The testing illusion
The testing illusion
As an outbreak progresses, testing numbers diverge from reality
If yesterday a country made 10k tests and declared 2k new cases, and today makes 12k tests and declares 1.8k new cases, the outbreak is receding, right?
Not necessarily.
A few reasons why:
Hospitalized people need to be tested to validate recovery, often more than once. This means that as the outbreak progresses, and as the number of hospitalized people increases, “number of tests” diverges from “number of people tested”.
Doctors need to be tested regularly to prevent in-hospital contagion, in the hospitals that adopt such procedures. This means that a significant percentage of tests are for “safety protocols” rather than to “test suspected cases in the general population”.
Delays. As an outbreak progresses, it is possible that labs in the country are saturated and cannot process all the tests they made. As the outbreak progresses, countries might face a scarcity in the reagents used to analyze the swabs (as it’s happening in Italy). “Tests made” usually refers to “swabs taken”, not to “swabs analyzed”. This results in delays that might make the curve look flatter than it is.
“Almost certain cases” are not tested anymore. As an outbreak progresses and countries have limited testing capacity, they tend to enact policies that aim to save test kits on “almost certain cases based on symptomatic evaluations” and to reserve them for testing, say, contacts of infected cases. France and Spain already officially enacted such policies.
While this makes sense, the problem is that those “almost certain cases” are diagnosed and treated as if they had contracted the COVID-19 virus, but they are not included in the count of confirmed cases. The result is that a test which would have had very high chance of returning positive is exchanged with a test with a lower chance, and stats as “number of cases” or “percentage of tests turned positive” appear lower than they really are.
Applying Wittgenstein’s ruler, if we do not know who gets tested and how data is reported, we cannot know whether curves about new daily cases represent:
New daily cases, or
Testing policies, or
Government reliability, or
Something else.
Ask your government who is getting tested. Only then you’ll know how to interpret its numbers.
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