AI-Assisted Cough Tracking Could Help Detect the Next Pandemic

Some researchers have turned their focus to artificial intelligence to study an underused symptom common to most respiratory pathogens—cough.

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When Joe Brew worked for the Florida Department of Health as an epidemiologist for two years starting in 2013, he helped with syndromic surveillance, meaning he had the arduous job of reviewing the symptoms of patients coming into the emergency departments from all across the state. The goal of such work: to detect an abnormal spike of symptoms in an area that may indicate there’s a public health concern.

Public health authorities worldwide continue to use this type of surveillance. The outbreak of a novel pathogen in Wuhan, China in late 2019, for instance, was in part detected by a large uptick of patients coming to the hospital with symptoms of a respiratory infection, with unknown etiology. But Brew says this system fails to prevent the transmission of a virus like SARS-CoV-2 because by the time patients arrive at the hospital, they have likely already been ...

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Meet the Author

  • Max Kozlov

    Max is a science journalist from Boston. Though he studied cognitive neuroscience, he now prefers to write about brains rather than research them. Prior to writing for The Scientist as an editorial intern in late 2020 and early 2021, Max worked at the Museum of Science in Boston, where his favorite part of the job was dressing in a giant bee costume and teaching children about honeybees. He was also a AAAS Mass Media Fellow, where he worked as a science reporter for the St. Louis Post-Dispatch. Read more of his work at www.maxkozlov.com.

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