Visualization map of seasonal illness/fever from smart thermometers
healthweather.us
healthweather.us
Kinsa has been selling a digital thermometer for a while. As part of the device, it uploads readings to both your phone and then sends the data back to Kinsa.
Based on their reporting (part of what you're seeing visualized on this map), they have been able to see trending signs of flu outbreaks for a while up to 2 weeks before the CDC issues its reports.
The key difference is that the CDC relies on hospitals compiling reports and sending them in, where Kinsa gets the data directly. This causes a delay of up to 2 weeks in the CDC reports.
Where this ties in with covid-19 is that in the last few months, when they layer recent data over historical data from the last few years, they see an atypical increase in fevers being reported. This can be seen in the graph where the expected trend is going down, but they're now seeing abnormal increases since February.
From the news report, Kinsa is selling thousands of thermometers per day right now and is running into manufacturing issues.
Another point that gets mentioned in the report is that Kinsa has tried offering their data to the CDC before but due to CDC policy, they (CDC) require taking ownership of the data in order to accept it. I'm honestly very uninformed about this part so expect some inaccuracy in what I'm saying. If someone who has more details could reply to this comment, I think that would be very helpful to know.
On the positive side, the Bay Area isn't looking bad at the moment. On the negative side, all of my family is in Florida and I wasn't aware until just now that it was getting that bad state wide.
Florida's governor is still refusing to close beaches, which are packed with people, many of them traveling long distances to get there (spring break), with countless people being interviewed on camera saying they don't care..
Some cities are finally taking measures into their own hand and closing beaches, but at the moment it's only a few.
Given the fact that Florida's population tends to skew older, the data mixed with the public response is concerning.
Our governors incompetence is alarming in any case, though not unexpected.
This info, paired with the recent infection of a US congressman from Florida, makes me suspect they may have a lot of unrealized cases.
2. It would skew the numbers (by conjecture) if a higher proportion of people were old because then a higher proportion of people acquiring the disease would have high fever.
List of counties with confirmed infections - https://coronavirus.ohio.gov/wps/portal/gov/covid-19/ (right under the number of cases)
Map of infections in Ohio - https://www.datawrapper.de/_/etm2H/
Map of Ohio counties by population - https://www.maps4office.com/us-ohio-map-county-population-de...
Map of Ohio child poverty (red is more) - https://www.cleveland.com/datacentral/2020/01/every-ohio-cit...
The child poverty map correlates a bit better with the data from healthweather.us (esp if you factor in the population (density) of each county). The south and east counties in Ohio are pretty sparsely populated.
1) y is CDC ILI activity, % outpatient visits for flu-like symptom, not actual % population that are ill,
https://academic.oup.com/ofid/article/6/11/ofz455/5610164
2) how can you tell credibly from this data it’s just more healthy ppl taking temperature now vs a true decline in fever rate? Feel this is a marketing stunt or a poorly done study.
The technical issues are solved, and there are only 4 main hurdles IMO: 1. privacy, 2. data is privately owned (it costs to have it released), 3. professional gate keeping and 4. that governments are not yet tasked with addressing the problem. Surely all of these can be overcome, with various multi-pronged approaches.
Because having the information out there are too many negative external factors. And health data is pretty hard to anonymize.
> The U.S. Health Weather Map is a visualization of seasonal illness linked to fever
I think the assumption they make is fever == sickness.
I would love to be able to go back in time for a few weeks (animated), and also to be able to see a comparison against last year.
Edit: also this is a fairly leading indicator of problems (and includes many that are sick but get better), compared with confirmed cases which lags and underestimates, or deaths which severely lags (but fairly reliable indicator there is a serious problem)
- There's a lot more testing in Washington state, so there aren't as many undocumented cases as, say, Florida.
- Sparse Kinsa device coverage in Washington, and since the infection rate is still low vs the population at large, the elevated rate of actual disease is within the wide variation in data due to the sparsity.