Professor Lockdown and Imperial team say Covid-19 kills 1.15% of all patients - TWICE as high as the best guess of No10's top scientists and the World Health Organization

Covid-19 kills around 1.15 per cent of all people who are infected, according to the latest projections by 'Professor Lockdown' and his team.  

Neil Ferguson's startling projection that up to 500,000 Britons could die of the life-threatening disease convinced ministers to put the UK into lockdown in March, on the basis that the virus has an infection fatality rate of around 1 per cent.

And today the Imperial College London epidemiologist, who was forced to stand down from SAGE after allowing his married lover to visit him at home between March and April, has predicted the fatality rate could be even higher. 

Professor Ferguson and colleagues at Imperial boast their calculations — which say the equivalent of one in every 100 people who get infected with the virus die from it — are some of the most accurate to date.

However, their figure is more than double the best guess of top experts at the World Health Organization, who say the IFR stands at around 0.5 per cent. Even Number 10's own scientific advisers are adamant it kills just one in 200 infected patients.

Top scientists have been baffled over the true mortality rate of the disease since the start of the pandemic in December, with estimates ranging from 0.01 per cent to 1.4 per cent.

To measure the death rate accurately, experts must know the number of infections. But early studies relied on flawed testing results, giving an inaccurate figure for how many people have had the disease, the Imperial team argue.

In the study, they admitted the death rate was much lower for younger people, saying it stands at around 0.1 per cent in the under 40s - the same as seasonal flu. And they added in low-income countries - which have younger populations - it could be as low as 0.23 per cent.

Experts have been baffled over the true mortality rate of the disease since the start of the pandemic in December, with estimates ranging from 0.01 per cent to 1.4 per cent

How Professor Neil Ferguson has advised the government on series of outbreaks including swine flu, foot and mouth and BSE 

Professor Neil Ferguson, who has advised the Government on swine flu and BSE

Professor Neil Ferguson, 51, was born in Cumbria but grew up in Mid Wales, earning a masters degree in Physics and a PhD in theoretical physics from the University of Oxford. 

He specialises in measuring the spread of infectious disease in humans and animals through mathematical modelling and has provided data on several outbreaks including the swine flu outbreak in 2009 in the UK, the 2012 Middle East respiratory syndrome coronavirus outbreak and the ebola epidemic in Western Africa in 2016.

He is currently the director of the MRC Centre for Global Infectious Disease Analysis at Imperial College, London, and, before his resignation, a member of the government's SAGE committee that advises ministers on tackling the coronavirus pandemic.  

In March, he calculated that without a draconian national lockdown, coronavirus would claim 510,000 lives.

But crucially, he also estimated that 250,000 would die if ministers stuck with the strategy of controlling the spread with limited measures – such as home isolation for those displaying symptoms of the virus.

Prof Ferguson reckoned that if the strictest possible measures were introduced the number of deaths over a two-year period would fall to below 20,000.

In hindsight that estimate was ambitious – in less than three months Britain's death toll has soared to more than 32,000. But it was enough to persuade Mr Johnson to impose the most drastic peacetime measures ever seen. 

Prof Ferguson has been a regular presence on television and on the radio throughout the crisis. But he has rejected the 'Professor Lockdown' nickname used by many.

In one interview, on the Andrew Marr show last month, he insisted it was up to ministers to make the decisions. 'We provide scientific evidence along with a lot of other scientific groups across the country which fed into government policy,' he said.

'But we did not determine that policy, there are a number of balancing acts involved in doing that.' He also points out that he leads one of at least five modelling teams who had come to similar conclusions in March.

But as a long-term member of the Government's SAGE scientific advisory committee – and with a high-profile media presence – his voice is one that will have been heard louder than most.

On March 18 he fell victim to the virus himself. Two days previously he stood next to Health Secretary Matt Hancock at a Press conference.

Mr Hancock learned he had the virus a few days later. Mr Johnson and Chris Whitty, the chief medical advisor, developed symptoms the same day. Colleagues describe the 51-year-old as an energetic workaholic who has little need for sleep. 

Prof Ferguson rose to prominence during the 2001 foot and mouth crisis. His research, carried out with mentor Professor Roy Anderson, helped persuade Tony Blair's government to carry out a devastating cull of animals, and saw him awarded an OBE.His work suggested that animals to be culled should include not only those found to be infected with the virus but also those on adjacent farms.

