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Christophe De Greift identifies the problem of low data literacy and shares four rules that can improve statistical data during COVID-19 and our understanding of the situation. 

The world was caught off guard by a new virus that we are still trying to understand. If we turn to official sources to find answers to our questions, we often find graphics that are not very relevant and even misleading about COVID-19. In the era of artificial intelligence and predictive analytics, we continue to suffer from low data literacy in institutions and circumstances where decision-making based on reliable data should take precedence…

Hoping to see a rapid improvement in the official sources of communication on the health situation, I recall below some basic quality criteria for statistical communication, and I illustrate each criterion with an example recently found in official sources – anonymous so as not to hurt sensitivities – as well as a proposal for improvement.

The four rules covered are:

• Key questions
• Comparisons
• Interpretation
• Building Indicators

Read the full article, 4 Rules to Improve Our Statistical Communication in COVID-19 Time, on Christophe’s blog.