A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research

• Published in: Data (Basel) Vol. 5; no. 4; p. 118
• Main Authors: Sha, Dexuan, Malarvizhi, Anusha Srirenganathan, Liu, Qian, Tian, Yifei, Zhou, You, Ruan, Shiyang, Dong, Rui, Carte, Kyla, Lan, Hai, Wang, Zifu, Yang, Chaowei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2020
• Subjects: big data; Coronaviruses; COVID-19; Data collection; Data warehouses; Decision analysis; Decision making; Economic analysis; Economic conditions; Housing; Human behavior; Impact analysis; International trade; Outbreaks; policy stringency; public health; Public policy; Quality control; Social factors; Socioeconomic data; Socioeconomic factors; Spatial resolution; spatiotemporal data; Standard data; state level; Stock exchanges; USA; United States > US; China; Europe
• ISSN: 2306-5729; 2306-5729
• DOI: 10.3390/data5040118

The outbreak of COVID-19 from late 2019 not only threatens the health and lives of humankind but impacts public policies, economic activities, and human behavior patterns significantly. To understand the impact and better prepare for future outbreaks, socioeconomic factors play significant roles in (1) determinant analysis with health care, environmental exposure and health behavior; (2) human mobility analyses driven by policies; (3) economic pressure and recovery analyses for decision making; and (4) short to long term social impact analysis for equity, justice and diversity. To support these analyses for rapid impact responses, state level socioeconomic factors for the United States of America (USA) are collected and integrated into topic-based indicators, including (1) the daily quantitative policy stringency index; (2) dynamic economic indices with multiple time frequency of GDP, international trade, personal income, employment, the housing market, and others; (3) the socioeconomic determinant baseline of the demographic, housing financial situation and medical resources. This paper introduces the measurements and metadata of relevant socioeconomic data collection, along with the sharing platform, data warehouse framework and quality control strategies. Different from existing COVID-19 related data products, this collection recognized the geospatial and dynamic factor as essential dimensions of epidemiologic research and scaled down the spatial resolution of socioeconomic data collection from country level to state level of the USA with a standard data format and high quality.