COVID-19 and Lockdown

9 min readNov 11, 2020

The UK’s recent decision to enforce a second national lockdown compelled me to write an updated analysis of the pandemic so far.

My previous post on the topic, “The SARS-CoV-2 Pandemic”, provided an extensive evidence-based review.

However, given the current circumstances and the ongoing uncertainty among the general population, I wanted to emphasise the preponderance of evidence which unequivocally shows…

We should not be particularly fearful of COVID-19, and we should not be entering a second lockdown.

Be sceptical of test results

PCR tests can be used to detect the presence of viral material in a sample (or swab). They represent the primary method being used to diagnose COVID-19 in patients.

In laboratory conditions, PCR tests have demonstrated a median false positive detection rate of 2.3%. In other words, of all tests, 2.3% will falsely detect the presence of viral material.[1]

This false positive rate would suggest that, of all recent positive tests, around 33% are false positives.

However, there are several factors which may contribute to a higher false positive rate regarding the current use of PCR tests to diagnose COVID-19:

Under mass-testing conditions — where huge numbers of swabs are taken and handled by more people, and lab conditions are not consistent — it is likely that the margin for error would be higher.[2]
The true positive detection of viral material does not necessarily mean the presence of COVID-19, or even infectious material — even where viral load is high.
The testing process has been skewed towards finding false positives (due to the extremely high Ct limits being used).

Using tests to diagnose COVID-19 deaths

Despite the aforementioned uncertainties, COVID-19 death statistics appear not to be suffering from significant inaccuracies associated with using PCR tests for diagnoses, given their strong relationship with excess deaths.

Either the error margin associated with false positive diagnoses diminishes for severe COVID-19 cases; or deaths are being incorrectly linked to COVID-19, but these overestimations are being accounted for by undiagnosed COVID-19 deaths.

Figure 1: Based on data from Our World in Data and the Office for National Statistics.

Should we be scared of dying from COVID-19?

To consider this question, it is important to appreciate the value in using excess mortality statistics to measure the impact of a viral outbreak…

Excess mortality rates allow for better comparison between countries, as they not only avoid the problem of countries incorrectly or differently recording COVID-19 deaths, but also consider the excess deaths indirectly caused by the pandemic and responses to it. Furthermore, comparing age-standardised excess mortality rates across selected cities can reduce analytical challenges that arise from differences in population densities and age demographics.

How bad were excess deaths involving COVID-19?

In England and Wales, there were around 59,000 excess deaths between March and June.[3]

Over a similar period, the Office for National Statistics (ONS) found that approximately 25% of excess deaths did not involve COVID-19.

This suggests that COVID-19 was involved in roughly 44,250 excess deaths during the initial outbreak.

For context, this can be compared (albeit imperfectly) to the worst levels of excess winter deaths (EWDs) that have occurred over the last 30 years in England and Wales (EWDs refer to excess deaths between December and March compared to the rest of the year):[4]

2017/2018: 49,410.
2014/2015: 43,720.
1999/2000: 48,420.
1998/1999: 46,810.

This is not a comparison between COVID-19 and the flu, since EWDs are due to multiple causes. However, these figures highlight that, in general, the increased probability of death from COVID-19 during the initial outbreak was similar to that of a harsh winter season.

As discussed later, the evidence is extremely weak regarding suggestions that COVID-19 deaths will reach or exceed the heights seen during the first wave.

How vulnerable are the vulnerable?

Those who are particularly vulnerable include the elderly, and those with cardiovascular diseases, hypertension, respiratory diseases, diabetes, or some other obesity-related issues.[5][6][7][8][9][10][11][12]

Of all people who are infected by COVID-19, a certain percentage will die — this is referred to as the infection fatality rate (IFR, not to be confused with the case fatality rate, which considers only confirmed cases).

Current IFR estimates remain broadly inconclusive. However, a study published in Nature Journal suggests that the IFR is about 0.01% for 30 year olds, 0.1% for 50 year olds, 1.0% for 70 year olds, and between 5–11% for over-80s.[13]

In addition to age: location, sex, and comorbidities were found to be significant factors in determining the IFR. However, as recognised in the Nature Journal report, the IFR is likely to be lower in general, due to unaccounted for positive cases.

