Pandemic Open Data: Blessing or Curse?

Abstract

The SARS-CoV-2 pandemic spawned an abundance of open data originally collected by local public health agencies, then aggregated, enriched, and curated by higher-level jurisdictions as well as private corporations such as the news media. The COVID-19 datasets often contain geospatial references making them amenable to being presented cartographically as part of map-centered dashboards. Pandemic open data have been a blessing in that they enabled independent scientists and citizen researchers to verify official proclamations and published narratives related to COVID. In this chapter, however, we demonstrate that these data also are cursed with serious issues around variable definitions, data classification, and sampling methods. We illustrate how these issues interfere with unbiased public health insights and instead support narratives such as the “pandemic of the unvaccinated.” Nevertheless, open data can serve as a tool to counter dominant narratives and state-sanctioned misinformation. To advance this purpose, we need to demand disaggregated data with transparent metadata and multiple classification schemes.