A State of Fear: How the UK government weaponised fear during the Covid-19 pandemic

Home > Other > A State of Fear: How the UK government weaponised fear during the Covid-19 pandemic > Page 17
A State of Fear: How the UK government weaponised fear during the Covid-19 pandemic Page 17

by Laura Dodsworth


  In 2000 Ferguson predicted there would be up to 136,00011 cases of Creutzfeldt-Jakob disease in the UK. In fact there were 178 over 20 years.12 In 2001, Ferguson’s modelling led to the policy of ‘contagious culling’ (culling healthy animals on neighbouring farms) which led to 6.5 million cattle, sheep and pigs being slaughtered, economically devastating Britain’s farmers. A report entitled Use and abuse of mathematical models: an illustration from the 2001 foot and mouth disease epidemic in the United Kingdom13 strongly concluded that ‘the slaughter that took place was grossly excessive’ and that ‘the rift between the models and the practical reality of implementation may be so huge as to make the models irrelevant’. In 2005, Ferguson said that up to 200 million people could die worldwide from bird flu. They didn’t.

  MP Esther McVey neatly argued that the Imperial modelling should not be considered infallible by pointing out that 2,700 prisoners were predicted to catch Covid and die, yet only 47 did. As she said in January 2021: ‘There is no better example of the scaremongering to drive government policy they wanted to see from the so-called experts than the predictions on prisoner deaths. I appreciate that these estimates aren’t an exact science but the difference between a prediction of 2,700 to the reality of 47 is embarrassing to say the least.’14

  At the time of publication the modellers on SPI-M have predicted a ‘pessimistic but plausible’ third wave in the summer of 2021, resulting in a further 59,000 deaths.15 Models are only as good as their ingested data and this model reportedly under-estimated vaccine efficacy, herd immunity and did not allow for the seasonality of a respiratory virus. So, what is the point?

  Model reliability doesn’t seem to need to be proven. There are no penalties for being over-cautious and getting it wildly wrong. And despite his track record, Ferguson et al are still producing models for the UK government, terrifying people and unleashing dire consequences on the way.

  PUBLIC HEALTH ENGLAND DEATH DATA

  Under Public Health England’s original system, a Covid death was anyone who tested positive for Covid and then died of anything at any time. So, if someone was run over by a bus, their death would be counted as a ‘Covid death’ if they had tested positive for Covid at any point in the past. No further explanation is needed about how wrong that is, and how it would inflate the death figures.

  The team at the Oxford Centre for Evidence-Based Medicine pointed out the anomaly and Matt Hancock, the Health Secretary, ordered an inquiry. Dangerously poor-quality data from Public Health England was misleading the government. Were Public Health England innocent of such a misleading mistake?

  The new system counted deaths within 28 days of a positive Covid-19 test. This would still include people who died from other causes – not all of these deaths were ‘from’ Covid either – but it was an improvement and resulted in the immediate removal of 4,149 deaths from the 15 July death count.

  As David Paton said, ‘The metrics always seem to err on the side of maximising numbers and it takes time to undo that, like with the Public Health England death counting. The BBC continued to report PHE death data even though the government had officially suspended it, so that had the effect of people thinking deaths were higher than they were. There is also a case for saying we don’t report daily cases and deaths for flu, so just reporting by day is damaging in itself.’

  And on a stronger note, the anonymous scientist who advises at Whitehall told me, ‘The higher the death toll, the more draconian the measures you can bring in. The plan would be to go with the big numbers and then say there was a problem with the figures.’

  THE BMA AND MASKS

  Some data has crumbled like icing sugar at the merest whiff of a challenge. Sadiq Khan quoted some quite astonishing figures: that someone not wearing a face covering had a 70% risk of transmitting the virus, but by wearing a mask the risk was reduced to 5%, dropping to 1.5% if both parties were wearing masks.16 The source was the British Medical Association (BMA). I contacted the BMA, which claimed that their Medical Academic Staff Committee and Public Health Medicine Committee had produced the calculations. Seven emails, two tweets and one phone call later, it turned out these figures had not been calculated by the BMA, but were ‘based on a presentation by Chinese infectious disease specialist Professor Wenhong Xhang in March’.17

  The BMA withdrew its claims, but by then the figures had been published on national broadcast and print media and in Twitter memes shared by Sadiq Khan, and are all still in circulation now. Associated Press Factcheck came to the same conclusion as me and labelled the claims ‘partially false’.18 The strange thing is that memes were circulating in other languages at around the same time and earlier, making BMA’s claim to have produced the calculations even more spurious.

