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In an update that illustrates just how challenging it is to track the spread of a fast-moving virus, the U.S. Centers for Disease Control and Prevention on Tuesday lowered its estimate of how prevalent the Omicron variant is in the United States.
The latest agency data pegs Omicron's prevalence at 59%, a sharp drop from its estimate last week of 73% of all COVID cases.
“The 73% got a lot more attention than the confidence intervals [which measure the range of certainty on an estimate], and I think this is one example among many where scientists are trying to project an air of confidence about what's going to happen,” David O'Connor, a virologist at the University of Wisconsin-Madison, told The New York Times.
O'Connor added that he had thought the earlier estimate had “seemed high” and that the agency made the estimate based on a “relatively small number of [gene] sequences.”
Genetic sequencing is the only way to confirm which variant is involved in a particular case and that is not done on every sample, he explained.
“It's like playing Name That Tune, and trying to say, based on just the first note, if the song is Ice Ice Baby by Vanilla Ice, or Under Pressure,” O'Connor said. “Without more data, it can be really hard to know which one it's going to be.”
While predictions are likely to become more accurate as researchers learn more about Omicron, even the new 59% estimate is likely to be revised in future weeks, experts said.
“I just want people to be very aware that that is an estimate, that's not actually from sequence-confirmed cases,” Nathan Grubaugh, an epidemiologist at the Yale School of Public Health, told the Times. “With Omicron in particular, it's been very difficult to have any sort of projections, because things are changing just so so rapidly.”
In Connecticut, where Grubaugh is tracking probable Omicron samples, the variant is responsible for more than 80% of cases, while in Wisconsin, where O'Connor is tracking cases, about half were Omicron in just three days.
“If I was making a betting prediction, it wasn't so much that the number 73% was wrong, but the timing to get there was wrong,” O'Connor said.
Numbers in hand are the most telling, one expert noted.
“I don't know how the CDC built their algorithm, but human beings made these programs, and humans are fallible,” Massimo Caputi, a molecular virologist at the Florida Atlantic University School of Medicine, told the Times. “At the end of the day, you can predict as much as you want but you need to look at the numbers you have in your hand.”
Estimating more precisely will be important to the patients who have COVID-19 because their treatments may vary, depending on whether they are infected with the Delta variant or Omicron. Two of the three monoclonal antibody treatments available in the United States don't work against Omicron.
This has affected hospital decision-making about whether to give these treatments to patients. Administrators from three New York hospitals all said they would stop giving patients the two treatments that are ineffective against Omicron, theTimes reported.
“If you still have those Delta cases, discontinuing monoclonals means all those people who would have benefited from them won't be receiving them at all,” O'Connor explained.
He suggested that scientist and healthcare providers should better communicate their uncertainty about the numbers.
“Having the humility to acknowledge that there's a lot that no one knows and is unknowable right now is going to be really important,” O'Connor said.
SOURCES: U.S. Centers for Disease Control and Prevention; The New York Times
Cara Murez and Robin Foster
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