USF Data Scientist Launches #Masks4All
Data scientist Jeremy Howard was teaching a USF class several weeks ago on deep learning, discussing how to use evidence to make decisions. He wanted to explore whether wearing masks could help slow the spread of coronavirus infection.
“I was shocked that the evidence was incredibly strong” in favor of masks, he said. “I recorded the lesson for the students, and they said it’s too important not to share. That was just three weeks ago.”
Today, Howard’s research is being cited worldwide as support for mandatory mask rules.
“The scientific evidence and global consensus is clear: homemade masks can stop the spread of COVID-19,” he said.
If you have COVID-19 and cough next to someone from 8 inches away, wearing a cotton mask will reduce the amount of virus you transmit to that person by 36 times, Howard found.
Since researching masks with his USF class, Howard has written a commentary for the Washington Post, appeared on CNN, and built a social and policy movement — #Masks4All — to share the findings.
Cities like San Francisco and New York, as well as many towns and states across the country, have adopted mandatory mask rules. Worldwide, in nations like Taiwan and the Czech Republic, where social distancing and masks were part of the early fight against coronavirus, the disease spread has been limited.
As for the students he teaches at USF? “They’re super excited,” Howard said. “This is a great example of what we talk about in class. When the data tells you something, get behind it.”
And while the Bay Area has been able to flatten the curve through its early response to the coronavirus, Howard said the next step — getting back to work and school — should include universal mask wearing.
“Masks should be part of our future forever,” he said. “They are astonishingly effective at blocking the droplets. And, any mask is effective.”