  The effort to counter misinformation online has certainly seemed one-sided.

  HOSPITALISATIONS

  Sir Simon Stevens, the Chief Executive of the NHS, said on 29 December 2020 that 20,426 people were being treated for Covid in hospitals in England, which was higher than the previous peak of about 19,000 in April.

  Comparing two absolute numbers was problematic. During the winter we always have more patients than we do in April. Numerically there were more patients in December, but just presenting that as a crude statistic is disingenuous because we also had more beds nationally overall than we did in April and without the occupancy figures as a percentage it’s impossible for anyone to understand what the inpatient numbers mean. Further breaking down occupancy into overall total, ICU, beds with oxygen and mechanical ventilation beds for Covid and non-Covid would provide more insight.

  In April 2020, all the Covid patients were there because they were truly ill with Covid. Later, we were routinely testing people in hospitals regardless of why they were admitted, which was a sensible measure for infectious control, but meant some people were classed as Covid patients in the government dashboard figures but were actually in hospital for different reasons. The absolute number of 20,426 includes those admitted with Covid and diagnosed with Covid in a hospital setting. So, what was the total split by people who go into hospital because they had Covid, nosocomial infections (acquired in hospital) and those who were routinely tested when they were in for something else and had a positive test result? Answers to those questions would have revealed how much of a problem community versus nosocomial infection was and helped guide decisions about the value of restricting liberties in the community.

  An NHS England data scientist who must remain nameless for the sake of their job, shared some confidential information with me. We looked at the data for the south-east and London when I was writing to my MP about the tier restrictions at the time. At that point my MP told me that local hospitals were overwhelmed with Covid admissions. In fact, in mid-December in the south-east and London only 20% of the total hospital admissions were patients actually admitted with Covid. About 25% of ‘hospital admissions’ had caught Covid in hospital. And the remaining 55% had been tested while in for another matter and found to be positive. By January 2021 the government had admitted (albeit in a very low key no-fanfare way) that test results could be positive ‘long after’ someone is infectious.19 Which means that of those 55%, an unspecified but significant number will be ‘false positives’. All this paints a different picture. In addition, approximately 30% of the most recent admissions were from care homes, therefore also nosocomial infections, as they were acquired in a care setting.

  Another important consideration is staffing levels. Talking about absolute numbers of in-patients requires the context of occupancy percentages and also staff available to look after them.

  A responsible government and NHS would be providing this context. The use of absolutes was not untruthful, but it obscured more important facts. It seemed like a false flag, designed to create alarm and therefore soften us up for the next tranche of emergency restrictions. A BBC article20 reporting on Stevens’s statement only gave a modicum of context and led straight into a scientist’s call for more lockdow
n, in what had become a familiar government-media lockstep.

  The use of alarmist data is, well, alarmist, and the elision of detailed data is suspicious. Combined, this erodes trust in leaders and the media.

  I emailed NHS England’s media team with a request for all of this data. I followed up with emails, phone conversations and tweets. I did not receive the data.

  By March 2021, Covid hospitalisations were at the same levels as October 2020. Strangely, Simon Stevens did not provide an update to the nation. As usual, numbers were used to scare, but not to reassure.

  THE WHITTY AND VALLANCE ‘SHOCK AND AWE’ PRESENTATION

  Chief Medical Officer Chris Whitty and Chief Scientific Adviser Sir Patrick Vallance warned on 21 September that there could be 4,000 Covid deaths per day in the autumn. Nothing like that total was ever reached. The Vallance chart showed infections hitting 50,000 cases a day by 13 October without action. When this day arrived, the moving average was 16,228.

