"Missing/Unspecified": Demographic Data Visualization During the COVID-19 Pandemic. (January 2021)

• Record Type: Journal Article
• Authors: Atherton, Rachel
• Other Names: Frith Jordan guest-editor.
• Is Part Of: Journal of business and technical communication. Volume 35:Number 1(2021)
• Page Start: 80
• Page End: 87
• Publication Date: 2021-01
• Subjects: data visualization -- COVID-19 -- social justice -- race -- ethnicity -- demographic data; Business communication -- Periodicals; Communication of technical information -- Periodicals; 658.45
• DOI: 10.1177/1050651920957982
• Languages: English
• ISSNs: 1050-6519

Abstract

While data 1 has shown that COVID-19 disproportionately affects Black people, the CDC's early data listed race as "missing/unspecified" at high rates. Incomplete demographic data obscures the virus's full impact on marginalized communities. Without more information about who the virus is affecting and how, we cannot protect our most vulnerable. This article demonstrates disconnects between reported datasets and data visualizations in public-facing COVID health and science communication and suggests steps that technical and professional communicators can take in creating or using data visualizations accurately and ethically to describe COVID conditions and impacts.