Nearly 130,000 U.S. Lives Saved by March if Everyone Wore Masks: Study | Health News

By Dennis Thompson
HealthDay Reporter


FRIDAY, Oct. 23, 2020 (HealthDay News) — A resurgence of the new coronavirus is bearing down upon the United States, with hundreds of thousands more deaths likely to occur over the next few months, according to one of the nation’s top epidemic modeling teams.

But there’s one thing everyone can do to forestall the surge and save lives — wear a face mask whenever you’re out in public.

The model suggests that total COVID-19 deaths in the United States could exceed 500,000 by the end of February under the most likely scenario, according to findings published online Oct. 23 in the journal Nature Medicine.

However, as many as 130,000 of those deaths could be avoided if some social distancing measures were reinstated and 95% of Americans always don a mask when they’re out and about, the researchers found.

“Expanding mask use can be one of the easy wins for the United States,” said senior researcher Dr. Christopher Murray. He’s director of the Institute for Health Metrics and Evaluation at the University of Washington in Seattle. “It can both delay the re-imposition of social distancing mandates and can save many, many lives.”

A recent HealthDay/Harris Poll shows there’s reason for hope in that regard. More than nine in 10 U.S. adults (93%) said they sometimes, often or always wear a mask or face covering when they leave their home and are unable to socially distance, including more than seven in 10 (72%) who said they always do so.

The new COVID-19 forecast predicts that a surge in the pandemic is inevitable. This week’s increase in cases likely was “the turn,” Murray said.

“We are heading into a very substantial fall/winter surge. The idea that the pandemic is going away, we do not believe is true,” Murray said. “The turn this week where deaths and cases are now going up at the national level is very much in line with what the paper is suggesting.”

More than 1 million COVID-19 deaths could be expected to occur by late February if no lockdowns or social distancing mandates are re-imposed as infection rates surge, the researchers forecast.

If governors gradually re-impose social distancing mandates, there likely will be more than 511,000 total COVID-19 deaths by the end of February, the model predicts.

This is a more likely scenario, Murray said.

“Governors are going to re-impose mandates when things get quite bad because they’re going to try to avoid hospital systems being overwhelmed,” Murray said, and those mandates will change the trajectory of the pandemic.

“As the reality of this fall/winter surge finally kicks in in the U.S., I think we will shift the discussion to what are the set of less-stringent mandates that could be used to at least put the brakes on transmission more than just expanding mask use,” Murray said.

Under this scenario, the states hardest-hit by infections would be Arizona, New Jersey and Louisiana, the researchers predict.

A scenario in which nearly everyone wears

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How Covid-19 Death-Rate Predictions Have Changed Since March

In March, estimates of how many Americans would die from Covid-19 in the coming months ranged from 81,000 to 2.2 million.

That disparity—which arguably produced as much confusion as insight—prompted one independent data scientist to build his own model in hopes of arriving at a better forecast. (He did.)

Now, as many as 50 different research groups make predictions, but one of the most accurate assembles all of the individual models, calculates the median value and looks no more than four weeks into the future.

The ensemble forecast was founded by the Reich Lab at the University of Massachusetts, Amherst, in collaboration with the Centers for Disease Control and Prevention and is based in part on models previously developed to forecast influenza and other infectious diseases.

In the next four weeks, it predicts the total number of deaths attributed to the new coronavirus will surpass 240,000—adding roughly 17,000 deaths to the current tally.

Such projections help policy makers and health-care officials decide how to manage resources and implement or relax interventions intended to curb the spread of the disease.

“It gives you guideposts,” said Jeffrey Shaman, an infectious-disease modeler at the Mailman School of Public Health at Columbia University. “Are you going in a bad or good direction? Is it under control?”

But even now, the projections of individual models sometimes differ substantially, according to Michael Johansson, co-leader of the CDC’s Covid-19 modeling team. In June, one model predicted that by July, the death toll would top 263,000. Another anticipated that it would be less than 120,000.

By focusing on the median, the ensemble forecast has consistently provided reliable four-week projections. In this case, its projection was 130,558, and the actual figure was 130,089.

“That’s been one of the big advantages,” Dr. Johansson said. “By leveraging all the information from all the model approaches, we get forecasts that are demonstrably robust.”

The Covid-19 Forecast Hub is the central repository for individual forecasts. Those included in the ensemble—currently more than 40—are probabilistic forecasts that look four weeks into the future; provide a point estimate of the expected number of deaths in the period; and include the range within which the actual number will likely fall with prediction intervals of 95% and 50%.

The ranges for each forecast are divided into 23 quantiles. The Hub calculates the median for each quantile, and the ensemble forecast is the median of those values.

“Because of previous work, we know you don’t want to exclude models unless there is a clear reason to do so,” Dr. Johansson said. “They capture different things.”

By confining the forecasts to the short term, changes in policy or public behavior are also less likely to upset the projections.

In contrast, the earlier models tried to predict the number of deaths that would occur months later.


How has your understanding of Covid-19 evolved since March? Join the conversation below.

“Forecasts beyond a relatively short prediction window are not going to be very robust,” Dr. Johansson said. “You

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