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.

中文翻译：

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“缺失/未指定”：COVID-19 大流行期间的人口统计数据可视化

虽然数据 1 显示 COVID-19 对黑人的影响不成比例，但 CDC 的早期数据将种族列为“缺失/未指定”的比率很高。不完整的人口统计数据掩盖了病毒对边缘化社区的全面影响。如果没有关于病毒影响谁以及如何影响的更多信息，我们就无法保护我们最脆弱的人。本文展示了面向公众的 COVID 健康和科学传播中报告的数据集和数据可视化之间的脱节，并建议了技术和专业传播者在准确和合乎道德地创建或使用数据可视化来描述 COVID 条件和影响时可以采取的步骤。