That calculation comes from research published today in Science Advances that seeks to understand how many COVID deaths fell through the cracks of official reporting systems. The untallied cases show the burden of the pandemic in the U.S. fell most heavily on marginalized people.
“These vulnerable groups are just taking a higher risk at every step, and the accumulation of all of that is this disparity in COVID mortality at the end,” says Mathew Kiang, an epidemiologist at Stanford University and a co-author of the study.
In the new research, Kiang and his colleagues analyzed official records published by the Centers for Disease Control and Prevention for deaths occurring from March 2020 through December 2021 for adults aged 25 and older—some 5.7 million records in all. First, they fed a machine-learning algorithm the records of deaths in hospitals, which at the time were testing most patients for COVID. They trained the algorithm to recognize hospital deaths in which COVID was formally identified as an underlying cause. Then they used the algorithm to flag potential unrecognized COVID deaths by identifying records that looked like hospitalized COVID deaths but occurred in other settings where testing was less likely.
All told, the algorithm identified between about 150,000 and 160,000 potential unrecognized COVID deaths on top of the 840,251 that were officially reported. Those numbers suggest that for every five recognized COVID deaths, one additional death went unmarked. That ratio is on par with other analyses that have simply compared the total observed number of deaths with the number of total deaths expected based on historical data, says Daniel Weinberger, an epidemiologist at the Yale School of Public Health, but the new method is both more sophisticated and more granular.
Source: www.scientificamerican.com
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