A decade later another highly critical report said the Government ordered the destruction of millions of animals because of 'severely flawed' modelling.

In 2002, Prof Ferguson published a report on the BSE crisis, years after the peak of the episode.He speculated that BSE in cows and sheep could cause up to 150,000 human deaths – to date fewer than 200 have died.

He has since been involved in modelling numbers during the SARS, bird flu, ebola and Zika epidemics, with varying accuracy.

He stands by his work – pointing out that each calculation has come with a 'range' of possible eventualities.

To understand how deadly Covid-19 is, scientists have to work out the 'infection fatality rate' .  

The IFR estimates how many people die from the disease overall, including patients who don't show any symptoms and may never get tested.  

To measure IFR, scientists use official data on deaths. Most countries record a Covid-19 death as anyone who died after testing positive for the disease.

But not all the countries use the same measurements. The UK used anyone dying at any time after testing positive - which meant some victims were counted even if they recovered and were hit by a bus a month later. 

But to calculate the IFR, scientists also must know exactly how many people have had the coronavirus — technically called SARS-CoV-2 — and this is not as easy to gauge. 

Millions would have had the disease and not been tested due to a lack of capacity in the early days of the crisis. So measuring IFR is a difficult task, which is why estimates are so varied.

The only way academics can currently estimate how many people have had the coronavirus is through looking at how many people have developed antibodies to the virus.

Infected patients make antibodies — proteins made by the immune system to fight off pathogens in the future — weeks after their battle with the disease.

But not everyone who has Covid-19 develops antibodies if other parts of their immune system, such as T cells, clears the virus.

And studies have shown antibodies can wane over time, meaning many patients who were infected in the spring may now not be spotted by testing. 

Just this week, a Government-funded study from Imperial found antibody levels in England declined by 26 per cent from June to September.

That's why Professor Ferguson and colleagues claim estimates of the IFR to date are not as accurate as their own, which they say accommodate for these limitations. 

After screening 175 studies, the researchers identified 10 antibody surveys they considered high quality because they had factored in the chances of antibody levels waning and inaccuracies in tests. 

The most common reasons for excluding studies were a lack of reliable information on the accuracy of antibody test used in the study.

The Imperial study found IFR consistently increases as people get older, with the risk of death doubling approximately every eight years of age.  

Because of this, the researchers claimed IFRs would be different in rich and poor countries. Low-income countries often have younger populations due to variations in life expectancies. 

The IFR in a typical low-income country was calculated as 0.23 per cent.

But in high income countries, which have a greater concentration of elderly people, the IFR was estimated as 1.15 per cent. 

This means more than one in every 100 people who get the coronavirus will die, including those who don't show symptoms at all, are critically ill, and everyone in between.

The paper concluded: 'Our estimates of the IFR of Covid-19 are consistent with early estimates and remain substantially higher than IFR estimates for seasonal influenza (less than 0.1 per cent in the US).

'To the best of our knowledge, this is the first study accounting for seroreversion as part of IFR estimation as well as simultaneously accounting for uncertainty in serological test characteristics and delays from infection to death and seroconversion.'

Previously the World Health Organization — which published Imperial's work — said its best guess on the IFR was 0.6 per cent.

Dr Maria Van Kerkhove said in August the estimate was based on data from several studies. At the start of the pandemic, when little was known about SARS-CoV-2, the agency feared the IFR was 3.4 per cent.

Dr Kerkhove said 0.6 per cent 'may not sound like a lot but it is quite high'. It would suggest Covid-19 kills one in every 167 infected people.

It would also make the disease six times deadlier than seasonal influenza, which is estimated to kill 0.1 per cent of cases.

The Imperial team said of the studies they looked at, the IFR ranged from 0.33 per cent in Denmark to 2.3 per cent in Italy.

IFR estimates tend to be higher when researchers cannot account for everyone that has had the disease.

If they predict 100 people have had it, and 10 die, it would give an IFR of 10 per cent. But if they detect 1,000 people have it, and 10 die, it would give an IFR of 1 per cent. 

Of the studies looked at by Imperial, antibody prevalence ranged from 1.6 per cent in Zurich, Switzerland to 12 per cent in New York State. 