  Former Prime Minister Theresa May criticised the government’s approach, remarking that ‘for many people it looks as though the figures are being chosen to support the policy, rather than the policy being based on the figures’. Even The Guardian, which in general took a pro-lockdown approach during the epidemic, commented that the ‘data was selective… determined to cause alarm’.21 In a highly unusual move, the UK Statistics Authority also voiced concerns that the graphs presented to the public were out of date and over-estimated deaths.

  THE SECOND WAVE

  Public Health England said that more people died in the ‘second wave’ compared to the first wave of the epidemic.22 Yet according to the Continuous Mortality Investigation, set up by the Institute and Faculty of Actuaries, there were 72,900 excess deaths from March to the end of December. 60,800 of those occurred in the first wave, but just 12,100 in the second.23 It means that, unlike the first wave, huge numbers of people included in the coronavirus death figures would have been expected to die of other causes in those final few months of the year. It seems unlikely – impossible even – that Public Health England would not know this.

  THE MOST DEADLY INFECTIOUS DISEASE IN A CENTURY

  To mark the anniversary of a year of restrictions, the ONS produced a report which declared Covid-19 to be the most deadly infectious disease to hit Britain for over a century. Naturally this led to lurid doom-laden newspaper headlines such as ‘Coronavirus is the deadliest pandemic to hit Britain since the Spanish flu in 1918 and has caused the worst recession in 300 years – but house prices KEPT going up’,24 ‘COVID-19 most deadly infectious disease in UK in 100 years’25 and ‘Devastating UK Covid data lays bare impact of virus on lives, jobs and society in 2020’.26

  But according Covid the accolade of causing ‘more deaths in 2020 than other infectious diseases caused for over a century’ was only possible with a disorientating twisting of truths. The ONS categorised Covid as an ‘infectious and parasitic disease’, putting it in a different category to other respiratory diseases including influenza. In this surprising category, Covid wasn’t even keeping company with sepsis, as David Livermore, Professor of Medical Microbiology at the University of East Anglia, wrote for the Lockdown Sceptics website. As he pointed out, the ONS’s graph ‘wildly underestimates infection deaths’ such as for bacterial sepsis and flu, which falsely elevated the deadliness of Covid.

  Lockdown Sceptics asked ‘What was the ONS thinking producing such a misleading graph and report, knowing full well it would grab lurid headlines and feed the hysteria that has characterised the last 12 months?’27 This was a disheartening report from the ONS, but it was at least in keeping with marking a year of the ‘metrics of fear’.

  THE PCR TEST

  ‘We have a simple message for all countries: test, test, test,’ said Dr Tedros Adhanom Ghebreyesus, Director General of the World Health Organization, on 16 March 2020.28

  How would countries test? Using the PCR (polymerase chain reaction) test.

  On 14 December 2020, the WHO issued an Information Notice for IVD Users ‘to ensure users of certain nucleic acid testing technologies are aware of certain aspects of the instructions for use for all products’.29

  As many doctors and scientists had pointed out, the PCR test can produce false positives as well as false negatives. One problem is that when run at a high cycle threshold (Ct), the test can create a false positive, or pick up that someone had an infection weeks earlier. It is not a definitive test of infection or infectiousness.

  As the notice says, ‘when specimens return a high Ct value, it means that many cycles were required to detect virus. In some circumstances, the distinction between background noise and actual presence of the target virus is difficult to ascertain… the cut-off should be manually adjusted to ensure that specimens with high Ct values are not incorrectly assigned SARS-CoV-2 detected due to background noise.’

  In Portugal, judges ruled that a single positive PCR test cannot be used as an effective diagnosis of infection for the purpose of quarantining someone.30 Did the WHO issue the notice because of concern about legal action? When only a small proportion of people being tested have the virus, the operational false positive rate becomes important – think how many people might have had to quarantine unnecessarily, missing work, or an urgent medical exam, or to the detriment of their mental health, for example. For some people, being told they were positive with a disease that has been described ‘the greatest threat in peacetime’ could have been very stressful. Lockdowns and restrictions were based on the number of ‘cases’. And absolute totals of cases were used to scare people into complying with the rules.

