equity, public health, and food security.

Jaehee Park

JAEHEE PARK is a Joint Doctoral Program Student in Geographic Information Science in the Department of Geography, San Diego State University, San Diego, CA 92182, and the University of California, Santa Barbara. E-mail: [email protected]. Her research focuses on big data and social media analytics.

Eunjeong Ko

EUNJEONG KO is a Professor in the School of Social Work, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. Her research areas include preventive health-seeking behaviors, and racial and ethnic disparities in accessing and utilizing health services.

Joseph Gibbons

JOSEPH GIBBONS is an Associate Professor in the Department of Sociology, San Diego State University, San Diego, CA 92182. E-mail: [email protected]. His research centers on how forces of ethnoracial inequality in the form of residential segregation and gentrification affect individual health and healthy behaviors.