What about those asymptomatic Corona carriers?

Should we not be sampling the entire population for the Corona virus?

There seem to be more and more voices wondering why authorities are not testing to sample the general population for the Corona virus. In an article published in STAT, Prof. John Ioannidis - a Stanford professor of medicine, epidemiology, population health, biomedical data science and statistics - well-articulated this huge question bugging minds of many of us who are trying to follow the reasoning of decision makers: while assuming up to 80% of virus carriers to be asymptomatic, strict emergency measures are implemented including harsh population lock-downs which would actually include many of these subtle carriers. Yet it seems that a systematic screening effort or at least methodological sampling to find out what indeed is going on, is not happening most anywhere.

A few opportunistic studies of isolated case studies have come up with figures indicating for example that 17.9% or 30.8% of people with COVID-19 had no symptoms. In Iceland, the results of the first batch voluntary of 1,800 tests on people with no symptoms, produced 19 positive cases, or about 1% of the sample. But for effective management of public health, is it not imperative that we find them and understand their attributes, in conjunction with all the statistics that are collected regarding all the proclaimed "sick" people?

How can we only be testing the "sick" people and implementing nation-wide measures based upon mere assumptions regarding the prevalence of infecting agents among the rest of the population?

Would we not want to know, for example:

• Where are clusters of the "invisible carriers" are and focus our efforts on their isolation?
• Validate the notion that two weeks without symptoms are sufficient to determine that an individual has not been infected?
• Define what actually is the minimal set of symptom that are indicative?
• At what pace are more and more people becoming exposed to the virus - with or without getting "sick"? perhaps that would clarify if there is any merit in the notion of "herd immunity" effect?

"The most valuable piece of information ... would be to know the current prevalence of the infection in a random sample of a population and to repeat this exercise at regular time intervals to estimate the incidence of new infections", writes Prof. Ioannidis. "Sadly, that’s information we don’t have. In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lock-downs."

Makes sense to me.