What went wrong with data journalism during the Covid-19 pandemic

And what we should learn from this, plus some examples of how high-quality data journalism can make a difference

Numbers, indices, statistics, transmission curves, vaccination rates. The Covid-19 pandemic was mainly described using the same language of scientists and healthcare professionals. But too often information was inaccurately reported, and results misinterpreted. It has become more and more evident that journalists, and not only science journalists, should learn how to deal with data and scientific information to improve the quality and reliability of their work. Reporting data requires the capability of using data, but also critically reporting on numbers and data, making comparisons, and drawing conclusions.

For more than two years, numbers have become the protagonists of our life. During the pandemic, the data were first and foremost used to track the spread of the virus, the rollout of Covid-19 vaccines, and the areas where the distribution was unequal. Our actions, our perception of risk, and the decisions of governments have been based on numbers and percentages. And these numbers reached most of us through data journalism: a form of journalism that selects and analyses data to get new information and evidence. And, not least, analyzing and presenting data in clear and accessible ways is also fundamental for debunking misinformation and conspiracy theories, and helping people to make informed decisions about their health and safety.

Public data, the key role of transparency

When it comes to public data (such as the ones broadly spread and used during the pandemic), the reliability of information highly depends on transparency. However, data transparency was often incomplete or missing depending on the specific situations in the different countries. Data are not objective per se. They do not tell a single story. They help contextualize a story and highlight the voids, the gaps, and the need for further analyses and further and better data collection. Data can be of help but to achieve this goal, they need to be understood and become a much more common ingredient of public conversation on any socially and ethically relevant issue.

That’s why, overall, negative examples of data handling during the Covid-19 pandemic highlight the importance of accurate and transparent data collection and reporting. On the other side, journalists had to deal with some limitations not merely related to their capability of properly collecting and handling statistical information. First, the transmission of inaccurate or incomplete data made it difficult for public health officials to make informed decisions about how to respond to the pandemic. Some countries have struggled to collect and report data on Covid-19 cases and deaths due to a lack of testing or inadequate reporting systems. Second, accurate reporting was frequently also translated into the pressing need for data journalists to transcend national borders, which is not yet a practice.

There are, however, prominent examples of data journalism related to the global pandemic. Born as a tentative answer to insecurities, criticism, and doubts that emerged, they show the potential in working with data with different approaches and were able to contribute to the clarity, reliability, and validity of the information on the pandemic. These stories demonstrate the success of using data journalism as a methodology to uncover a story through publicly available data (open-access data and public scientific data) and combining them in a rigorous manner to report on a science-related story. And in some cases, high-quality data journalism could make public information that is scattered across several official documents easily available and accessible to citizens as well as to journalists via a dedicated repository.

Accurate data collection and handling: an iconic example

The Covid tracking project is an iconic example of how accurate data collection and handling can provide a valuable resource for journalists, researchers, and the public, to better understand the impact of the pandemic in their communities and to inform policy decisions. It was launched in March 2020 and coordinated by The Atlantic magazine, but it was possible thanks to a group of volunteers from a variety of backgrounds, including data scientists, journalists, and healthcare professionals. Every day and every week, these people from every corner of the US collected data on Covid-19 testing, cases, hospitalizations, and deaths from all 50 states in the US, as well as from the District of Columbia, Puerto Rico, and other territories. The project aimed to provide accurate and up-to-date information on the pandemic and to fill gaps in the data being reported by the federal government. The data from the Covid Tracking Project has become the basis not only for journalistic investigations but also for more than one thousand scientific papers, including works published by The New England Journal of Medicine, Nature, and JAMA, and 11 letters by federal lawmakers demanding answers on the pandemic response from government leaders and commercial labs.

Pictures by Markus Spiske and Manuel Geissinger, Pexels