The annals of science brim with researchers who pushed the boundaries of sense and good taste in a laudable quest for knowledge. With the unveiling of the 30th annual Ig Nobel awards, another case shall be added.

To test the validity of a story in a work of ethnographic literature, Metin Eren, an anthropologist at Kent State University in Ohio, made a knife from his frozen faeces. He then set about butchering an animal hide, an endeavour that ended in failure.

âItâs an honour to be recognised,â Eren said, before the ceremony in which he was honoured for his work on Thursday. âIâve followed the Ig Nobels my entire life. Itâs a dream come true. Really.â (...)

The work combines thousands of data points from tree rings, lake and ocean sediments, corals and stalagmites, among other features, and extends the time frame for radiocarbon dating back to 55,000 years ago â 5,000 years further than the last calibration update in 2013.

And that's my problem with the medical profession viewpoint. They, rightly deal with individuals and want to know exactly what is going on with their patients. But statistics are powerful tools for dealing with populations. If we had good data on a sample of people, along with whether they felt they had symptoms and their body temperature, we would have a very good estimate of how many people had been affected.

That thought went through my mind too, surely a few samples of the general population would give us at least some indication within certain confidence intervals. At the moment I haven't heard a thing in any country of how many of the general population have already been infected. The video Miami posted today refers to an extrapolation by the Imperial College that infers (based on hard data) that between 2 and 7 % of the European population has already been exposed. (edit: This is not survey based but a bottom-up calculation from the number of deaths, transmission rates and fatality rates.) That would be fantastic news if true.

I hope they get the new sero-surveys up and running soon. Might make everyone calm down a bit.

A mate of mine (health advisor to the UN in Geneva) basically put everything down in a couple of sentences: "The only reliable way to get true estimates of what percentage of a population has been infected is from a population-based sero prevalence study, which gives you the denominator you need to accurately estimate death rates.

I disagree with this, if I understand correctly. A random (or as close to random as you can practically get) sample of the population, performed through time would give you a good estimate of the infection rate and how it is changing. Since the rate is high, your sample size doesn't need to be huge to find the infected %. It's hard to estimate one in a million, but not so hard to estimate one in a hundred.

I believe the original suggestion is a test for everyone, not a sample. It's impossible to know who's experienced the virus if we didn't allow testing for everyone with symptoms, let alone to the numbers of asymptomatic people that may have antibodies and don't know they have them.

And that's my problem with the medical profession viewpoint. They, rightly deal with individuals and want to know exactly what is going on with their patients. But statistics are powerful tools for dealing with populations. If we had good data on a sample of people, along with whether they felt they had symptoms and their body temperature, we would have a very good estimate of how many people had been affected.

A mate of mine (health advisor to the UN in Geneva) basically put everything down in a couple of sentences: "The only reliable way to get true estimates of what percentage of a population has been infected is from a population-based sero prevalence study, which gives you the denominator you need to accurately estimate death rates.

I disagree with this, if I understand correctly. A random (or as close to random as you can practically get) sample of the population, performed through time would give you a good estimate of the infection rate and how it is changing. Since the rate is high, your sample size doesn't need to be huge to find the infected %. It's hard to estimate one in a million, but not so hard to estimate one in a hundred.

I believe the original suggestion is a test for everyone, not a sample. It's impossible to know who's experienced the virus if we didn't allow testing for everyone with symptoms, let alone to the numbers of asymptomatic people that may have antibodies and don't know they have them.