100 weeks ago, I wrote the first issue of this newsletter on Substack.
I wrote about a change in hospitalization data, which had just shifted from the purview of the CDC to a different team at the Department of Health and Human Services (HHS). This felt like a niche topic at the time, but I wanted to provide a clear explanation of the change after seeing some misleading articles and social media posts suggesting that the CDC was losing control of all COVID-19 data.
At the time, my goals were simple: explain where COVID-19 data come from and how to interpret the numbers; provide tips and resources for other reporters on this complicated beat; and help people in my broader social network understand pandemic trends. The COVID-19 Data Dispatch’s aims haven’t changed too much, even as I’ve expanded it to its own website, worked with guest writers, coordinated events, and more.
As I look back on 100 issues, I wanted to share a few lessons for other reporters still on the COVID-19 beat (and, more broadly, anyone working on public health communications). I’m also sharing a couple of notes from readers about how the publication has helped them.
Lessons I’ve learned:
- Lay readers can handle complicated topics! You don’t need to overly simplify things, just use clear language and examples that are easy to follow. This is honestly my entire ethos as a science writer so I found it hard to pick an example post, but one may be my piece on why U.S. Long COVID research is so difficult, which built on reporting for a Grid feature.
- FAQs are good formats for breaking down complex topics or new information. I like to use FAQ formats and lots of subheaders whenever I’m writing about a new variant (or subvariant) of concern, like this post on BA.4 and BA.5, or when walking through the implications of a federal guidance change, like this post discussing testing and isolation with the Omicron variant.
- Consistency is key. One thing I frequently hear from readers is that they appreciate the regularity of COVID-19 Data Dispatch issues; if they tune out of other pandemic news, they can still expect me to deliver some important updates once a week. This is definitely a built-in advantage of the newsletter format, but I try to take the consistency further by having regular sections (such as “National numbers”) with statistics reported in a similar way each week.
- Emphasizing the same issues over and over can feel repetitive to the writer, but it’s helpful for readers. Whenever I remind readers about holiday data reporting lags, for example, I have to remind myself that most people are not constantly thinking about COVID-19 trends the way that I am—and might not be consistently reading my newsletters, either. It’s another aspect of being consistent.
- Provide trends and context, not just isolated numbers. This is another key aspect of my “National numbers” updates: I always explain how a given week’s case or hospitalization numbers compare to previous weeks. Another important piece of context, I think, is where numbers come from: for example, reminding readers that case numbers mainly include PCR test results, not at-home antigen test results.
- Acknowledge uncertainty! This is crucial in any kind of data reporting, especially when reporting from data systems that are as flawed and incomplete as the U.S.’s COVID-19 data systems. For example, last month’s post about interpreting limited data during our undercounted surge explains the limitations of several common sources, as well as what the sources can still tell us.
- Provide readers with tools to see local data. This is a central reason why so many publications built COVID-19 dashboards in 2020, and why some outlets continue to maintain them now. People love to look up their states or counties! I often don’t have the bandwidth for hyperlocal visualizations myself, but point to these resources in “Featured sources” updates whenever possible.
- Use readers’ questions to drive reporting. Some of my favorite COVID-19 Data Dispatch posts have been inspired by reader questions, from the “Your Thanksgiving could be a superspreader” post in fall 2020 to my explanation of why the CDC’s isolation guidance is not based on scientific evidence earlier this spring. If you write to me with a question, you’re probably not the only person with that question—at least, if my metrics on these posts are anything to go by.
Testimonials from readers:
Josh Zarrabi (software engineer at the Health Equity Tracker): “You’re, like, the only COVID news I get anymore. Every Sunday morning with my coffee.”
Chris Persaud (data reporter, Palm Beach Post): “Thanks to your newsletter, I’ve found useful data for my news reports.”
Jeremy Caplan (director of Teaching & Learning at Newmark J School): “COVID-19 Data Dispatch is consistently informative. I limit my COVID news diet, so it’s helpful to have this singularly focused resource for keeping up with the data.”
My Grandma: “In our Berkeley family (C, P and me) we have relied on you and your newsletter for helping us through these difficult times. The research, guidance and advice in your Data Dispatch, is invaluable.”
Thank you to all of my readers for your support over the last 100 weeks. I hope the COVID-19 Data Dispatch can continue to provide you with the news and resources you need to navigate the (continuing!) pandemic.
And of course, if you’d like to support this work, consider setting up a reoccurring donation or buying me a coffee!