Do Nothing vs High Risk

I wanted to hold of posting for a number of reasons but feel compelled too now….i may regret it but its been stirring now for too long….i’d like to first state i have no training or experience in pandemics, epidemiology, statistics or any clinical/medical/scientific background.

 

The reasons for writing this is that I’m a bit of a nerd with an interest in looking at and understanding data. For some reason its usual inane state excites me in what you can achieve with it either creatively, or more importantly scientifically. I have for a few years studied many types of data/APIs and explored what can be done with the data creatively via my website ginandtronic.com I’m also interested in the perception of risk having been involved in the events and construction industries for many years.

 

One thing i have learnt is that data can often be useless without comparative data to scale it against. Otherwise it becomes speculative forecasting. Whilst exploring the internet during the COVID-19 crisis i came across lots of amazing data visualisations many of them using the same publicly available coronavirus data set from The John Hopkins University https://github.com/CSSEGISandData/COVID-19. I then began to explore this data and document examples of displaying it on code19.co.uk with a view of creating a reference for the future.

 

What i started to see when studying the data was there was something unusual in the media representation, and talking to many friends of the numbers vs official statements vs worst and best case scenarios..etc etc etc….it was a minefield to dissect and big scary numbers are what the media loves. The aim of this post is to maybe create some room for different interpretations of the data. I’m not a conspiracy theorist, i trust the government, i love science and applaud the NHS, this is not a whacky ‘cover up’ theory its merely a nerd looking at data and questioning our reaction to it.

 

As we enter our 2nd week of ‘Lockdown’ The advisers to the government seem calm and collected, with a solid consensus among them. In the face of a new viral threat, with numbers of cases surging daily, I’m not sure that any prime minister would have acted very differently.

 

I believe we now all live in a very different world to 20 years ago when it comes to risk and response…the terms ‘Do Nothing vs High Risk” “Flatten the curve” “The Hammer Effect” have been heard many times during the crisis and they are terms that perfectly suit our ever growing risk-aware world and the way we go about our lives. The “Flatten the Curve” graph below has been instrumental in changing the coronavirus policy in the UK and US.  The idea is simple: Taking steps like washing your hands or staying home if you’re sick can slow down new cases of illness, so that the finite resources of our healthcare system can handle a more steady flow of sick patients rather than a sudden deluge.

 

 

The difficulty with these charts is showing uncertainty. Even though it’s a chart of a concept and not a model from real data, it’s easy for people to interpret it as a precise prediction, as it looks like a chart and we’re used to charts being precise. The UK’s lockdown has been informed by modelling of what ‘Might’ happen. This is again a very real reflection of the risk averse society we are part of now – Insurance Brokers tend to like it, Creatives don’t.

 

Researchers at University College London have produced estimates for the likely number of UK deaths which vary from between 13,791 and 1,110,332 depending on whether mitigation is successful and if the relative risk turns out to be lower than expected, compared to a “do nothing/high-risk” scenario.

 

If successful, then in hindsight it may look like Covid-19 wasn’t such a big deal after all, and we did all that for nothing. Don’t be fooled…If we take drastic measures to reduce the incidence of Covid-19, it follows that the deaths will also go down, we risk being convinced that we have averted something that was never really going to be as severe as we feared. Its a win/win situation that suits our ever growing risk aware world and politicians perfectly….

 

Dr John Lee a a recently retired professor of pathology and a former NHS consultant pathologist. Says “It certainly seems reasonable, now, that a degree of social distancing should be maintained for a while, especially for the elderly and the immune-suppressed. But when drastic measures are introduced, they should be based on clear evidence. In the case of Covid-19, the evidence is not clear. The UK’s lockdown has been informed by modelling of what might happen. More needs to be known about these models. Do they correct for age, pre-existing conditions, changing virulence, the effects of death certification and other factors?” Tweak any of these assumptions and the outcome (and predicted death toll) can change radically.

