REPORT: Restrictions Are Slowing Coronavirus Infections, Thermometer Data Suggest

A new report from the NY Times suggests stay at home restrictions throughout the nation are slowing the spread of coronavirus infections.

The data is based on thermometer readings and the rapid drop in the number of fevers.

NY Times reports harsh measures, including stay-at-home orders and restaurant closures, are contributing to rapid drops in the numbers of fevers — a signal symptom of most coronavirus infections — recorded in states across the country, according to intriguing new data produced by a medical technology firm.

At least 248 million Americans in at least 29 states have been told to stay at home. It had seemed nearly impossible for public health officials to know how effective this measure and others have been in slowing the coronavirus.

But the new data offer evidence, in real time, that tight social-distancing restrictions may be working, potentially reducing hospital overcrowding and lowering death rates, experts said.

The company, Kinsa Health, which produces internet-connected thermometers, first created a national map of fever levels on March 22 and was able to spot the trend within a day. Since then, data from the health departments of New York State and Washington State have buttressed the finding, making it clear that social distancing is saving lives.

The trend has become so obvious that on Sunday, President Trump extended until the end of April his recommendation that Americans stay in lockdown. Mr. Trump had hoped to lift restrictions by Easter and send Americans back to work.

“That would have been the worst possible Easter surprise,” said Dr. Peter J. Hotez, dean of the National School of Tropical Medicine at Baylor College of Medicine in Houston, who added that he thought the Kinsa predictions were based on “very robust technology.”

Kinsa’s thermometers upload the user’s temperature readings to a centralized database; the data enable the company to track fevers across the United States.

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