Debate is raging over the Imperial College London study that predicted up to half a million COVID-19 deaths and sparked the UK lockdown, with criticisms that it was “severely flawed” and was “a cautionary tale” about the limits of mathematical modelling.
The British epidemiologist whose predictions about how coronavirus might impact the UK is pushing back against the notion he radically changed his figures, a public relations fight in which he has enlisted allies in the scientific community, reports The Washington Times.
Dr Neil Ferguson of the Imperial College London has reiterated that his figure for potentially more than 500,000 deaths from the virus in the UK is unchanged, although that figure is tied to a nightmare scenario in which no mitigation steps are taken against the virus’ spread.
Given the virus-aversion policies that have been adopted, Ferguson told Parliament the actual death figures for the UK would most likely be less than 20,000, and said that is consistent with previous studies. The report says all of the figures are derived from computer models in which Ferguson and his colleagues control the inputs, but the 500,000 figure – along with another prediction that a partial implementation of proper mitigation policies could still leave some 250,000 dead – alarmed the world when they were widely publicised.
Ferguson and his colleague say the media conflated various models, or confused speculation with conclusions, in their reporting on his work and a study at Oxford University that looked at various infection rates.
“The study did emphatically not conclude (even tentatively) that half of the UK population already had coronavirus,” Kris De Meyer, who described himself as a “neuroscientist and researcher in good practices in Science Communication” is quoted in the report as saying. “All it did was explore 4 different theoretical model scenarios, and show that all of them could be matched to real-life data in the UK and Italy.”
In another model scenario, Oxford put the infected percentage of the population at 5%.
Ferguson says that the COVID-19 epidemic in the UK appears to be starting to slow down, with the number of new hospital admissions appearing to be reducing. Yahoo News reports that Ferguson said the slowing of the spread of COVID-19, the disease caused by the virus, was the result of the social distancing measures brought in by the government. “In the UK we can see some early signs of slowing in some indicators – less so deaths because deaths are lagged by a long time from when measures come in force,” he is quoted in the report as saying.
Ferguson said the epidemic was spreading at different rates in different parts of the country. He said antibody tests, currently in final stages of validation, would be “critical” to the understanding of the epidemic, adding they would “hopefully” be available in days.
Experts have cast doubt on Ferguson’s work, says a Daily Mail report. A rival academic has claimed Ferguson has a patchy record of modelling epidemics, which could have led to hasty Ministerial decisions. Professor Michael Thrusfield of Edinburgh University said Ferguson was previously instrumental in modelling that led to the cull of more than 6m animals during the foot and mouth outbreak in 2001, which left rural Britain economically devastated.
Thrusfield, an expert in animal diseases, claimed the model made incorrect assumptions about how foot and mouth disease was transmitted and, in a 2006 review, he claimed Imperial’s foot and mouth model was “not fit for purpose”, while in 2011 he said it was “severely flawed”. Thrusfield said the episode was “a cautionary tale” about the limits of mathematical modelling and he felt a sense of “déjà vu” about the current situation.
But the report says, Ferguson defended Imperial’s foot and mouth work, saying they were doing “modelling in real time” with ‘limited data’. He added: “I think the broad conclusions reached were still valid.”
His estimate that coronavirus deaths could be “substantially less” than 20,000 was based on “the presence of the very intense social distancing and other interventions now in place”. Without such controls, his team still believed Britain could see 500,000 deaths.
Last night, NHS England medical director Professor Steven Powis warned: “If we can keep deaths below 20,000 we will have done very well… Now is not the time to be complacent.”
Modelling by researchers at Oxford University found that COVID-19 may already have infected far more people in the UK than scientists had previously estimated – perhaps as much as half the population, says a Financial Times report. If the results are confirmed, they imply that fewer than one in a thousand of those infected with COVID-19 become ill enough to need hospital treatment, said Sunetra Gupta, professor of theoretical epidemiology, who led the study. The vast majority develop very mild symptoms or none at all. “We need immediately to begin large-scale serological surveys – antibody testing – to assess what stage of the epidemic we are in now,” she said.
The modelling by Oxford’s Evolutionary Ecology of Infectious Disease group indicates that COVID-19 reached the UK by mid-January at the latest. Like many emerging infections, it spread invisibly for more than a month before the first transmissions within the UK were officially recorded at the end of February.
The report says the research presents a very different view of the epidemic to the modelling at Imperial College London, which has strongly influenced government policy. “I am surprised that there has been such unqualified acceptance of the Imperial model,” said Gupta.
The Oxford study is based on a what is known as a “susceptibility-infected-recovered model” of COVID-19, built up from case and death reports from the UK and Italy. The researchers made what they regard as the most plausible assumptions about the behaviour of the virus.
The modelling brings back into focus “herd immunity”, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected.
The government abandoned its unofficial herd immunity strategy – allowing controlled spread of infection – its scientific advisers said this would swamp the National Health Service with critically ill patients.
But the Oxford results would mean the country had already acquired substantial herd immunity through the unrecognised spread of COVID-19 over more than two months. The report says if the findings are confirmed by testing, then the current restrictions could be removed much sooner than ministers have indicated.
The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.
Jose Lourenco, Robert Paton, Mahan Ghafari, Moritz Kraemer, Craig Thompson, Peter Simmonds, Paul Klenerman, Sunetra Gupta
Commenting on this University of Oxford research, Tim Hartford, UK economist writes in a Financial Times report that according to John Ioannidis, an iconoclastic epidemiologist, we know less than we think. But, writes Hartford, we are not completely ignorant.
He writes that alongside the COVID-19 death total, there are other clues to the truth. For example, thousands of people were evacuated from Wuhan city in late January and February and most of them were tested. A few tested positive and several were indeed symptom-free, but not the large majority the Oxford version of the tip-of-the-iceberg hypothesis would imply. The entire population of the town of Vò in Italy was repeatedly tested and, while half of the positive cases were asymptomatic, that is still much less than the Oxford model might lead us to expect.
So, Hartford writes, while it is possible that most of us could have been infected without knowing – and that herd immunity is within easy reach – it is not likely. That may explain why neutral experts have responded to the Oxford study with caution, and some concern that it might provoke a reckless response from individuals or policymakers.
So, what now, he asks?
Stay indoors if you want to save many lives and prevent health systems from being overwhelmed. The bitter experience of Italy and Spain demonstrates the importance of flattening the peak of the epidemic. That remains true even if, as we might hope, the epidemic is much milder and more widespread than we now believe. It might have been tempting to wait and gather more evidence – but faced with an exponentially rising pile of corpses, “wait and see” is not an option.
Health systems should expand capacity, buying more ventilators and more protective equipment for doctors and nurses. In all but the most optimistic scenarios we will need them now, we will need them later in the year and we will need them from time to time in the future. This crisis is teaching us that we should have had more spare capacity all along, despite the cost.
Test, test, test – and not only using the current tests to detect infection, but new ones for antibodies that should show whether people have already had the virus and have developed some degree of immunity. Sunetra Gupta says such tests may start to produce results in a matter of days.
Hartford writes that the epidemiologists are doing their best, but they are not omniscient. They need facts with which to work.
“Gathering those facts systematically is one of many urgent tasks ahead of us.”Full report in The Washington Times Full Yahoo News report Full Daily Mail report Full Financial Times report (subscription needed) MedRxiV Full Financial Times report on the Business Day site