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.
From IndyStar
View Full Article
No entries found