“Quit throwing numbers at us, and tell us what they mean.”
That's what a community member told Shannon Hoskins, an epidemiologist at a rural county health department in Washington State, during a board of health meeting at the height of the Delta wave. It stopped her cold and changed how she worked.
I came across Shannon's story in Public Health from the Ground Up, a Substack newsletter I subscribe to. It's written for public health professionals, but the lessons translate directly to nonprofit data work.
Shannon had spent over a decade providing numbers. What her community needed, she realized, was the story inside them. Data was supposed to guide decision-making. But if people couldn't understand it, they couldn't use it.
Her response was practical. She started with the count — the number of people affected — before reaching for rates, trends, or comparisons. A raw count is concrete. Anyone can hold onto it. From there, she built out the fuller picture, adding context in a way communities could still follow.
She also tackled one of the trickiest challenges in small-community data work: suppression. In smaller jurisdictions, even a handful of data points can risk identifying individuals, so epidemiologists sometimes can't share certain numbers at all. That silence can breed suspicion. Communities may wonder what's being hidden and why. Shannon's approach was to have that conversation before the work even starts: explaining upfront what data will be collected, what may or may not be reportable depending on how many people are affected, and why. That way, when a number is missing from the final report, communities aren't surprised. They already know the reason. Transparency about what can't be shared, it turns out, builds as much trust as the data itself.
Out of all this, Shannon built the Local Health Data Analysis and Communication Toolkit, now in its third edition, covering everything from small numbers guidance to health disparities analysis to communications tools.
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