The Figures Don’t Match Up To the Fear, a Doctor Writes

There follows a guest post from our in-house doctor, formerly a senior medic in the NHS, who says the widely trailed tsunami of hospitalisations has not only failed to arrive after ‘Freedom Day’, but we seem to be on the downslope of the ‘third wave’.

The philosopher Soren Kierkegaard once remarked: “Life can only be understood backwards, but must be lived forwards.” I have been reflecting on that comment, now we are three weeks since the inappropriately named July 19th ‘Freedom Day’. Readers will remember the cacophony of shrieking from assorted ‘health experts’ prophesying certain doom and a tidal wave of acute Covid admissions that would overwhelm our beleaguered NHS within a fortnight. Representatives from the World Health Organisation described the approach as “epidemiologically stupid”. A letter signed by 1,200 self-defined experts was published in the Lancet predicting imminent catastrophe.

Accordingly, this week I thought I should take a look at how the apocalypse is developing and then make some general observations on the centrality of trust and honesty in medical matters.

Let’s start with daily admissions to hospitals from the community in Graph One. Daily totals on the blue bars, seven-day rolling average on the orange line. Surprisingly the numbers are lower than on July 19th. How can that be?

Perhaps there are more patients stacking up in hospitals – sicker patients tend to stay longer and are hard to discharge, so the overall numbers can build up rather quickly. So, Graph Two shows Covid inpatients up to August 5th. Readers should note that Graph Two includes patients suffering from acute Covid (about 75% of the total) plus patients in hospital for non-Covid related illness, but testing positive for Covid (the remaining 25%). How strange – numbers seem to be falling, not rising. This does not fit with the hypothesis – what might explain this anomalous finding?

Maybe the numbers of patients in ICU might be on the increase – after all, both the Beta variant and the Delta variant were said to be both more transmissible and more deadly than the Alpha variant. Graph Three shows patients in ICU in English Hospitals up to August 5th. It shows a similar pattern to Graph Two – a small fall in overall patient numbers in the last two weeks. I looked into the Intensive Care National Audit and Research Centre ICU audit report up to July 30th. This confirms the overall impression from the top line figures. Older patients do not seem to be getting ill with Covid. Over half the admissions to ICU with Covid have body mass indices over 30. Severe illness is heavily skewed to patients with co-morbidities and the unvaccinated. Generally speaking, the patients have slightly less severe illness, shorter stays and lower mortality so far.

Finally, we look at Covid related deaths since January 1st, 2021, in Graph Four. A barely discernable increase since the beginning of April.

So, whatever is going on with respect to the progress of the pandemic, the widely trailed tsunami of hospitalisations has not arrived yet – in fact, we seem to be on the downslope of the ‘third wave’.

Often in an experiment or scientific investigation, the observed results don’t fit the expected outcome. On such occasions, it’s wise to revisit the base assumptions and re-examine the raw data to see if we made a measurement error or a calculation error.

Rather helpfully, last week the NHS did release some information in relation to the numbers of patients in hospital ‘with Covid’. Regular readers may recall I wrote about it. In essence, the revelation was that the NHS numbers in Graph Two consistently over-estimate the numbers of patients with acute Covid illness by about 25%.

The NHS were only able to provide data back to June 18th, 2021, but their clarification cleared up a point that had been bothering me since I wrote an analysis of a large data set published in the Lancet looking at Covid inpatients between January and August 2020. The analysis showed that 25% of the patients recorded as Covid positive last year did not require oxygen in hospital. I thought that very odd but maybe the explanation is that the NHS has been overestimating the numbers of acute Covid patients by about a quarter since the pandemic began. There may be other explanations, but the numbers are remarkably consistent. If anything, the corrected raw data suggests we have a lower burden of Covid related disease than we thought a few weeks ago.

This brings me to my next point – the absent signal. When a predicted signal fails to show up, we need to ask why. Did we miss it? Were we looking in the wrong place? Or were our assumptions wrong in the first place?

As the numbers don’t support the imminent catastrophe hypothesis, I expected to see a signal from the ‘health experts’ revising their predictions and explaining the experimental error which led them to frame an incorrect hypothesis. So far, I haven’t seen that signal – admittedly I don’t watch TV so could have been looking in the wrong place. I did notice Professor Ferguson predicting 100,000 cases per day (by which he meant positive tests on largely asymptomatic people) by the end of July. Oddly a couple of days later he was back on the airwaves commenting that the pandemic was over. These statements seem to me to be contradictory – yet there was no explanation as to how he came to the 100,000 figure, nor as to what had changed to make him revise his assessment so rapidly.

Readers may think I’m being flippant and overly critical of our public health scientists, but this is an important point. In medical science, the ability to critically assess information and admit errors is very important. Dogmatic adherence to a particular belief in the face of evidence to the contrary can be dangerous as it compounds error and makes repeated mistakes more likely. Given the hugely significant consequences of the advice given by Ferguson and his confederates in SAGE and the confidence with which they make predictions which turn out to be incorrect, this absent signal is crucially significant.

While on the subject of data interpretation and presentation, I noticed the new NHS Chief Amanda Pritchard was on the media round speaking of the high percentage of younger people currently in hospital with Covid – her key point being that people aged 18-34 made up 20% of admissions compared to five per cent in January. For some reason, she forgot to put her remarks in context – Graph Four and Graph Five provide that context.

Graph Four shows a clustered column of daily admissions by age. Readers can clearly see overall admissions running at just over 600 a day compared to over 3,500 in mid-January and that the slope of the curve on the right-hand side is downwards.

Graph Five shows the percentage breakdown of admissions by age. Clearly, the percentage of younger people has increased as a proportion of the total, but this is because the numbers of older people admitted for Covid has collapsed. There are no greater numbers of younger people being admitted per day than there were in January, but far fewer older people. Hence the relative percentage of younger people has risen as the overall total has fallen.

Why does this matter? The NHS argue that Covid still presents hazards to younger people and that selective presentation of statistics and the use of frightening adverts in the press are a justifiable way of persuasion. It is a classic ‘ends justifies the means’ argument. I thought medicine had left this paternalistic (or should I say ‘nannying’) mindset a long time ago – but as with many things, I find I’m mistaken. There is a reasonable argument to be made for Covid vaccination in young adults – but I don’t think selective use of data is a sensible way to make it, because eventually, it damages trust in important civic institutions. In one of my first posts on the Lockdown Sceptics website, over a year ago, I commented on the tendency of the NHS to misuse or ‘manage’ the presentation of data. I think that concern has been borne out over the last 12 months.

The Government may take the view that we have no time for such philosophical niceties as we remain in the midst of a crisis. I think the numbers refute this, and that trust is fundamental to the functions of a democratic society. To return to Kierkegaard: “There are two ways to be fooled. One is to believe what isn’t true; the other is to refuse to believe what is true.”

Fool me once, shame on you. Fool me twice, shame on me.

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