On Monday, April 6, 2020 at 6:45:59 PM UTC-7, Andy Blackburn wrote:
Nice site.

I've been looking at a lot of data. The problem with the confirmed case counts is that they seem to be substantially gated by availability of tests. The rates of confirmed cases by age bracket vary by 40x (older people get a lot more tests, because they get sicker - but I doubt millennia's are 1/40th as likely to get infected - they just don't get symptomatic - or sick enough to justify a test).

So, rates of infection based on under-testing alone are possibly 5x what's reported overall. Then there is the time lag from infection to test result which has averaged around 11 days (7 days to become symptomatic enough to go to the doctor and 4 days to get a test result and biome a confirmed case) , so the reported rates of infection are whatever the daily growth rate is to the 11th power. That can be up to 25x in the rapid growth phase, but probably more like 2-3x now. Once everything peaks the time lag effects are more manageable, but still the mortality rate is a highly confounded metric because the denominator is so uncertain.

Once we get broad, randomly distributed antibody tests we will know a lot better what's going on. In the mean time take a grain of salt on the reliability of the data - depending on which data you are looking at.

Andy Blackburn
9B


On Monday, April 6, 2020 at 11:07:16 AM UTC-7, 2G wrote:
The U. of Chicago has taken my infection rate metric (confirmed cases per million population) to the next level: interactive county-by-county visualization. This shows hot spots that state level data miss. Hot spots are counties with high infection rate that are surrounded by counties with elevated infection rates (this filters outliers, isolated counties with a high infection rate). The U. of Chicago is using the same data source that I have been using in my personal data analysis (1point3acres.com).

https://news.uchicago.edu/story/stat...ncluding-south

The tool allows you to drill down to county level data that includes:
1. Confirmed case count.
2. COVID-19 deaths.
3. Licensed hospital beds
4. Daily new data (cases, deaths, infection rate, death rate)

https://geodacenter.github.io/covid/map.html

The country-wide view can select from 10 different metrics:
1. Confirmed count
2. Confirmed count per 10k population
3. Confirmed count per licensed bed (this is well above 1 for the NYC area)
4. Death count
5. Death count per 10k population
6. Death count per Confirmed count
7-10. Daily metrics

All of this data is available by date since the start of the crisis. You can also compare state-only data to country data to see the dramatic difference between the two.

Agreed that there is a major limitation on the confirmed cases data, but it is all we have to work with. I expected a quantum jump in this as testing became more available, but that didn't happen, just a very smooth exponential increase. This must be because "confirmed" must include doctor's diagnosis as well as positive test results. On the other hand, deaths are deaths, so you can rely on that data.

Tom