@BigChocFrenzy it is intuitively obvious that the median infection age should be lower than the median age of the population, since younger people are more sociable, infection rates for flu are far higher among children, etc.
Therefore Germany's median case age is higher than the (true) median infection age, but it gets closer to the true figure than the UK.
In other words the difference between the median case age and the median population age should be inversely proportional to the number of tests - the more testing you do, the more will be not-very-sick young people at minimal risk, and the less you do, the more will be the very ill, who are, quite plainly the very old.
We need to look at several parameters:
- test positive rate (%) - if this is very low, then testing is adequate, if it is high than testing is hopeless. The UK's latest positive % (of daily tests) was 44.2% which is absolutely fucking shit and evidence of the absolute total utter failure of the government to provide adequate testing infrastructure. As a national rate it should be single digits, and perhaps for plague-ridden cities such as London & New York it could plausibly be in the teens. [this parameter should be published]
- median population age [this parameter should be easily googlable for any country]
- median age of those testing positive [most likely published]
- median age of those who are infected [unknown, can be estimated from the above]
In other words if there is a very high % of positive tests, such as in failed countries such as the UK, necessarily the case age must be far older than the infection age. Countries with very low infection rates and minimal testing OR high infection rates & adequate testing for that should give case ages that are fairly accurate.
Of course the obvious thing is simply random sample testing of the population. Suffice to say I see no reason why infections should be older than the population as a whole, but plenty of reasons why most countries completely fail to address the testing challenge resulting in test data that are useless for most purposes (such as the spurious 'survival rate' often quoted).