MORTALITY RATE ESTIMATE FOR EACH AGE

KEY: Ages and risk of death 

0-4: 0.00

5-9: 0.01 

10-14: 0.01 

15-19: 0.02 

20-24: 0.03 

25-29: 0.04 

30-34: 0.06 

35-39: 0.10

40-44: 0.16

45-49: 0.24

50-54: 0.38 

55-59: 0.60

60-64: 0.94

65-69: 1.47

70-74: 2.31

75-79: 3.61

80-84: 5.66

85-89: 8.86 

90+: 17.37

 

The overall estimated IFR does match that given by Cambridge University experts, who in late August gave a guess of 1.1 per cent.

They said it could be as high as 1.4 per cent after analysing Government data in the UK, showing that around eight per cent of the population had antibodies.

Previously a review of antibody surveillance studies by Stanford University experts in June suggested the coronavirus has a mortality rate of 0.25 per cent. 

It reviewed 23 studies and showed variations in IFR across the world. Data showed Kobe — a city in Japan — had the lowest fatality rate (0.02 per cent), based on its having recorded 10 deaths among an estimated 41,000 cases.

At the other end of the scale was the 0.86 per cent estimate from Milan, where 1,459 deaths had occurred out of a projected 170,000 cases.

A more recent estimation from the review's leader, Professor John Ioannidis is 0.27. The paper, published in the Bulletin of the World Health Organization last week, reviewed 61 studies from around the world.

London School of Hygiene and Tropical Medicine took a different approach, and studied the Covid-19 outbreak on the cruise ship the Diamond Princess.

Cruise ships are deemed an ideal environment to study because there is complete data available for everyone on board at the time. 

The team found in March the fatality rate was 1.2 per cent — 13 deaths out of 712 cases — but the rate was adjusted to 0.5 per cent to reflect the entire population.

THe WHO believe Covid-19 kills 0.6 per cent of all patients or one in every 167. Although it sounds minimal, it means Covid-19 is six times deadlier than the flu and almost as twice as fatal as polio

Another German study in May which honed in on the small town of Gangelt put the rate at around 0.37 per cent.

Gideon Meyerowitz-Katz, of the University of Wollongong in Australia, estimated the IFR was 0.75 per cent. But it could be as low as 0.49 and as high as 1.01.

He and his colleague Dr Lea Merone, of James Cook University, searched online for IFR studies from around the world. 

By comparison, the seasonal flu kills around 0.1 per cent of those it infects. Ebola kills around 50 per cent of all cases. 

Mr Meyerowitz-Katz pointed to data from a separate study in Qatar that suggested it may be as low as 0.01 per cent — the equivalent of one death for every 10,000 cases. He said it was 'by a very long way the lowest I've seen'.

The model was based on data about how the virus naturally spreads in a population and the results on results of mass swab and antibody tests. 

Experts led by Dr Laith Abu Raddad found that the IFR was 0.01 per cent, which was 'remarkable', the researchers said.  

But the estimate — that Covid-19 only kills 0.01 per cent of people it infects — cannot physically be true for the UK. It would mean the UK would only have suffered 6,600 deaths, for its population of 66million. The truth death toll stands between 45,000 and 60,000.

The IFR is different to the case-fatality ratio , another measures of how many people die of a disease which is based only on confirmed cases.  

CFR is simply the number of deaths divided by diagnosed cases — which only represent a proportion of true infections.

The CFR ratio in Britain is around six per cent, given that 58,925 of the 965,340 people diagnosed have died. 

How Imperial College report written by Prof Ferguson warned of 500,000 deaths and persuaded the PM to implement lockdown 

A scientific paper published by Professor Neil Ferguson and his colleagues on the Imperial College COVID-19 Response Team was credited for persuading Boris Johnson's Government to ramp up their response to the coronavirus.

The paper predicted that the Government's original plan to 'mitigate' the outbreak instead of trying to stop it could have led to a quarter of a million people dying.

Using data from Italy and China, the scientists predicted how different Government measures would have different impacts on the outbreaks.

If no action at all had been taken against the coronavirus it would have claimed 510,000 lives, the team's report said.

Had the Government stuck with their strategy of trying to 'mitigate' the spread – allowing it to continue but attempting to slow it down – with limited measures such as home isolation for those with symptoms this number would be roughly halved to 260,000.

If the strictest possible measures are introduced – including school closures and mandatory home quarantine – the number of deaths over a two-year period would fall below 20,000, the scientists said, despite Britain's death toll far-surpassing that number.

