The main snag with this model is hospitalizations. Even if we grant that there was no testing available, and that early deaths of covid19 would have been attributed to cardiac disease or pneumonia, and that there may have been some kind of less lethal early strain or some other voodoo, the hospitalization rate would still be expected to be constant, and it hasn't been. Health care workers have broadly been reporting pretty typical case loads up until early to mid March.
For some corroborating data, there's a "smart thermometer" company [1] that uses the aggregated data from their thermometers to maintain health "weather" metrics for the US [2]. Right on their health weather page, you can see a chart showing typical rates for seasonal infections across the US, up until March 1st. And if you're concerned that New York is tilting the results, then you can even zoom in to the San Francisco area [3] and see the same behavior.
Kinsa's CEO has published a writeup on medium [4] that compares a couple of different areas with different responses and timelines, and he says that the data he's seeing suggests that stay-at-home orders are making a big difference in infection rates. They have more stuff like this on their Twitter account [5].
I would think that if this were the same disease all the way back in December, the data would look very different. There'd be no explanation for the fall-off of fever rates all the way up to March 1, when it suddenly started climbing.
For some corroborating data, there's a "smart thermometer" company [1] that uses the aggregated data from their thermometers to maintain health "weather" metrics for the US [2]. Right on their health weather page, you can see a chart showing typical rates for seasonal infections across the US, up until March 1st. And if you're concerned that New York is tilting the results, then you can even zoom in to the San Francisco area [3] and see the same behavior.
Kinsa's CEO has published a writeup on medium [4] that compares a couple of different areas with different responses and timelines, and he says that the data he's seeing suggests that stay-at-home orders are making a big difference in infection rates. They have more stuff like this on their Twitter account [5].
I would think that if this were the same disease all the way back in December, the data would look very different. There'd be no explanation for the fall-off of fever rates all the way up to March 1, when it suddenly started climbing.
[1]: https://www.kinsahealth.co/
[2]: https://healthweather.us/?mode=Atypical
[3]: https://healthweather.us/?regionId=06075&mode=Atypical
[4]: https://medium.com/@inders/your-sacrifices-are-saving-lives-...
[5]: https://twitter.com/kinsa