The above is exactly what I have been looking for in my cumulative flow diagrams… the top line curving over and flattening out while the recovery line (green) steadily increases. When the green and orange lines touch, it will mean that there are no active cases remaining. A couple of interesting things about this diagram.
- New cases seem to be shrinking down to zero. This might mean that the infection is close to running its course. There may be new waves, but Iceland is one of the most likely countries in the world to catch it quickly.
- The cycle time for recoveries is now slightly longer than the 14 day quarantine period. Not sure what this might mean, unless maybe Iceland has learned that 14 days is too short to declare a recovery?
- The death line on this chart (red) looks flat but it actually isn’t… the number is 9. This means the infection rate (ratio of deaths to all infected) is around 0.5% The news outlets are very impatient to present the infection rate in each locality and are rushing forward numbers like 4%-10%. Of course most of us know that’s bogus and irresponsible because no one has any idea (except in iceland) how many people were truly infected. We know that the infection rate for influenza during this COVID-19 period has been between 0.06% and .11% based on the CDC’s estimates and models. I suspect the media outlets are scrambling to document infection rates so they can provide this sensational comparison (or perhaps make a political point in the process.
- Case Rates vs. Infection Rates. Above I showed infection rates, which is the total number of deaths divided by the total number of infections. Sometimes the case rate is shown interchangeably with the infection rate, but it is a different thing and is typically defined as the number of deaths divided by the number who report for medical care due to the infection. The case rate, therefore, is very hard to calculate unless hospitals keep good records and release them (something I’m not seeing right now). We know infection rates because the numbers of tests and the numbers who “fail” the test and are infected are both released.
In the diagram above we can see some of the same data from my chart, but what is interesting is the low number of the active cases that are hospitalized. This would translate to something like 6% of all the confirmed cases that are getting hospitalized. Only .8% of the cases go to the ICU.
The above chart is also interesting. Iceland has two different techniques for testing for COVID-19, the NUHI (government) and the deCODE (private). What’s most interesting, however, is that in the last month, the percentage of tested people who show up as infected has dropped to nearly zero. This might show that the outbreak is dying out there.
Finally, Iceland’s infection demographics is very illustrative for the rest of the world. As you can see above, the age groups that have been confirmed as a COVID-19 infection range largely from 18 to 70. I presume that this is because the outlier ages are quarantined more effectively (not going out to buy groceries, etc.). However, we see most of the deaths in the over 60 age group (consistent with other European findings). What this doesn’t show is that contrary to other news reports, Iceland is seeing essentially zero difference in cases between the genders. It’s essentially 50-50.
What does studying Iceland help us understand? Because they are approaching this outbreak scientifically, they are learning more and faster than any other nation. I’d imagine that this is also preventing their media folks from sensationalizing and being creative with numbers. One of the conclusions from the 1918 Spanish Flu outbreak was that the media’s type of reporting could truly influence the direction the outbreak went in their region. In Philadelphia, the city that was hardest-hit during the Spanish Flu, the media was trumpeting “Nothing to worry about here” even after the city had seen 14K deaths in three weeks. In other cities, the media (and government) focused on telling the hard truth and the outbreak was more controlled.