On March 11, 2020, the World Health Organization announced that COVID-19 had reached pandemic status, and people around the globe struggled to understand the current and future scope of a rapidly spreading, deadly virus. As countries entered lockdown one by one, the people sequestered within their homes turned to news outlets for answers. That’s when people around the world, looking for answers on television news, government websites or social media, had their first encounters with data dashboards.
Throughout the course of the pandemic, millions of users – from journalists to researchers to policymakers – called upon data analytics daily. Data dashboards take highly complex statistical data and make it easy to read and process. Data designer Lisa Charlotte Muth of Datawrapper, a German startup offering an open-source web tool to create easy-to-read, interactive charts for websites, remarked on the increased reliance on COVID-19 dashboards. “You didn’t have any data set before that was so essential to how you plan your life,” says Muth. “The weather, maybe, was the closest thing you could compare it to.”
Data supported our understanding of the virus, and the public’s reliance on the information revealed the impact easy-to-understand data can have on our society. From policymaking to dispelling misinformation, data changed the course of the COVID-19 pandemic and may influence where we go from here. Top data scientists are now reflecting upon the lessons they learned from this phenomenon, ones they hope won’t be lost over time.
If We Post It, More Data Will Come
Beth Blauer, a data and public-policy specialist at Johns Hopkins University in Baltimore, Maryland, noticed the possible influence data had on the general public’s understanding early in the pandemic. Blauer was trying to understand racial disparity in susceptibility to the virus, something mentioned only anecdotally. Blauer and her team added a new graphic depicting which of the U.S. states published infection and death data broken down by race and ethnicity to the John Hopkins’ COVID-19 data dashboard, the Coronavirus Resource Center, and the response was almost immediate. “We started to see the map rapidly filling in. And it confirmed that we have the ability to influence what’s happening here,” she says. When Blauer first posted the graphic in mid-April of 2020, only 26 of the 50 U.S. states shared racial and ethnic data. In just a month, 14 more states started sharing that perspective, and suddenly reporters and policymakers were paying attention to the racial disparity. Thus, an early lesson learned was how creating awareness and visibility through clearly communicated data can influence change.
Hard Data is Hard to Maintain
Data dashboards require a great deal of work to ensure data is up-to-date and accurate. The Johns Hopkins dashboard started with a Google sheet populated by Lauren Gardner, associate professor and co-director of the Center for Systems Science and Engineering at Johns Hopkins University, and her PhD student, Ensheng Dong. “We literally decided this one afternoon, and built the initial version of the dashboard that night,” says Gardner. “It seemed like a manageable, simple task, given the scale of the problem at the time. Of course, we didn’t know the scale that this would grow to.” Within weeks the website had upwards of four billion inquiries a day.
One of the greatest challenges Gardner’s team faced was compiling complete and consistent COVID-19 data. It was “very manual and very messy,” says Gardner. “We were scrambling, collecting and validating reported data as fast as we could.” Even as public agencies started sharing data, the timing of the data capture and reporting in methods, many of which weren’t machine readable, continued to cause problems. Given the need for evidence-based decision during a pandemic, a clear lesson learned was that data important for public health should be freely available, machine-readable, and standardized.
Easy-to-Read vs. Easy-to-Understand
While those who have studied math and statistics have a high rate of “graphicacy,” or the ability to understand data presented in graphs and figures, the COVID-19 data dashboard’s readership quickly became an information source for people of all backgrounds. “I think the pandemic helped to bring the graphicacy of the general public to a higher level,” says Maarten Lambrechts, a data-visualization consultant based in Diest, Belgium.
Even so, the lesson learned is the significant need for simplicity and clarity to ensure users walk away understanding the message. Language used in titles and subtitles of charts became of the utmost importance, such as being certain to specify “confirmed” deaths or “confirmed” cases. “An emphasis on ‘confirmed’ is really important because we know that it’s an underestimate of the total,” says Hannah Ritchie, head of research at the non-profit organization Our World in Data in Oxford, UK. “It might seem very basic, but it’s really crucial to how you understand the data and the scale of the pandemic.”
The Dangers of Incomplete Data
In the initial stages of the pandemic, incomplete data posed an issue with reflecting the reach and severity of the virus and risked fueling misinformation. Ritchie has been observing the direct consequences of incomplete and inconsistent data, specifically those resulting from availability of COVID-19 testing. During the pandemic, a lack of test data gave the impression that some countries weren’t as affected by the pandemic, which simply wasn’t true.
Now, more than two years later, incomplete data may stem from a waning diligence in data gathering. Ritchie and others fear that a perceived “end” to the pandemic is to blame. “As rich countries start to get more back to normal because of high vaccination rates, for example, will they turn around and just let these projects die?” Ritchie wonders. While we all look forward to the day when coronavirus can be just another data point in a bigger picture, faltering in our efforts to collect data now may come at a great cost in the future – a lesson we may need to learn before our attitudes toward ongoing data monitoring change.
Creating a Better-Informed World
Blauer and other data scientists hope that the lessons learned during the COVID-19 pandemic won’t be lost, and that the organized data response to COVID-19 will be applied to other global issues. “Creating standards that are easily adoptable, like measuring cases and deaths for COVID, will be really important when we’re trying to do the hard work of eradicating poverty and improving climate conditions,” says Blauer. “The big question is, are policymakers willing to do it?”
The level of coordination involved would be unprecedented, but the pandemic may have convinced people that the effort and cost would be worthwhile. As we move back to our schools, offices, labs, and cultural venues, perhaps policy leaders will recognize how much proactive and reactive measures rely on data when facing some of our planet’s biggest issues … and make decisions accordingly.
Did you enjoy this blog post? Check out our other blog posts as well as related topics on our Webinar page.
QPS is a GLP- and GCP-compliant contract research organization (CRO) delivering the highest grade of discovery, preclinical and clinical drug research development services. Since 1995, it has grown from a tiny bioanalysis shop to a full-service CRO with 1,100+ employees in the U.S., Europe and Asia. Today, QPS offers expanded pharmaceutical contract R&D services with special expertise in neuropharmacology, DMPK, toxicology, bioanalysis, translational medicine and clinical development. An award-winning leader focused on bioanalytics and clinical trials, QPS is known for proven quality standards, technical expertise, a flexible approach to research, client satisfaction and turnkey laboratories and facilities. Through continual enhancements in capacities and resources, QPS stands tall in its commitment to delivering superior quality, skilled performance and trusted service to its valued customers. For more information, visit www.qps.com or email info@qps.com.
