It’s not that mathematicians have no clue of astrophysics, but that they aren’t working in that area and understanding the field enough to contravene decisions made by astrophysicists.

There’s a rationale around what is, and is not, included in case definitions and included in dashboards. It’s likely that these decisions are made by epidemiologists with not only specific training, but also access to much more data than the person who builds the dashboards.

Making a decision to include data in a visualization without understanding why is not a good idea because it’s common that people think they know what numbers mean, but only because they have limited visibility.

Having a degree in data science doesn’t mean that I’m a data scientist. If I’m hired in a web dev role, then I hope my input is received well and considered by epidemiologists in charge. And I hope they’d be able to spend time explaining the rationale behind their decisions.

This seems like a similar analogy where the build engineer decides to change the git repo because they know better than the dev team. Then someone reading the article says “well they have a PhD in computer science so they should know what they’re doing, it’s simple.”