The Kinsa data is barely even weak evidence in favor of R0 < 1. The downward trend in fever readings are confounded, likely severely, by their thermometers having to be actively used vs. being a passive wearable. It seems plausible that more people will check their temperature when they are concerned about COVID-19, and since most people are healthy this will spuriously drive average fever readings down. Plausibly the timing of increased thermometer use will coincide somewhat with shelter-in-place orders since they correlate with severity & awareness of the local outbreak.
Their FAQ notes that they have seen 2-3x normal usage of their thermometers (this was as of March 29, they haven’t updated this part of their FAQ since) and consider this “healthcare seeking behavior” a potential driver of their trends. This has not stopped them from promoting their data to government agencies and NYT, without mentioning this or any other limitations whatsoever (at least to the NYT).
I was completely wrong, I don’t think their data is subject to this worry. They now have a preprint up. From supplementary methods:
We define daily fever counts as the number of unique users per region that take multiple elevated temperature (37.7 C) readings over the past week, and then normalize these counts by the estimated number of unique users who have used the thermometer over the past year.
So lots of repeat readings shouldn’t affect the gauge, and neither should more of their user base taking readings. Unless they are seeing a lot of new users, or lots of returning users that haven’t used the thermometer in over a year, both of which seem somewhat unlikely, their metric should be fine.
Thanks for pointing this out. Having recently looked at Ohio County KY, I think this is correct. %ill there max’d out at above 1% the typical range but has since dropped below 0.4% of the typical range and started rising again (which is notable in contrast with seasonal trends) [Edit to point out that this is true for many counties in the Kentucky/Tennessee area]. This basically demonstrates that having a reported %ill now that is lower than previous in the Kinsa database is insufficient to show r0<1. Probably best to stick with the prior of containment failure.
The Kinsa data is barely even weak evidence in favor of R0 < 1. The downward trend in fever readings are confounded, likely severely, by their thermometers having to be actively used vs. being a passive wearable. It seems plausible that more people will check their temperature when they are concerned about COVID-19, and since most people are healthy this will spuriously drive average fever readings down. Plausibly the timing of increased thermometer use will coincide somewhat with shelter-in-place orders since they correlate with severity & awareness of the local outbreak.
Their FAQ notes that they have seen 2-3x normal usage of their thermometers (this was as of March 29, they haven’t updated this part of their FAQ since) and consider this “healthcare seeking behavior” a potential driver of their trends. This has not stopped them from promoting their data to government agencies and NYT, without mentioning this or any other limitations whatsoever (at least to the NYT).
I was completely wrong, I don’t think their data is subject to this worry. They now have a preprint up. From supplementary methods:
So lots of repeat readings shouldn’t affect the gauge, and neither should more of their user base taking readings. Unless they are seeing a lot of new users, or lots of returning users that haven’t used the thermometer in over a year, both of which seem somewhat unlikely, their metric should be fine.
Thanks for pointing this out. Having recently looked at Ohio County KY, I think this is correct. %ill there max’d out at above 1% the typical range but has since dropped below 0.4% of the typical range and started rising again (which is notable in contrast with seasonal trends) [Edit to point out that this is true for many counties in the Kentucky/Tennessee area]. This basically demonstrates that having a reported %ill now that is lower than previous in the Kinsa database is insufficient to show r0<1. Probably best to stick with the prior of containment failure.