Coronavirus UK – while Johnson fiddles, the UK burns

Written by Joel Smalley MBA on June 9, 2020. Posted in Current News

The UK response to the coronavirus is fundamentally wrong. Why fundamentally? Because from the beginning, the situation has been treated homogeneously, whereas the public health risk is entirely heterogenous.

As a result, focus has been on the wrong metric – cases. The term “cases” has changed implication, so it is important to explain how. Initially the term was used to refer to those infections that were serious enough to merit hospitalisation. However, as more testing was done, the term includes everyone who tests positive, regardless of severity.

To continue to monitor cases and make headline figures of them is misleading and is the reason why the UK and most other governments continue to fail in dealing with the situation. While the debate rages about what policies are effective about stemming the inevitable spread of the virus, the focus where it matters – on hospitalisation and ultimately death – has been lost.

Boris Johnson’s pithy mantra “Stay at home, protect the NHS, save lives”, delivered on 23rd March and the Department of Health and Social Care Media Centre’s response to a Channel 4 Dispatches documentary on 3^rd June[i], “our response has ensured that the NHS has capacity for everyone who needs it and that it can provide the best possible care for people who become ill”, highlight the important objective of the public health policy – to prevent hospitalisations and death.

Hospitalisations and death are significantly more important than the number of cases but only in the detail. The detail in the data does not support the current policy responses – indiscriminate lockdowns, social distancing, and mask wearing. And no-one in government, their advisors or select committees[ii] is asking the right questions of the data.

According to NHS statistics[iii] as of 26^th May, of all the hospital deaths related to COVID-19 in England, more than 95{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} had a pre-existing condition such as asthma, chronic kidney disease, chronic neurological disorder, chronic pulmonary disease, dementia, diabetes, rheumatological disorder or ischaemic heart disease.

Taking into consideration the age distribution of the population[iv], despite accounting for less than 5{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the population, those aged over 80 account for 53{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the deaths, of which 97{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} had pre-existing condition.

Accounting for less than 19{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the population, those aged between 60 and 79 account for more than 38{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the deaths, of which 95{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} had pre-existing condition.

Despite accounting for almost half the population, those aged under 40 account for just 0.8{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the deaths, and only 0.1{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} with no known pre-existing condition.

Representing almost a quarter of the population, under 20s with pre-existing condition account for 0.05{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the deaths and 0.01{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} without.

The pattern is clear – the risk of death is very much skewed towards the elderly and those with pre-existing conditions. Since 63{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of all deaths occurred in hospitals, analysis of the deaths data is also a useful proxy for the risk of burden on the NHS.

Another way to understand the situation is by looking at the infection fatality rate (IFR), i.e. the proportion of people who have died relative to being infected. Again, it is important to examine the heterogenous distribution of this rate to get a proper insight that should govern public policy and allow each individual to act in accordance with their own risk, as they do in every other aspect of their life.

In the ONS Coronavirus (COVID-19) Infection Survey pilot: 28 May 2020[v], 6.78{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of those individuals providing blood samples tested positive for antibodies to COVID-19. Applying this ratio to the population, it is estimated that just under 4 million people in England have contracted the virus. This produces an IFR of about 0.66{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117}. There is evidence to suggest a significant number of people have innate immunity[vi] which could possibly mean the overall IFR is half this number.

Assuming an equal distribution of infection, the IFR ranges from 6.8{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} for those aged 80 and above with pre-existing conditions to 0.0003{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} for those under 19 without. In other words, that’s roughly 1 in every 15 to 1 in every 300,000.

By now, it should be completely apparent that to deal with this coronavirus, public health policy should be almost entirely directed towards protecting the elderly and those with pre-existing conditions from infection. It is inconceivable that this can be achieved by basing policy on any hypothetical, epidemiological model that does not explicitly account for the heterogeneity of the risk and targeted strategies towards this section of the population.

Instead, the entire UK policy still appears to be reliant on the suppression of the general reproduction rate of the virus, i.e. containing the spread and minimising the cases. What sense does it make to close the high street, schools, parks and beaches, and only re-open them with a plethora of conditions when the majority of the susceptible population are in care homes and hospitals? Over 16,000 care home residents in England have succumbed to the virus between 10^th April and 29^th May[vii], representing well over 50{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of the total.

All targeted measures that would more logically and practically mitigate the risk of the virus to the health service and the population are ignored in favour of indiscriminate measures like social distancing, reduced class sizes in schools, the wearing of non-surgical masks, and other such measures, which have little scientific evidence to support them and don’t correlate with the empirical outcome data, to permit the resumption of business and activity.

This conclusion is shared by others across the world, including for example Scott W. Atlas, MD, a Senior Fellow at Stanford University’s Hoover Institution and the former chief of neuroradiology at Stanford University Medical Center[viii] who states:

“The overwhelming evidence all over the world consistently shows that a clearly defined group — older people and others with underlying conditions — is more likely to have a serious illness requiring hospitalization and more likely to die from COVID-19. Knowing that, it is a common-sense, achievable goal to target isolation policy to that group, including strictly monitoring those who interact with them.”

By and large, it is now too late to make the biggest difference in the primary and secondary care facilities where most of the contagion in the susceptible is nosocomial but at least the logically ineffective myriad of other often confusing and contradictory measures should be dispelled.

[i] https://healthmedia.blog.gov.uk/2020/06/03/response-to-channel-4-dispatches-britains-coronavirus-catastrophe-did-the-government-get-it-wrong/

[ii] https://parliamentlive.tv/Event/Index/c36d74b3-2fe2-4309-8554-f50fe966f7a3

[iii] https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-daily-deaths/

[iv]https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/articles/overviewoftheukpopulation/august2019

[v]https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/28may2020

[vi] https://www.cell.com/cell/fulltext/S0092-8674(20)30610-3

[vii]https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/numberofdeathsincarehomesnotifiedtothecarequalitycommissionengland

[viii] https://thehill.com/opinion/healthcare/494034-the-data-are-in-stop-the-panic-and-end-the-total-isolation

About the author: Joel Smalley holds an MBA from the University of Toronto and  works as a Blockchain architect and early stage, polymath data-driven technologist, specializing in fintech, healthtech and IoT. He is currently CIO and CTO of Toucan Labs. 

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