Some figures look impressive — but mislead more than they inform.
Cumulative case curves without population context.
– Case fatality rates shown without age stratification.
– Maps colored by raw counts instead of incidence.
– Models presented without uncertainty intervals.
The problem is not the data.
The problem is interpretation.
A single figure can shape public perception, policy decisions, and media narratives.
And yet, figures are often consumed quickly, without asking critical questions:
– What is the denominator?
– What time frame is being used?
– Who is missing from the data?
– How much uncertainty is hidden?
Learning epidemiology is not just about producing analyses.
It’s about reading them critically — including your own.
Before trusting a figure, pause for a moment.
The most important information is often what’s not shown