A State of Fear: How the UK government weaponised fear during the Covid-19 pandemic by Laura Dodsworth (feel good novels .TXT) 📕

Apparently, their decision to present 50,000 cases by mid-October as a possibility was taken carefully, but it was widely suspected that the decision was made because the bigger the number, the greater the fear, and the more compliant the adherence by the population. The anonymous scientist who works within Whitehall told me, ‘You can’t do a pandemic without honesty and trust, but the problem is people don’t trust the government anymore. The Whitty and Vallance press briefing was the ultimate psyop. Even really intelligent people had so much cortisol flooding through them that they couldn’t think rationally. I know people who believed the fantasy graph. Now they’re sold on more lockdown.’

While death tolls and cases dominated the headlines, other metrics were quieter casualties. Discussion of all impacted metrics is essential for people to make cost-benefit analyses. Yet Covid deaths were not balanced against unemployment, the lengthening NHS waiting list, missed cancer screenings, national debt, business closures, or calls to suicide helplines. As Paton told me, ‘There is a lack of critical thinking about parallels. We don’t say no one is allowed to drive a car to prevent all road traffic accidents. We can have different value judgements, but it’s not unhealthy or wrong to discuss tradeoffs and take a cost-benefit approach.’

What is the result of all this fear-mongering? The messaging that was initially designed to help us stay safe by scaring us has been so effective that Britain quickly became the most frightened nation in Europe.1 People significantly over-estimated2 the spread and fatality rate of the disease. The British public thought 6–7% of people had died from coronavirus – around 100 times the actual death rate based on official figures. I tested this out on a neighbour and asked her what percentage of the British people had died. She said 10%. That would have been a very noticeable 6.6 million corpses.

Did using the metrics of fear work? Did it create more compliance in the British public? Whether you think people followed the rules or not will depend on your own experience and attitudes. I asked a dear friend if he and his partner had been compliant. He told me that they had followed the rules very strictly to start with, and they had always followed them in general. It transpired they had had people over to their house, but only a couple at a time and only for drinks, not for dinner, so that was alright in their eyes. Of course for a long time people couldn’t enjoy a drink in a pub without ordering a substantial meal so, although he had the best intentions, my friend was negligent in omitting the life-saving food. I expect most people followed the rules, but they broke them in small ways when it suited them.

One study3 in September set out to investigate adherence to ‘Test, Trace and Isolate’ as it was considered ‘one of the cornerstones’ of the recovery strategy. It found that only 18% of people self-isolated after developing symptoms and only 11% quarantined after being contacted by Test and Trace. People’s reported behaviour fell short of their intended behaviour, but this seems a very unsurprising insight into human nature.

The government and media whipped people into a sustained and at times hysterical fear. Then frightened people voted for harder lockdown measures in public opinion polls. Government then obliged the people with more restrictions. The restrictions didn’t allow the fear to subside, then people voted for more restrictions, and so on in a self-perpetuating doom-loop. Public health policy became a sick dog chasing its own tail.

There is another reason that the government focused on particular metrics during the epidemic. Key Performance Indicators (KPIs) are to civil servants what the Ten Commandments were to Moses.

KPIs enshrine the work of all professionals in a department towards improving those goals and evidencing how they are doing so. For Covid, the KPIs were ‘cases’ (positive PCR test results), hospitalisations and deaths. Once established, the KPIs would have superseded the metrics for the economy, or other aspects of public health, or anything else. Staggeringly, the Treasury revealed it did not forecast the economic impact of the second lockdown.4

The clearer and more easily measurable the KPI, the more powerful it is in rallying activity and obscuring contexts outside the KPI. These KPIs overtly act to blind the government and all civil society to anything else, and then effectively confuse journalists and the public, which in turn creates more fear. The Covid KPIs sit like greedy little gods on thrones made of skulls, demanding obsequious worship.

It gets worse. The Covid KPIs are not reported as they are actually defined. I noticed throughout 2020 that journalists, doctors and politicians would misuse them. For instance, ‘Patients admitted’ actually includes ‘people admitted to hospital who tested positive for COVID-19 in the 14 days prior to admission, and those who tested positive in hospital after admission. Inpatients diagnosed with COVID-19 after admission are reported as being admitted on the day prior to their diagnosis.’5 So, patients admitted with Covid aren’t just patients admitted with Covid – which is what anyone would assume unless they have read the small print – they are also patients who were admitted for something completely different, but tested positive routinely for Covid, as well as patients who were infected with Covid while in hospital. The overall total will be a useful measure when planning how to manage wards and healthcare, but as a public-facing metric it is misleading, and as a KPI it cannot solely respond to restrictions designed to reduce community transmission, when it is also driven by nosocomial infection.

Similarly, deaths were frequently reported using the figure that the UK government dashboard pushes to the top: death ‘by date reported’. Due to time lags in death registration those figures could be lumpy, subject to sharp ups and downs. There was always a dip on a Monday (after weekend delays)