Researchers trying to model how many Americans could be hospitalized or killed by COVID-19 have been criticized from multiple quarters, with accusations that they scared people to death or gave leaders false certainties. It was OK to reopen businesses.
In Colorado, recent projections that the state could run into hospital beds as early as September do not appear to be true, as new coronavirus infections slowed to a rapid increase in mid-July.
Other projections have far underestimated the toll of the outbreak, predicting that about 300 would die at the onset of the virus. As of Friday, 1,736 Coloradans had been killed by the virus, and another 121 people had died with it in their systems.
Experts point to at least three factors to explain why projections have not hit the market: the inherent limitations of models, gaps in our knowledge of the new virus and people changing their behavior faster than expected.
Jimi Adams, an associate professor of health and behavioral sciences at the University of Colorado Denver, said there is often a misunderstanding of what models do. Some, like new two-week forecasts from Google, are trying to predict what will happen. Others are trying to explain what could happen under various possible scenarios, including if no policy changes, which is unlikely during a pandemic, he said.
Think of the difference like Ebenezer Scrooge’s question to the Ghost of Christmas Future: “Are these the shadows of things that will be, or are they shadows of things that can only be?” Basically, Scrooge asks if he has any power to prevent a future where he dies alone and Tiny Tim dies young. While the ghost does not respond, Scrooge changes his behavior to try to avoid the scenario with the least care, and the future to come is less bleak.
We saw something like this happen because states and cities required people to stay at home or wear masks, and because people responded to a resurgence in cases by avoiding high-risk institutions, said Beth Carlton, an associate professor of environment and occupational health at the Colorado School of Public Health.
It is unusual for people to change their behavior as quickly and dramatically as they have in response to COVID-19, she said. That’s good for public health, but makes it harder to project what’s going to happen.
“People have the power to change the direction of these forecasts,” she said. “Some of the power is individual, and some is policy.”
Up-and-down swings
Phone location data used to estimate social distance and responses to masked surveys show that people become strict about distance as cases of media reporting and relax as the image begins to improve, which was not what scientists initially expected, said Ali Mokdad, a professor at the University of Washington’s Institute for Health Metrics and Evaluation. While it is good that people take precautionary measures when they feel at risk, relax when cases fall just set the next spike, he said.
“Unfortunately, we will see these up-and-coming swings unless people adapt to the virus,” he said.
The IHME’s latest model was near deaths in Colorado by early August, projecting 1,869 deaths by Wednesday – 18 more than the total number of people who died as a result of the virus. It is estimated that between 2,149 and 5,006 people could die by 1 December. As almost all Coloradans wear masks in public, and the toll can vary from 2,744 to 18,244 if they do not.
Initially, models had to rely on data from China and Europe, which were not always applicable to the US situation, Mokdad said. The image was also restricted in the early months of the spread of the virus in the US, as a lack of testing meant no one really knew how far the virus had spread, he said.
“Our model has evolved because we have more data,” he said.
Katie Colborn, research director for surgical outcomes and applied research at the Anschutz Medical Campus of CU, had previously worked on predicting malaria outbreaks in countries where the disease is common. With malaria, there is nearly a decade worth of high-quality weather and case data, so it is possible to predict that an unusually rainy season will likely result in more cases, at least in the short term, she said. For COVID-19, the early warning signs are not nearly as clear.
Researchers are still trying to work out how the disease is transmitted, including how long it could stay in the air after an infected person speaks, Colborn said. Other questions, such as why it is widespread in nursing homes but apparently not in childcare centers, also need answers, she said.
Refine approach
The PolicyLab at Children’s Hospital of Philadelphia is also refining its approach as knowledge evolves. In May, they had predicted that there would not be much chance of a renewed outbreak in Colorado Springs this summer, but that Denver could be in danger. Both cities have seen an uptick in coronavirus infections, but growth is steeper in El Paso County, where residents appear to be practicing less social distance.
In more recent projections, they have shifted to focus on the next one to four weeks, said Brian Fisher, an associate professor of pediatrics and epidemiology at the University of Pennsylvania. The further you look, the more likely you are to leave because behaviors as policies may have changed, he said.
They also learned that the effects of temperature and humidity are more complex than originally thought, Fisher said. This spring, they had thought that hot days would work against the virus, but that did not happen, perhaps because people began to congregate in rooms with air conditioning, he said.
The PolicyLab model uses mobile data on visits to non-essential businesses, such as shops and restaurants, to estimate social distance, Fisher said. That has no responsibility for other precautionary measures that people would have taken, such as wearing masks or taking takeout instead of sitting in a restaurant, so it is possible that some counties will not see the expected rebound in cases where people go out more, he said. hy.
“It may be that they have reduced social distance, but they are doing it in an intelligent way,” he said.
Models will differ based on the quality of their data, as well as the mathematical choices and assumptions of their creators about human behavior, said Aditya Khanna, director of network models at the University of Chicago. While specific figures may not reflect what is really happening, most have just been predicting that if people started living the way they did before the pandemic, there would be a spike, he said.
“There are some things that are very clear,” he said. “In the big picture, there’s a lot we’ve already learned.”
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