Hospitalisations

Government Officials Continue to Tell Half the Story on Covid Statistics

The U.K. Statistics Authority says it is concerned by the misrepresentation of Covid data by the Government and its head, Sir David Norgrove, points out that “we’ve intervened more during the pandemic and made more comments than in the years before”. It is, of course, expected that mistakes are to be made on occasion, but it’s concerning that time and again these mistakes are being repeated, and with damaging consequences. The Telegraph has published a good piece on this.

“With statistics, it’s usually cock-up rather than conspiracy,” [Sir David] added. “They are under pressure and they get themselves into a hole and we have to help dig them out.”

Yet despite this, nothing seems to be changing.

At a press conference from Downing Street on Wednesday evening, Dr. Jenny Harries, the Chief Executive of the U.K. Health Security Agency, took the public through slides showing that there were currently 7,891 people in hospital with Covid in the U.K.

What she failed to mention is that this figure does not only include people admitted with Covid, but also those who test positive for coronavirus while in hospital for another condition.

Hospitals were instructed to distinguish between the two groups earlier this year, but so far it has not filtered down into the official figures.

In fact it is only possible to find the data by scrolling to the very bottom of the “Hospital Activity” page of the NHS website. Even then, the figures are woefully out of date.

At the most recent count for England on October 12th, 26% of the overall cases were not primarily Covid.

If that was extrapolated to Dr. Harries’ British data, it would mean that more than 2,000 people included in the Government’s press conference figure are actually in hospital for other causes.

A similar problem can be seen in the daily reported death figures published on the Government’s coronavirus dashboard. On Tuesday, many experts seized on 223 reported deaths to argue that Britain should enact ‘Plan B’ restrictions.

But the reported death data does tend to jump around depending on the day of the week and reflects deaths over several days. Look at the figures by “date of death”, and it is clear to see the situation is largely plateauing.

Dr. Jason Oke, a senior statistician at the University of Oxford, pointed this out earlier this week, saying: “As we have said right from the beginning, we need to focus on deaths by date of occurrence, not deaths by date reported. 

“Reporting Tuesday’s numbers – always the highest – in isolation, tends to exaggerate things, and gives no indication of current trends, which has if anything been slowly falling through September and October, [and] no guarantee of future trends of course.”

Regular readers of the Daily Sceptic won’t be surprised by this report on the misrepresentation of data, especially given our in-house doctor’s repeated highlighting of “a remarkable consistency in [officials] grossly overestimating the numbers of Covid hospital admissions“, and more – but the Telegraph story is still worth reading in full.

Infection Rate in Vaccinated People in Their 40s Now More Than DOUBLE the Rate in Unvaccinated, PHE Data Shows, as Vaccine Effectiveness Hits Minus-109%

In the latest Vaccine Surveillance report from Public Health England (PHE) the infection rate in double-vaccinated people in their 40s went above 100% higher than in the unvaccinated for the first time, reaching 109%. This translates to an unadjusted vaccine effectiveness of minus-109%.

Vaccine effectiveness continues to drop fast in all over-18s (see chart at top), hitting minus-85% for those in their 50s, minus-88% for those in their 60s and minus-79% for those in their 70s. (For definitions and discussion of limitations see here.)

New York Times Forced to Correct Article Claiming 900,000 Children Hospitalised by Covid – Real Figure Is 63,000

The New York Times has been forced to retract a claim by its reporter Apoorva Mandavilli that “nearly 900,000 children have been hospitalised with Covid since the pandemic began”. This figure isn’t just slightly off the mark – it’s 837,000 cases too high.

Mandavilli included this exaggeration in a piece on the vaccination of healthy children against Covid. It is bound to have swayed some minds. The National Review has more.

Mandavilli has been a controversial figure at the Times for her ideologically-colored pandemic coverage. In May, she tweeted: “Someday we will stop talking about the lab leak theory and maybe even admit its racist roots. But alas, that day is not today.” She later deleted the tweet but not before adding: “A theory can have racist roots and still gather reasonable supporters along the way. Doesn’t make the roots any less racist or the theory any more convincing, though.”

The theory has not yet been disproved. To the contrary, it has picked up a number of prominent supporters in the scientific community, including former Times reporters Nicholas Wade and Donald McNeil. McNeil was the lead coronavirus reporter at the publication prior to his being fired and smeared by the Times for uttering a racial epithet in the context of discussing its moral valence and grace on an educational trip several years ago.

The correction is notable as the nature of the threat that coronavirus poses to children figures heavily in the continued and often partisan debates over vaccine and mask mandates in schools.

