The capability to produce a daily count over a large nation is a proof of the functioning existence of a large, distributed infrastructural system which moves around test samples and reagents, coordinates clinical staff + remote techs, and has unimpeded internal information flow.
When the count goes down, sometimes that means the thing people think it means.
Other times it means that the orderly functioning of the supply chain that produces the count has been impaired.
Other times it means that the orderly functioning of the supply chain that produces the count has been impaired.
It is very important that we not mistake Scenario #2 for Scenario #1.
In Scenario #2, you will see a decrease in the number of tests produced per day, an increase in reported latency between tests being ordered and tests results being ready, and an increase in test positive rate as capacity rationed for patients with known worse clinical outcomes.
All three of those data points are available from official services, but those data points are not as widely understood as the count is by analysts, policy makers, and others.
“Explain that rationing.”
Suppose that getting access to testing takes a clinician 15 minutes one week but 30 the next. Their rational response is to not conduct discretionary bubble tests (“Probably a waste of time anyhow.”) but still conduct tests for severely ill patients.
Suppose that getting access to testing takes a clinician 15 minutes one week but 30 the next. Their rational response is to not conduct discretionary bubble tests (“Probably a waste of time anyhow.”) but still conduct tests for severely ill patients.
From a provision of care perspective, the person with bilateral pneumonia and severe difficulty breathing needs clinical effort more than someone who came in with a high fever.
From an information theory perspective, a test on first patient gives you less new info than second.
From an information theory perspective, a test on first patient gives you less new info than second.
“It seems unlikely the doctor will make that decision. Don’t they cover this in...”
One of Japan’s foremost epidemiologists was complaining earlier today about how few doctors understand Bayes’ Rule.
How often has this been critical during their career, etc etc.
One of Japan’s foremost epidemiologists was complaining earlier today about how few doctors understand Bayes’ Rule.
How often has this been critical during their career, etc etc.