  The Ct in the UK appears to be set at 45. As Professor Carl Heneghan said when he gave evidence in the House of Commons to the Science and Technology Committee on 17 September 2020, ‘A cycle threshold above 35 generally involves people who are not infectious, yet NHS England documentation that has not been updated since January runs cycle thresholds to 45 that identify people who are not infectious.’

  Heneghan was asked about introducing random testing – mass testing – as Professor Alan McNally of Birmingham University had recommended. This was his answer: ‘In effect, you are saying that random tests will pick up people, potentially with dead virus. Remember, it picks up an RNA strand that is 220 nucleotides long. That degrades much slower than the actual infection when you have it on board. After eight days, we cannot isolate live virus, but for up to 90 days you can isolate the RNA fragments and pick them up when you test, so, if you randomly go into schools, you might as well shut them down right now. It is not a process that I have recognised in 20 years’ experience of being a clinician, as a GP, or a process that is aligned with evidence-based medicine. If we are to go down those routes, we have to think of the wider context of what harms they introduce, what the social consequences are and what the plan is.’ The UK government rolled out mass testing and proposed mass testing in schools. Although, when mass testing was introduced in schools in March 2021, the less sensitive lateral flow test was used.

  POSITIVE TESTS, CASES AND PATIENTS

  This is an example of scary semantics rather than dodgy data. People who tested positive were called ‘cases’ and in one case I noted the word ‘patient’31 was used. Both ‘case’ and ‘patient’ imply illness and symptoms, whereas many of the positive test results were asymptomatic or post-infectious. A medical diagnosis of ‘case’ would normally involve symptoms plus a positive test, not a test on its own.

  DEATH STATISTICS

  I was flung into my armchair death-expert status by the whiplash of an epidemic and lockdown. The next chapter explains how changes to the death registration process mean there are now serious problems with counting the dead.

  EMILY, 45, NURSE

  A colleague who does the bookings emailed me to say, ‘You’ve got a patient coming in for an overdue blood test this afternoon, she’s really nervous and she’s been shielding since March. Can you meet her from the car to make sure she attends?’

&
nbsp; It’s not unusual to have a nervous patient – needle phobia is certainly not uncommon! The appointment time came, but I was busy finishing off with another patient so I hadn’t made it out to the car park. As I completed some forms I suddenly heard shouting and screaming coming from the reception area. I rushed out and saw a lady, obviously very distressed, walking with two sticks and wearing a mask and visor, supported by a man. She was incomprehensibly sobbing, shaking and flushed, as she staggered down the corridor.

  I rushed over (obviously in standard mask and apron) and tried to calm her down and ascertain what was wrong, encouraging her to come into the blood test room to sit down.

  She continued to cry and hyperventilate. It was difficult to comprehend anything that she was saying. I was worried that she was becoming increasingly short of breath, so I encouraged her to remove her mask but her husband said she wouldn’t take it off because she was ‘too scared of the virus’.

  I asked her if she was nervous about the blood test but she continued to cry in a distressed manner, saying over again, ‘I don’t want to die, I’m so frightened, I don’t want to die, I’ll die of anything but not that virus.’ I managed to get her to slow her breathing and stop moving long enough to get the sample. Her husband told me that this was only the second time she’d left the house since March.

  11. COUNTING THE DEAD

  We humans keep dying. We always have. We always will. In 2019, approximately 57,000,000 people died globally, and 600,000 people in the UK, which equates to 1,600 people per day. As the only real certainty of life is that we are all going to die, we should be better at the death business by now.

  It’s important to count the dead. We count the big numbers and compare them annually – excess deaths are a barometer that ‘something is happening’. But we also need to know and record how people die, for public health management, planning NHS resources in the future, to inform government policy, for legal and jurisprudence reasons, and to provide certainty and alleviate the concerns and grief of the bereaved’s family.

 

‹ Prev