'Instead of talking about hundreds of thousands of deaths, there still will be a significant health impact that we'll be talking about,' Professor Ferguson said.

As a result, the Government implemented the lockdown, announcing that people should stop travelling, stop socialising and work from home. They were also told to avoid visiting their sick or elderly relatives unless they have to.

Other points in the Imperial College report, titled Impact of non-pharmaceutical interventions to reduce COVID19 mortality and healthcare demand, included:

WHAT ARE THE DIFFERENT MORTALITY RATE ESTIMATES FOR COVID-19? 

7.4%

Researchers led by Gabriele Pagani, of the Università degli Studi di Milano screened the entire population of Castiglione d’Adda, a town in the Lombardy region that has been heavily hit by Covid-19.

Almost a quarter of the population had antibodies (22.6 per cent) - 1,028 of the 4,550 inhabitants. But the official number of cases reported in the town, as of June 21, is five times lower, at 184.

The town had also recorded 76 Covid-19 deaths by June 21, which out of the 1,028 cases estimated, equates to a death rate of 7.39 per cent.

1.4%

Cambridge University analyse real-time COVID-19 data in the UK to paint a picture of the epidemic now, and work up a forecast of infections and deaths. 

The statistical modellers, led by Dr Paul Birrell, are working with Public Health England and their information feeds directly to government teams.

Their modelling suggests the overall infection mortality rate is 1.4 per cent - but it could be as low as 0.98 and as high as 1.8 per cent. It ranges from 0.0046 in those aged between 15 and 24 years old, and 18 per cent in those over 75.

1% 

Most coronavirus modelling, including the grim Imperial College London projection that warned 500,000 Brits could die without action and convinced ministers to impose a lockdown, are based on a death rate of around 1 per cent. 

0.75% 

Epidemiologist Gideon Meyerowitz-Katz, from the University of Wollongong, and James Cook University's Dr Lea Merone, collected information from 13 global studies that tried to calculate the true death rate of the coronavirus and settled on an overall estimate of 0.75 per cent.

They said it was 'likely' that it was somewhere between 0.49 and 1.01 per cent and that it would be higher among elderly people or the chronically ill, and lower for younger people. 

The number chimed with data emerging from New York, where random antibody testing in April suggested a quarter of the city of eight million people had been infected with the illness, meaning the 16,000 fatalities equaled a death rate of 0.79 per cent.

0.6%

World Health Organization officials believe the infection fatality rate of Covid-19 is 0.6 per cent based on various studies, or one in 200 patients.

At a virtual news briefing from the WHO's headquarters in Geneva on August 3, Maria Van Kerkhove, WHO's technical lead for coronavirus response said the figure 'may not sound like a lot, but it is quite high'. 

0.5%

A study from London School of Hygiene and Tropical Medicine found that the death rate on the Diamond Princess ship was 0.5 per cent. The cruise ship is ideal for studying because there is complete data available for everyone on board at the time there was an outbreak.

The team found the fatality rate was 1.2 per cent - 13 deaths out of 712 cases - but the rate was adjusted to 0.5 per cent to reflect the general population.

0.37%

In April, researchers did swab and antibody testing of a randomly selected 919 people from 405 households in Gangelt - a small town in Germany where the country's outbreak began.

Results showed around 15 per cent of the population of Gangelt had been infected with the coronavirus.

The town had recorded seven deaths out of 1,800 confirmed cases, which equates to a death rate of around 0.37 per cent.    

0.25%  

A review of antibody surveillance studies suggests the coronavirus has a mortality rate of 0.25 per cent, meaning it kills one in every 400 people who get it.

The new estimate was based on figures from 23 different testing surveys carried out worldwide, which suggested the actual mortality rate ranged from as low as 0.02 to as high as 0.78 per cent.

They measured antibodies in the blood, a sign of past infection, which may be more reliable than estimating how many people have been infected.

0.01 per cent

Qatari researchers led by Dr Laith J. Abu Raddad from Cornell University, Doha, used a mathematical model to get an idea of how many people in Qatar had been infected over the pandemic. 

The model was based on data about how the SARS-Cov-2 naturally spreads in a population and the results of a series of studies in Qatar that used swab and antibody tests until around the date July 10.

The model showed that the IFR was 0.01 per cent, which was 'remarkable', the researchers said.