The problem with simplistic stats is that it often indicates what might be fallacies.

Take the per 100000 figures for example.

There will be a fair few areas in which nowhere near 100000 will have taken the test, so the headline figure will come from a proportion.

But even this leaves questions. A basic GCSE maths question will usually ask "what's wrong with the data collection method", with one of the regular answers having to include the words "bias sample". The point is that we have no idea why so many people feel the need to take the test. Obviously some will be showing symptoms...fair enough, especially if they need this evidence for their employers. But many (the vast majority) will not.

It seems to me that there is a reasonable chance that the sample is inherently bias, and that any fear/panic is overstated. It may well simply be the case that this is an example of Chinese whispers which is making things look far worse than they are.

Am not denying that a fair few have become ill and worse.

But one cannot help think it's not as bad as the media make out.

You've not mentioned the subject of your diatribe but I'm guessing that it's COVID-19 .....

Coronavirus (COVID-19) Infection Survey, UK: 18 December 2020

https://www.ons.gov.uk/peoplepopulat...11december2020

The percentage of people testing positive for the coronavirus (COVID-19) in England has increased; during the most recent week (6 to 12 December 2020), we estimate 567,300 people (95% credible interval: 533,600 to 602,300) within the community population in England had the COVID-19, equating to around 1 in 95 people (95% credible interval: 1 in 100 to 1 in 90).

Over the most recent week, the percentage of people testing positive has increased sharply in London, with other increases in the East of England, the East Midlands, and the South East; the percentage of people testing positive in the North West and Yorkshire and The Humber has continued to decrease in the most recent week.

In the most recent week, the percentage of people testing positive has increased in most age groups, other than those in school Year 12 to 24 years old, and those aged 50 to 69 years; there are now early signs the percentage testing positive is levelling out among older teenagers and young adults.

The percentage of those testing positive has increased over recent weeks in Wales; during the most recent week (6 to 12 December 2020), we estimate that 33,400 people in Wales had COVID-19 (95% credible interval: 23,800 to 44,300), equating to 1 in 90 people (95% credible interval: 1 in 130 to 1 in 70).

The percentage testing positive in Northern Ireland appears to no longer be decreasing; during the most recent week (6 to 12 December 2020), we estimate that 8,500 people in Northern Ireland had COVID-19 (95% credible interval: 5,100 to 13,000), equating to 1 in 215 people (95% credible interval: 1 in 360 to 1 in 140).

The percentage testing positive in Scotland has increased; during the most recent week (6 to 12 December 2020), we estimate that 52,500 people in Scotland had COVID-19 (95% credible interval: 41,600 to 64,600), equating to 1 in 100 people (95% credible interval: 1 in 125 to 1 in 80).

If there are less than 100k people in the population (which is what I think you meant) then yes they would have to scale up the actuals accordingly to give a comparable figure. Nothing technically wrong with that but does raise eyebrows. They do the same with the worldometer world covid per million figures in places where you have less than a million population.

The issue with scaling up is that you are extrapolating, which is often highly dodgy and can't be relied on.

Stats folk have been known to make (in retrospect) catastrophic and false claims.