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The coronavirus has now killed more than 82,000 people in the United States. How many more will die? Scientists have built different models that answer that vital question differently. NPR's Nurith Aizenman reports on one team that has tried to make sense of competing projections.
NURITH AIZENMAN, BYLINE: Americans got a glimpse of just how many different forecasts there are for this pandemic at a White House press conference last March. Dr. Deborah Birx of the Coronavirus Task Force started thanking all of the modelers she'd been consulting.
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DEBORAH BIRX: There was a modeler out of the University of Washington, from Harvard, from Columbia, from Northeastern, from Imperial.
AIZENMAN: Since then, the number of epidemiologists and statisticians putting together COVID-19 projections has only multiplied. We're talking dozens. And that makes it challenging to get even a ballpark idea of where the pandemic is headed.
NICHOLAS REICH: Each of these models has their own perspective.
AIZENMAN: Nicholas Reich is a biostatistician at University of Massachusetts Amherst.
REICH: They're using different data sources, using different methodologies.
AIZENMAN: It's not even possible to make side-by-side comparisons. Each model uses slightly different formats, time frames. So Reich and his colleagues at Amherst have come up with a kind of portal through which each modeler can communicate their findings. Now...
REICH: All of these forecasts can be represented in a single, standardized way.
AIZENMAN: The most pessimistic forecast - by June 6, 120,000 people will have died. The most optimistic - 103,000 dead by that date, which is as far out as Reich's roundup goes. He's also produced what's called an ensemble model, a merging of all the forecasts into one single projection. In this case, by June 6, the death toll will reach 110,000. Caitlin Rivers is an epidemiologist at Johns Hopkins University.
CAITLIN RIVERS: Having this ensemble approach really pulls together those different results and makes them, in some ways, greater than the sum of their parts.
AIZENMAN: She notes that when it comes to forecasting yearly outbreaks of the flu, ensemble models tend to outperform any single model. In fact, Reich's expertise comes from years of working with the U.S. Centers for Disease Control and Prevention to create ensemble models of seasonal flu. The ensemble approach also helps smooth out the weekly changes among many models as their creators have tweaked and updated them. James Scott leads a team that created a forecast by the University of Texas at Austin.
JAMES SCOTT: If you've seen our model getting more pessimistic over the last, say, seven to 10 days, it's because there's been a notable uptick in mobility patterns around the United States.
AIZENMAN: More people interacting face-to-face means more infections and more death. But other models have become more optimistic. Meanwhile, Reich thinks he can still improve on his ensemble model. Right now, it's effectively an average of all the projections that go into it. Eventually, he hopes to give more weight to the projections that have proven more accurate.
REICH: We've been sort of building the car as we're driving it at 90 miles an hour down the highway and we're learning as we go.
AIZENMAN: To see how the models line up and how they've changed over time, you can go to npr.org.
Nurith Aizenman, NPR News.
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