 

I discovered that the government publish the UK weekly death rates currently at the time of writing dated up until 21 March. Next weeks update with figures up to March 31st will be very interesting. Statistically, we would expect about 51,000 to die in Britain this month. The current (759 – 27 March) deaths attributed to COVID-19 represent 1.4%. You could also note that there were also 186 fewer than in that same week over the course of the last five years. Globally over the first three months of the year. The world’s current (26819 – 27 March) coronavirus deaths represent 0.18 per cent of that total. These figures might shoot up but they are, right now, lower than any other infectious diseases that we live with (such as flu). Not figures that would, in and of themselves, cause a lockdown…but here’s potentially even more serious problem: the way that deaths are recorded. Dr John Lee states “If someone dies of a respiratory infection in the UK, the specific cause of the infection is not usually recorded, unless the illness is a rare ‘notifiable disease’. So the vast majority of respiratory deaths in the UK are recorded as bronchopneumonia, pneumonia, old age or a similar designation. We don’t really test for flu, or other seasonal infections. If the patient has, say, cancer, motor neurone disease or another serious disease, this will be recorded as the cause of death, even if the final illness was a respiratory infection. This means UK certifications normally under-record deaths due to respiratory infections.”

 

“Now since the emergence of Covid-19. The list of notifiable diseases has been updated. This list — as well as containing smallpox (which has been extinct for many years) and conditions such as anthrax, brucellosis, plague and rabies (which most UK doctors will never see in their entire careers) — has now been amended to include Covid-19. But not flu. That means every positive test for Covid-19 must be notified, in a way that it just would not be for flu or most other infections. What will this do to the data…???.In the current climate, anyone with a positive test for Covid-19 will certainly be known to clinical staff looking after them: if any of these patients dies, staff will have to record the Covid-19 designation on the death certificate — contrary to usual practice for most infections of this kind. There is a big difference between Covid-19 causing death, and Covid-19 being found in someone who died of other causes. Making Covid-19 notifiable might give the appearance of it causing increasing numbers of deaths, whether this is true or not. It might appear far more of a killer than flu, simply because of the way deaths are recorded.”

 

According to Prof Walter Ricciardi, scientific adviser to Italy’s minister of health, Italy’s death rate may also appear high because of how doctors record fatalities.

“The way in which we code deaths in our country is very generous in the sense that all the people who die in hospitals with the coronavirus are deemed to be dying of the coronavirus”

“On re-evaluation by the National Institute of Health, only 12 per cent of death certificates have shown a direct causality from coronavirus, while 88 per cent of patients who have died have at least one pre-morbidity – many had two or three,” he says. This puts Italy’s current death rate at 1038 vs 9134!! And we have yet to see any statistical evidence for excess deaths, in any part of the world. “We are only 2/3 weeks behind Italy” that is a phrase that has been widely used and bolstered public opinion in the strict social distancing measures.

 

The WHO reported in 2019 that swine flu ended up with a fatality rate of 0.02%. Evaluating case fatality rate CFR during a pandemic is a hazardous exercise, and high-end estimates end be treated with caution as the H1N1 pandemic highlights that original estimates were out by a factor greater than 10.

Estimating Case fatality rates in the early stage of outbreaks is subject to considerable uncertainties, the estimates are likely to change as more data emerges.

The overall case fatality rate as of 16 July 2009  (10 weeks after the first international alert) with pandemic H1N1 influenza varied from 0.1% to 5.1% depending on the country.  The WHO reported in 2019 that swine flu ended up with a fatality rate of 0.02%. Evaluating CFR during a pandemic is a hazardous exercise, and high-end estimates end be treated with caution as the H1N1 pandemic highlights that original estimates were out by a factor greater than 10.

COVID-19 isn’t the first threatening disease that’s surged around the world — nor will it be the last. In the next few days and weeks, we must continue to look critically and dispassionately at the Covid-19 evidence as it comes in.

 

As quoted by Dr John Lee in The Spectator

 

 

 

 

 

Infographic courtesy of Visual Capitalist