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F1000Research, Wellcome Open Research, (5), p. 208, 2020

DOI: 10.12688/wellcomeopenres.16227.1

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Framework to aid analysis and interpretation of ongoing COVID-19 research

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

The global coronavirus pandemic has precipitated a rapid unprecedented research response, including investigations into risk factors for COVID-19 infection, severity, or death. However, results from this research have produced heterogeneous findings, including articles published in Wellcome Open Research. Here, we use ethnicity, obesity, and smoking as illustrative examples to demonstrate how a research question can produce very different answers depending on how it is framed. For example, these factors can be both strongly associated or have a null association with death due to COVID-19, even when using the same dataset and statistical modelling. Highlighting the reasons underpinning this apparent paradox provides an important framework for reporting and interpreting ongoing COVID-19 research.