Sheldon H. Jacobson is Founder Professor of Engineering in Computer Science at the University of Illinois at Urbana-Champaign.
The common theme that permeates COVID-19 vaccine safety and effectiveness communication is that policies and decisions are science-based and data-driven. Unfortunately, data literacy is not ubiquitous, making it difficult to explain data-driven decisions. Data literacy requires a basic understanding of data measures, how they are computed, and how they can be used to inform decisions.
What can data scientists do to overcome such headwinds when communicating a data-driven message? All data communicated must be framed in the appropriate context. High-level data is often too coarse to personally touch people, who are interested in themselves and their own self-interests. Focusing, for example, on different age group and gender cohorts and communicating what the data says about them can be more meaningful and have more impact.
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