How to Read Pandemic Research Papers: Tips for Understanding Technical Language, Biostatistics, and Hierarchy of Evidence

Just because it’s published, that doesn’t mean it’s valid.

René F. Najera, MPH, DrPH

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No, your blood type does not determine your risk of COVID-19 infection and disease. (Photo by Obi — @pixel7propix on Unsplash)

If you only have a minute…

This blog post provides tips for reading pandemic research papers. It suggests familiarizing yourself with the technical language of epidemiological research, understanding basic biostatistics, and knowing the hierarchy of evidence. It also warns against pre-prints and reminds readers that individual experiences may differ from group findings. The post concludes by recommending consulting a licensed healthcare provider with questions about how researched therapies apply to specific conditions you may have (or are just curious about).

Okay, so you do have more than a minute…

As the COVID-19 pandemic recedes, and the Public Health Emergency of International Concern has been declared over, researchers are taking the time to look at all the data collected during the pandemic. They are analyzing billions/trillions of gigabytes of data, and will be writing hundreds of thousands of papers for academic journals for years to come. Talking heads on television — and disembodied voices on radio and podcasts — will interpret all these papers for you. However, it doesn’t hurt to read those papers yourself, read the evidence, and be more informed about the research that will likely inform future pandemic responses. In fact, learning to read the articles and getting all you can from them will make you more informed as a citizen, parent, customer, etc.

Familiarize Yourself With the Lexicon of Epidemiological Research

By design, research journal articles are written in highly technical language. As an author, you want your terms to be standard across the different sciences. For example, “bias” means a factor or factors that could contribute to your findings, but not necessarily because they’re a cause of the effect you’re seeing. It doesn’t mean the researchers were biased toward the study participants (hopefully). A “confounder” is a factor that influences the observed link between a cause and an effect…

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René F. Najera, MPH, DrPH

DrPH in Epidemiology. Associate/JHBSPH. Adjunct/GMU. Epidemiologist. Father. Husband. (He/Him/His/El)