Modernizing the peer review process and clarifying how to use and understand open data are two essential ways to make sure our science is accurate and accurately presented.

Earlier this year as the COVID-19 virus spread around the world, countries responded by imposing lockdown measures one by one. Scientists, seeing the subsequent satellite observations, rushed to publish papers about improved air quality, many of which appeared in short order on preprint servers. These preprints, which are often published in tandem with their submission to a peer-reviewed journal, spawned a host of press releases and news articles that were spread on social media.

We’re living in a time when calamitous current events are escalating the need for more information.

We’re living in a time when calamitous current events are escalating the need for more information. In response, scientists and media both are making leaps between observation and conclusion. If we want to make sure that assertions are accurate before they are widely disseminated, our rigorous and necessary review systems must be modernized so they aren’t circumvented. We must also make sure that the move toward open data is made with the means for nonexperts to understand the context and limitations of that information.

The Leap to Conclusions

The rush to print by both scientists and the press can raise questions about the validity of the research conclusions. One study published on a preprint server in early April by Harvard University researchers [Wu et al., 2020] was widely circulated on social media. The authors, who simultaneously submitted it to the New England Journal of Medicine, claimed in their paper that an increase in long-term exposure to particle pollution of 1 microgram per cubic meter can lead to a 15% increase in mortality from COVID-19, leading to many news stories on the correlation of air pollution and death rates from the virus.

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