Why SAGE and the UK government are wrong

SAGE have been using theoretical and outdated models that do not accurately predict the spread of the virus and subsequent deaths, leading to huge overestimations in hospital admission rates and COVID-19 deaths.[14][15]

Using London as a reference population, the models used by SAGE have not properly accounted for the following factors:

Most people have long-term immunity post-infection, and there are several lines of evidence which support this. Firstly, while roughly 15–20% of people in London have tested positive for antibodies, it is likely that 25–31% have long-term immunity, not through antibodies, but T cell immunity.[16][17] Secondly, SARS-CoV-2 is an extremely stable virus — much like other coronaviruses — mutating at around half the rate of influenza, so vulnerability to mutations is unlikely.[18] Thirdly, various studies have found little to no instances of infectious viral material in re-positive cases.[19][20][21][22]
20–60% of the population are resistant to COVID-19 despite having no known exposure to the virus. This pre-existing immunity comes from previously having had other coronavirus infections.[23]
As discussed earlier, the IFR is not fixed, but dependent on a range of factors including age, location, sex, comorbidities, and race. For example, 40% of Londoners are under 30, where the IFR is well below 0.01%.[24]

These missed analytical considerations can partly be explained by examining the backgrounds of SAGE members, which reportedly do not span across all the relevant disciplines.[25][26]

Furthermore, the extent to which SAGE has considered the costs of lockdown remains unclear.[27][28]

As such, their advice to enforce a second lockdown is not only based on one-sided evidence, but also wildly inaccurate predictive models.

There has never been a need for national lockdown

The purpose of lockdown is not to stop people from getting infected, but to delay the spread of a virus in order to protect healthcare services from being overwhelmed; or, as the UK government has repeatedly said, to “save the NHS” and “save lives”.

So, to what extent did the first lockdown succeed in these objectives, and do we need a second one?

The initial outbreak

Nationally, bed occupancies did not exceed 90%; they remained at the same levels as those observed over the last ten years (between 85–90%).[29] However, as discussed later, viruses do not spread evenly through a country, but in small ripples following an initial wave.

As such, the government’s short-lasting localised approach to implementing control measures in order to reduce the spread of COVID-19 was more logical, and followed the recommendations of the World Health Organisation.

However, the necessity for any types of lockdown remains unclear, as the first national lockdown appears to have had little to no impact on COVID-19 infections and deaths.[30]

This can also be seen in Figure 2, which shows that the rate of increase in deaths started to rapidly decline two weeks before they would have done if lockdown was responsible for this decline. Furthermore, there was no significant change in the death rate around the expected time, suggesting that lockdown was not responsible for any sort of decrease whatsoever.

Figure 2: Based on data from Public Health England.

The “expected date of lockdown impact on deaths” was calculated based on the following:

Symptom onset occurs 4–6 days after infection.[31][32][33]
The mean duration from onset of symptoms to death is 18 days.[34]

As with other common cold coronaviruses, the spread of SARS-CoV-2 is likely to be seasonal. This further supports observations that the normalisation of excess deaths over the summer period was unlikely to have been significantly influenced by any control measures regarding COVID-19.

The “second wave”

The hypothesis that we will see a second wave is completely unevidenced by historical outbreaks of new diseases.[35] Any subsequent waves have actually been first waves in disparate locations, and are significantly smaller than initial waves.

Excess mortality figures can be used to understand the extent to which subsequent waves are impacting the population.

It is no surprise that the greatest proportion of excess deaths during the initial outbreak was in London, given the capital’s huge population flow both internally and with the rest of the world.

As expected, London is not experiencing a second wave based on excess mortality statistics, implying community immunity has been achieved.[36][37]

Other towns and cities with large excess deaths during the initial outbreak are unlikely to experience any increases in excess deaths of a comparable nature; however, the required data is not yet available from the ONS or PHE to confirm this expectation.

Furthermore, initial observations suggest that COVID-19 cases during the current so-called second wave started to level off around three weeks ago, while hospital bed occupancy is currently below 65% — significantly lower than any level recorded over the last ten years.

This extreme low is doubly concerning. Not only is there a very low risk of the NHS being overwhelmed any time soon, but it suggests that tens of thousands of patients who would normally be treated in a hospital bed are being neglected.

Sweden

While country-vs-country comparisons may be analytically flawed, it is reasonable to compare the impact of COVID-19 between similar cities, particularly in relation to their control measures.

As such, London can be compared with Stockholm, where there was no lockdown and mask-wearing was actively discouraged:[38]

Excess mortality in London was significantly higher than in Stockholm.
Excess mortality in both cities is currently within normal ranges (i.e. close to zero).

Figure 3: Shows the percentage change in the 2020 age-standardised mortality rates for London and Stockholm during the initial outbreak of COVID-19, from what would have been expected based on the five-year average. Data from the ONS. Population density figures are approximations based on a range of sources.

The horrendous costs of lockdown

It is not just our basic human rights which are needlessly sacrificed during lockdowns:

National lockdown has cost the British people hundreds of billions of pounds.[39]
Excess deaths from other causes are reaching into the tens of thousands.[40][41][42]
The severe negative psychological impacts of lockdowns are well-evidenced.[43]

Furthermore, it is the low-income families who are worst affected.[44][45]

The long-term effects of these over-reaching control measures are also likely to be detrimental.

This view is not unsupported. A recent letter to Boris Johnson, signed by over 500 academics including medics, scientists, and statisticians, expressed concerns that the government’s response is causing more harm than good.[46]

Exacerbating the issue is the opposition leader, Keir Starmer, who has continually called for even stricter, more harmful control measures throughout the pandemic.

This has to stop.

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