NEW YORK — A recent study has unveiled that the early death toll from the COVID-19 pandemic in the United States was considerably higher than the official numbers initially suggested. This research sheds light on significant disparities in deaths that went unrecorded.
Official records indicate approximately 840,000 COVID-19-related deaths documented on death certificates in 2020 and 2021. However, researchers employing advanced artificial intelligence techniques estimate that up to 155,000 additional deaths likely occurred outside hospital settings and went unrecognized during that period. This suggests that nearly 16% of COVID-19 fatalities may not have been accounted for in the official statistics.
Published on Wednesday in the journal Science Advances, the study’s findings align closely with estimates from other research conducted on pandemic-related fatalities during those years. What sets this study apart is its focus on identifying which specific deaths might have been omitted from official counts.
The researchers concluded that those most likely to be missing from the official death toll were undiagnosed individuals, predominantly from Hispanic and other communities of color. These deaths occurred primarily in the initial months of the pandemic and were concentrated in certain Southern and Southwestern states, including Alabama, Oklahoma, and South Carolina.
Even six years after the coronavirus initially struck the U.S., significant barriers persist for many within these communities, notes Steven Woolf, a Virginia Commonwealth University researcher who was not part of the study.
“People on the margins continue to die at disproportionate rates because they can’t access care,” Woolf shared in an email, underscoring ongoing disparities in healthcare access and outcomes.
Access to care wasn’t the only challenge
While hospital patients were routinely tested for COVID-19, many who grew sick and died outside of hospitals were not tested — often because at-home testing was not readily available early in the pandemic, said one of the study’s authors, the University of Minnesota’s Elizabeth Wrigley-Field.
In some parts of the country, death investigations are handled by elected coroners who don’t necessarily have the specialized training that medical examiners do. Some research has suggested partisan opinions could affect whether a sick person or their family members sought COVID-19 testing, and whether coroners pursued postmortem coronavirus testing. Indeed, some coroners said families had pressed them not to list COVID-19 as a cause of death.
“Our antiquated death investigation system is one key reason why we fell short of accurate counts, particularly outside of big metropolitan areas,” said Andrew Stokes of Boston University, the senior author on the paper.
Death counts were swept up in COVID politics
The Centers for Disease Control and Prevention data count more than 1.2 million COVID-19 deaths since the pandemic erupted in early 2020. More than two-thirds of those reported deaths occurred in 2020 and 2021.
The count has long been debated, as false claims on social media said the number of COVID-19 deaths was inflated. Adding to the rancor was President Donald Trump, who in August 2020 retweeted a post claiming only 6% of reported deaths were actually from COVID-19 — a post Twitter later removed.
To be sure, there were other kinds of pandemic deaths. For example, uninfected people died from other medical conditions because they could not get care at hospitals overloaded with COVID-19 patients. People with drug addictions died of overdoses as a result of social isolation and losing access to treatment. Other studies that have estimated the actual number of pandemic deaths have taken those deaths into account.
But Stokes and his collaborators wanted to focus on the deaths of people infected by the coronavirus. They used machine learning to sift through the death certificates of infected patients who died in hospitals and then used patterns observed in those records to evaluate death certificates of people who died outside hospitals and whose deaths were attributed to things like pneumonia or diabetes.
Scientists’ understanding of the strengths and weaknesses of machine learning-reliant research is still evolving, but Woolf called this team’s use of it “intriguing.”