While Republicans such as Florida governor Ron DeSantis maintain that such decisions should be left up to parents, President Joe Biden and American Federation of Teachers head Randi Weingarten have advocated for mandates, insisting that they’re necessary to protect students and staff alike.

Worth reading in full.

The Modellers Keep On Making the Same Errors – And the Implications Are Huge

There follows a guest post from our in-house doctor, formerly a senior medic in the NHS, who draws attention to the errors made repeatedly by the modellers and government advisors and the huge implications of them.

Napoleon Bonaparte remarked that “history is the version of past events that people have decided to agree on”. When the official version of the pandemic is written, I wonder what analysis will be made of the role of statistical modellers and public health experts in driving Government policy over the last 18 months?

To inform this question it may be helpful to examine the recent evidence of how predictions have matched up to real events. For example, on September 8th, SPI-M-O (one of the multitudinous acronym salad bodies advising the Government), produced a paper entitled “Medium-term projections“.

Perhaps mindful of the woeful inaccuracy of previous predictions, the very first sentence heavily caveats the entire document:

These projections are not forecasts or predictions. They represent a scenario in which the trajectory of the epidemic continues to follow the trends that were seen in the data up to September 6th.

If that is the level of confidence the authors of the report have in their own abilities, one rather wonders what value this publication contains – yet this is the level of advice being given to decision-makers.

Firstly, to the “projection” of admissions. The document is in PDF format, so I am unable to reproduce it here, but the graphical representations show a 90% confidence interval fan chart for the period September 12th-28th. Hospital admissions in England are “projected” to be between 600 to 1,200 per day – a fairly wide spread. Graph One shows what actually happened – daily admissions on the blue bars, seven-day moving averages on the brown line.

It is clear that admissions have been consistently below the lower ‘projection’ for the entire period and the seven-day moving average at the end of the month was below 500 admissions per day.

Like Freddy Krueger, Professor Lockdown Refuses to Admit Defeat

No matter how many disastrously inaccurate predictions he makes, Professor Neil Ferguson is still doing the rounds of broadcasting studios and the parliamentary estate brandishing his crystal ball. His latest appearance was in front of the All Party Parliamentary Group on Coronavirus earlier today, where he warned that ‘Plan B’ would have to be activated if Covid hospital admissions climb above 1,200 a day. MailOnline has more.

England may have to resort to its winter Covid ‘Plan B’ if daily hospital admissions for coronavirus breach 1,200, ‘Professor Lockdown’ Neil Ferguson said today.

Boris Johnson announced last month that face masks, social distancing and vaccine passports might need to be brought back if the NHS comes under unsustainable pressure.

Ministers said the trigger point will be hospital rates now that the jabs have made case numbers less important – but they have not put a threshold on admissions.

Professor Ferguson – a key Government adviser whose modelling prompted the first lockdown last March – suggested England should not tolerate more than 1,200 daily hospitalisations. For comparison, Covid admission levels breached 4,000 during the darkest days of the second wave in January.

Speaking to a cross-party committee of MPs today, he said that the country was currently recording around 600 Covid admissions per day.

He added: “If that figure were to double, we’d need to think about moving to ‘Plan B’.” The epidemiologist, based at Imperial College London, called for “more intense” curbs if there is a sharp rise in admissions.

To get ahead of a winter wave, he said second doses for 16 and 17 year-olds could be brought forward and advised we are “more aggressive” in administering boosters.

Worth reading in full.

Stop Press: The Daily Sceptic‘s in-house doctor has sent through the latest INARC NHS England data, which shows current Covid hospital admissions steadily declining since Covid restrictions were eased on July 21st, in spite of Prof Ferguson’s prediction that cases would rise to 100,000 a day – that was “almost inevitable”, according to Mystic Meg – and possibly to 200,000.

Current daily hospital admissions have stabilised around 600, but ICU admissions continue to decline (see below). Still no sign of the much ballyhooed “surge” after schools reopened.

Democrats Still Dramatically Overestimate the Risks of COVID-19

In a previous post, I noted that people tend to overestimate the risks of Covid, especially the risks to young people – which are vanishingly small.

In a Gallup poll last year, 41% of Democrat voters in the U.S. said that the risk of hospitalisation is at least 50%! (And Republicans didn’t do much better). However, that poll was taken in December. Has people’s understanding improved since then?

According to a new poll, the answer is ‘not at all’. Gallup posed a similar question as before, only this time they asked about vaccinated and unvaccinated people separately.

