I agree that a lot could be done with those sorts of data.
One company that already is making some use of a similar dataset is Kinsa, who sells smart thermometers. They started a few years ago, tracking trends in the flu in the US based on the temperature readings of the people using their thermometers (along with location, age, and gender). Now they have a coronavirus tracking website up. It looks like the biggest useful thing that they’ve been able to do so far with their data is to quickly identify hotspots—parts of the country where there has been a spike in the number of people with a fever. That used to be a sign of a local flu outbreak, now it’s a sign of a local coronavirus outbreak. From the NYTimes:
Just last Saturday, Kinsa’s data indicated an unusual rise in fevers in South Florida, even though it was not known to be a Covid-19 epicenter. Within days, testing showed that South Florida had indeed become an epicenter.
Companies like Fitbit could make a similar pivot, looking to see if they can find atypical trends in their data in the Seattle area Feb 28 - Mar 9, the Miami area Mar 2-19, etc. And they might be able to take the extra step of identifying new indicators that help identify individuals who may have coronavirus (unlike Kinsa, as high body temperature was already a known indicator).
There are potentially a bunch more useful things that could be done with all of these datasets, if more researchers had access to them. For example, it might be possible to get much more accurate estimates of the number of people who have been infected with coronavirus. I may make another post about this soon.
I agree that a lot could be done with those sorts of data.
One company that already is making some use of a similar dataset is Kinsa, who sells smart thermometers. They started a few years ago, tracking trends in the flu in the US based on the temperature readings of the people using their thermometers (along with location, age, and gender). Now they have a coronavirus tracking website up. It looks like the biggest useful thing that they’ve been able to do so far with their data is to quickly identify hotspots—parts of the country where there has been a spike in the number of people with a fever. That used to be a sign of a local flu outbreak, now it’s a sign of a local coronavirus outbreak. From the NYTimes:
Companies like Fitbit could make a similar pivot, looking to see if they can find atypical trends in their data in the Seattle area Feb 28 - Mar 9, the Miami area Mar 2-19, etc. And they might be able to take the extra step of identifying new indicators that help identify individuals who may have coronavirus (unlike Kinsa, as high body temperature was already a known indicator).
There are potentially a bunch more useful things that could be done with all of these datasets, if more researchers had access to them. For example, it might be possible to get much more accurate estimates of the number of people who have been infected with coronavirus. I may make another post about this soon.