Could Half the UK Population Have Been Infected by COVID-19?

Peter Russell

March 25, 2020

Scientists were sceptical of University of Oxford modelling that suggested sizeable UK infection rates of COVID-19, but say the findings underline the need for extensive testing.

Statistics for infection rates and mortality from COVID-19 have proved hard to establish, but new modelling suggested that a significant proportion of the UK population might already have been infected with the novel coronavirus.

The draft research, which has not been peer-reviewed, estimated that up to 68% of people could have been exposed to the virus up until 19th March.

The analysis depended on how long the virus was circulating in the population before the first deaths from COVID-19 were recorded.   

'Theoretical Simulation'

The preliminary findings drew widespread comment, with many experts pointing out that there was nothing in the analysis to suggest that the UK's current strategy of trying to suppress the spread of the virus with a 'lockdown' should be challenged.

Prof James Naismith, director of the Rosalind Franklin Institute at the University of Oxford, described the findings as a "theoretical simulation". He said: "At this moment, nothing in [this] paper calls for or could be used [to] justify any change in current policy that is. Unless we all follow the current government advice on social distancing, the UK will see many thousands of deaths that could have been avoided."

However, assuming the modelling was accurate, the results could mean that the country had already acquired substantial 'herd immunity' through unrecognised spread of the illness. It could also lend some credence to controversial remarks by Sir Patrick Vallance, the UK Government's chief scientific adviser, that achieving herd immunity in the population of around 60% was a desirable and achievable goal.

The research also suggested that only a very small proportion of the population was at risk of needing hospital treatment, with the vast majority developing mild symptoms or none at all.

The findings give a different perspective to those put forward by Imperial College London, which warned of a large number of deaths unless the Government implemented much tougher measures of social distancing.

"I am surprised that there has been such unqualified acceptance of the Imperial model," Sunetra Gupta, professor of theoretical epidemiology, who led the study, told the Financial Times.

Spread of COVID-19 'Might Be Earlier Than Thought'

The latest analysis was based on available data from both the UK and Italy.

The authors wrote that "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".

They also concluded: "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."

The study called for an urgent scaling up of testing for COVID-19 to provide real-time data on infection levels. "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," the researchers said.

Further Reaction to the Study

Among the reaction to the findings, Prof James Wood, a researcher in infection dynamics and control of diseases, told the Science Media Centre: "This work is some simple modelling that tries to infer infection rates by fitting models to observed mortality."

Paul Hunter, professor in medicine at the University of East Anglia, agreed that hard data was needed to assess the proportion of the public susceptible to serious illness from the virus.

Commenting on the strength of the modelling, he said that "in my view it should not be given much credibility and should certainly not influence choice of strategies for mitigating the spread of COVID-19 or predicting the ultimate size of the epidemic in the UK should it have been left to run its course."

Prof Hunter took issue with the authors' assumption that "only a very small proportion of the population is at risk of hospitalisable illness", saying it was "far too early in the epidemic to know what this value is".

There would be "huge implications" if the modelling proved correct, according to Mark Woolhouse, professor of infectious disease epidemiology at the University of Edinburgh. He said: "It would imply that the main reason why COVID-19 epidemics peak is the build-up of herd immunity. Though that would not change current policy in the UK – which is focussed [on] reducing the short-term impact of the epidemic on the NHS, it would change enormously our long term expectations, making a second wave significantly less likely and raising the possibility that the public health threat of COVID-19 will diminish all around the world in the coming months."


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