Note: the questions were not identical. In last year’s poll, they asked, “What percentage of people who have been infected by the coronavirus needed to be hospitalised?” In the recent poll, they asked, “What percentage of people have been hospitalised due to the coronavirus?”

The denominator for the first question is ‘people who have been infected’, while the denominator for the second is ‘everyone’. However, many respondents may have assumed that the second question was referring to ‘people who have been infected’. This should be kept in mind when interpreting the results.

The chart below shows results for the version of the second question that asked about unvaccinated people:

Once again, 41% of Democrats (and 22% of Republicans) said that the risk of hospitalisation for those who aren’t vaccinated is at least 50%. The correct answer is less than 5%, so these respondents were off by a factor of more than 10. Only 42% of Republicans – and just 18% of Democrats – were in the right ball-park.

Democrats did do substantially better when asked about the risk to vaccinated people, as the chart below indicates. In this case, the majority of both groups were in the right ball-park. However, more than one in five respondents still gave an answer of 10% or more.

As I mentioned last time, part of this overestimation may reflect a general psychological tendency to overestimate small quantities; though I should stress, only part. After all, Republicans were much less likely to answer “50%” when the question referred to unvaccinated people.

It’s staggering that 18 months after the start of the pandemic, almost one third of Americans say the risk of being hospitalised from Covid if you’re not vaccinated is at least 50%. Clearly there has been a failure of communication on the part of public health authorities.

This finding may help to explain bizarre phenomena like the fact that young, fully vaccinated Americans are still wearing face masks outdoors.

One Stanford student, Maxwell Meyer, spent an hour ‘bike-spotting’ on a popular campus thoroughfare. For each bike that went past, he recorded whether the rider was wearing a helmet, a face mask, or both. Of the 400 cyclists that he observed, 34% were wearing a mask but no helmet! (And 7% were wearing both.)

Aside from some people simply being clueless about the risks, Meyer notes that wearing a mask has become a form of social signalling (‘I’m the sort of person who cares about doing his part’). Though of course, wearing a mask under such circumstances does approximately nothing – other than raise the question of how on earth you got into Stanford.

Even after lockdowns ended, various types of ‘Covid theatre’ have dragged on for months. This isn’t so surprising when you consider people’s skewed perceptions of the risks.

A Doctor Writes: The NHS Is Concealing Important Information from the Public

We’re republishing a post from our in-house doctor, formerly a senior medic in the NHS, on the unreliability of official figures on ‘Covid inpatients’ . This was first published in July and only now has the mainstream media finally cottoned on to the fact that the NHS’s Covid inpatient figures are unreliable. Since we published this, there have been at least three updates to the ‘primary diagnosis schedule’, all showing a consistent overstatement of 25%.

On Thursdays, the NHS release the weekly summary data in relation to Covid patients. Normally this is a more granular version of the daily summaries – it has some hospital level detail and figures on non-Covid workload for comparison. Usually interesting but not especially informative.

Yesterday was an exception. Placed down at the bottom of the page, almost like a footnote, was a “Primary Diagnosis” Supplement. Graph One shows the information contained in that spreadsheet. I find it astonishing. In essence, it shows that since June 18th, the NHS has known its daily figures in relation to ‘Covid inpatients’ were unreliable at best and deliberately untrue at worst.

The Yellow bars are what the NHS has been informing the nation were Covid inpatients. The Blue bars are the numbers of inpatients actually suffering from Covid symptoms – the difference between the two are patients in hospital who tested positive for Covid but were being treated for something different – where Covid was effectively an incidental finding but not clinically relevant.

For example, on July 27th, the total number of beds occupied by Covid patients was reported as 5,021. However, until today, we were not permitted to know that only 3,855 of those were actually admitted with Covid as the primary diagnosis. There has been a fairly consistent overestimate of the true number by about 25% running back to mid June – figures before that date are ‘not available’.

Why does this matter?

Well in one way it doesn’t matter very much. Whether the burden of Covid inpatients is 5% of the available beds or 3.5%, isn’t massively significant – it’s still a relatively small proportion. NHS managers are already arguing that even patients with Covid being treated for another condition still need isolation procedures and present an extra burden on the system. They may argue that the NHS is still under strain from staff absences, stress levels and the waiting list backlog – so it doesn’t really matter if the published figures are somewhat inaccurate.

But it matters hugely.

The Government’s Latest Scary Modelling is Already Wrong

There follows a guest post by Daily Sceptic reader Graham Williams (a pseudonym), a maths graduate and by profession an analyser of business plans, models, forecasts and funding requests. He is not impressed with the latest Government pandemic modelling.

I have just read the SPI-M consensus statement paper of September 8th, which appears to be at the heart of the recent stories about possible future lockdowns etc. This paper seems to be as big a load of negative, hyperbolic scaremongering as all the ones they have issued so far this year (February at the start of the roadmap, March, April, June and July).

In paragraph two they state: “SPI-M-O groups have reflected on their modelling of Step 4 of the Roadmap, and despite unexpected falls in cases in mid-July 2021, these scenarios can still be used to consider the future autumn and winter trajectory.”

They appear however not to have reflected that were it not for the unforecast Delta variant their modelling since February would have overstated the position of deaths, cases, and hospitalisations by June 21st by around 1,000%. Even with the rise caused by the variant, their forecasts remained hugely overblown, but they still continue to model with the same flawed methodology.

After paragraph two there follow about 18 paragraphs of largely unsubstantiated waffle with a few facts thrown in.

One of the facts is that R is currently (i.e., at the date of the paper) between 0.9 and 1.1, so broadly flat. The covering page to the report says: “These are not forecasts or predictions… They are based only on the observable trends and data available at the time the projections were produced.”

Had the modelling actually done what it said on the tin, project observable trends, then it would have been in line with their own medium-term projection of September 8th, which shows a fairly flat trend for September, even if arguably the base they have used is a bit low.

Almost a Quarter of ‘Covid Inpatients’ in England Are Primarily Being Treated for Something Else

It’s not been a good week for followers of conventional wisdom. The official lines on face masks and long Covid have (once again) been brought into question and now Government figures have shown (also not for the first time) that hospitalisation numbers are being skewed by the fact that almost a quarter of ‘Covid inpatients’ in England are actually in hospital for a different reason.

Given that “increasing Covid hospital admissions” could trigger the Government’s ‘Plan B’ of mask mandates and vaccine passports (and even perhaps ‘Plan C’ of another lockdown), the implications of this distortion of the truth could be huge. MailOnline has more.

Health service statistics show there were 6,146 NHS beds taken up by people who were Covid positive on September 14th, the latest date data is available for.

But just 4,721 patients (77%) were primarily being treated for the virus, with the remaining 1,425 receiving care for other illnesses or injuries. They could include patients who’ve had a fall or even new mothers who tested positive after giving birth.

In NHS hospitals in the Midlands, around a third of Covid patients were mainly being treated for another reason on September 14th.

Separate NHS figures suggest as many as half of daily hospitalisations only test positive after being admitted for a separate condition.

Hospital numbers have become the key metric for ministers and their scientific advisers, now that vaccines have taken the emphasis away from infection numbers.

Boris Johnson has said lockdown curbs may have to be reintroduced if Covid hospital numbers rise sharply as part of his winter blueprint to tackle the virus, which could see masks and working from home mandated again.

But he did not put a firm figure on the threshold that would trigger the return of restrictions when he announced the contingency plans earlier this week.

The latest figures suggest the standard Covid hospital numbers have become a less reliable way of gauging the outbreak and NHS pressure. [Have they ever been reliable?]

Worth reading in full.

Health Secretary Attempts to Outline What Could Trigger ‘Plan B’ This Winter

Just as plans for vaccine passports at ‘large venues’ left us wondering where exactly the measures would be enforced, we have been left in the dark about what will push the Government to enact ‘Plan B’ (including mask mandates and vaccine passes) or ‘Plan C’ (another full lockdown) this winter. Health Secretary Sajid Javid attempted to clarify the issue this morning but was coy about the specifics. Sky News has the story.

The Health Secretary has said A&E pressures and increasing Covid hospital admissions could trigger the Government’s Plan B for the winter – as experts warned hospital admissions could reach 7,000 a day.

Sajid Javid added that a new variant of concern would not necessarily be a trigger as he refused to rule out a lockdown.

Plan B, which includes mandatory face masks, a work from home order and vaccine passports, was revealed by the Government on Tuesday as part of the autumn and winter plan for dealing with the Covid pandemic.

The Health Secretary told Sky News: “What happens in the NHS is going to be hugely important to me, to the whole country, making sure that we don’t get to a position again where the NHS becomes unsustainable.

“I think we’re going to have to look at a number of measures, so of course that would be the level of hospitalisation, it will be the pressures on A&E, the pressures on the workforce, so we’d have to take all of these together.”

However, he refused to put a number on how many cases or admissions would trigger plan B.

Worth reading in full.