Nafeez Ahmed reports on the story behind a new study suggesting that nearly half of the UK population may already have been infected with the Coronavirus and claims that this could provide ‘herd immunity’.
On 24 March, the Financial Times claimed that as much as half of the British population may have already been infected by the novel Coronavirus, according to a new model by Oxford University’s Evolutionary Ecology of Infectious Disease group.
The conclusion, according to the FT’s science editor Clive Cookson, suggested that the country “had already acquired substantial herd immunity through the unrecognised spread of COVID-19 over more than two months”. If true, this would vindicate the Government’s “unofficial herd immunity strategy – allowing controlled spread of infection,” he stated.
Although numerous epidemiologists and scientists had questioned the validity of the Oxford model – which had not been peer-reviewed – it was promoted to the press by a PR agency with ties to the Government, raising questions about how and why this model was published and disseminated at this time.
The draft paper, which was originally posted to Dropbox, included a disclaimer noting that its content was “not final” and could be “updated any time”. The disclaimer also contained a contact point for journalists: “Contact for press enquiries: Cairbre Sugrue, email@example.com.”
Dr Lewis Mackenzie, a Biotechnology and Biological Sciences Research Council Discovery Fellow, commented: “Why on earth has this been sent to the media via a third party PR company instead of the Oxford University press team? Seems very irresponsible to encourage reporting on this topic before the scientific community had a chance to comment and peer-review it.”
When asked why its own press team did not release the study, Oxford University said: “All Oxford academics have freedom of expression regarding their areas of specialism, including communication through the media. It is therefore not uncommon for academics to make their own arrangements for contacting the press. The university cannot comment on individual arrangements that it is not party to.”
Caibre Sugrue is the founding director of Sugrue Communications, a technology PR agency. He is also a non-executive advisory board member of 100%Open, an innovation consultancy – which has worked for several British Government agencies, including the UK Ministry of Defence’s Defence, Science and Technology Laboratory (DSTL) and a leading charity which co-owns the Cabinet Office’s Behavioural Insights Team (BIT) or ‘nudge unit’.
A leading Silicon Valley communications consultant, Sugrue cut his teeth working with firms such as Intel, Hewlett Packard, Oracle and Xerox. His firm, Sugrue Communications, led directly on the public relations delivery for 100%Open’s MoD DSTL contract. In September 2017, a press release was sent out by Sugrue Communications, and signed off by Caibre Sugrue, in relation to a DSTL Defence and Security Accelerator “to identify innovative approaches to the delivery mission-critical supplies to the British Army over short distances”.
The press release announced that the DSTL had selected a “bio-inspired engineering company”, Animal Dynamics, an Oxford University spin-out working on autonomous drone delivery. The company is co-founded by Adrian Thomas, a Professor of Biomechanics in Oxford University’s zoology department, which also hosts the infectious disease group behind the new COVID-19 model published in March 2020.
The DSTL is an executive agency of the MoD. Its remit is to “apply cutting-edge science and technology (S&T) to keep UK Armed Forces, and the British people, protected from harm”.
100%Open played a central role in establishing the Defence and Security Accelerator by running the ‘Opening the Door’ project to “start preparing the MOD for open innovation”. 100%Open partnered with a London data-analytics firm, Aleph Insights, to diagnose MOD barriers to innovation. Aleph Insights was founded by Nick Hare, a former Government intelligence analyst. On his researchgate profile, he describes himself as “a superforecaster with the Good Judgment Project”. The latter was set-up by Phillip E. Tetlock, co-author of the book Superforecasting – which Boris Johnson’s chief advisor Dominic Cummings recommended to journalists after the resignation of Andrew Sabisky from his No. 10 role.
100%Open is also currently partnered with the innovation charity Nesta in developing a Global Innovation Policy Accelerator “to aid senior Government officials to explore how to create policies that accelerate innovation in their countries”.
Alongside the UK Cabinet Office, Nesta co-owns the Government’s Behavioural Insights Team, which has played a key role in providing behavioural science advice to the Government in relation to its COVID-19 response.
‘Nudge unit’ chief Dr David Halpern first spoke about “herd immunity” as a potential outcome of the UK Government’s Coronavirus strategy on 11 March in an interview with the BBC. A document published by the Government’s Scientific Advisory Group on Emergencies (SAGE) confirms that, a week earlier, some behavioural scientists had advised the Government to explain “that members of the community are building some immunity” as way of making the lack of “wider social isolation” policies “acceptable” to the public.
Caibre Sugrue did not respond to a request for comment.
Back to ‘Herd Immunity’
Many epidemiologists, experts and scientists have questioned the validity of the Oxford model. “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,” wrote the Oxford scientists.
However, Tim Colbourn, Associate Professor of Global Health Epidemiology and Evaluation and head of the UCL Institute for Global Health in London, told me that he believes the model’s entire foundational assumption to be demonstrably wrong.
While the paper assumed – optimistically – that only one in 1,000 COVID-19 infections would result in hospitalisation, he pointed out that this was contradicted by data in Italy which the Oxford authors appeared to have “not even checked”. He also expressed “concern” that the paper had been released to the media prior to scientific review.
In a letter published in the Financial Times, Colbourn and several other scientists described the gap between the Oxford study and real-world empirical data in detail: “More than one in 1,000 people have already been hospitalised in the Lombardy region of Italy, despite stringent control measures being implemented (population of Lombardy: 10,060,574; hospitalised: 10,905; hospitalisation rate per 1,000 population: 1.08; deaths: 4,178; deaths per 1,000 population: 0.42; data updated to 5pm March 24),” they stated. “Our Italian colleagues professors Walter Ricciardi and Anna Odone have data indicating much higher rates in some towns in Lombardy.”
Signatories to the letter included Anna Odone, Associate Professor of Public Health, University Vita-Salute San Raffaele, Milan; Walter Ricciardi, Professor of Hygiene and Public Health, Università Cattolica del Sacro Cuore, Roma; Elio Riboli, Professor in Cancer Epidemiology and Prevention, School of Public Health, Imperial College London; Nisreen Alwan, Associate Professor in Public Health, University of Southampton; and Martin McKee Professor of European Public Health, London School of Hygiene & Tropical Medicine.
The original FT piece had claimed that, if substantial herd immunity had been achieved, restrictions could be removed sooner than expected. The article added: “Although some experts have shed doubt on the strength and length of the human immune response to the virus, Prof Gupta said the emerging evidence made her confident that humanity would build up herd immunity against COVID-19.”
I contacted Professor Suntra Gupta, one of the co-authors of the study, to find out what this emerging evidence is. She did not respond to a request for comment. However, the model was reported worldwide and some commentators in both the US and UK used it to suggest that strong social distancing measures may be unnecessary.
Saving Lives the Immediate Focus
By 7pm on 24 March, the Oxford team issued a Twitter statement denying that the model should be used to draw firm conclusions: “Our results are not forecasts. These exercises are to generate much needed discussion around quantifying immunity ASAP. As stated in the text, we do not know the current state of the epidemic because we do not know the parameter p – tho we argue for it to be small.”
Dr Martin Goodson, Chair of the Data Science Section of the Royal Statistical Society, told the FT‘s science editor and author of the original piece that his “headline is extremely misleading… The study just reports the outcome of a model given certain assumptions. *Literally* no evidence is provided for these assumptions (namely parameter ρ)”.
Clive Cookson did not respond to Dr Goodson. His original article is still available to read on the FT.
Scientists are divided on the prospects for achieving herd immunity, but most agree that, while achieving it may be possible at some point, it is not clear how long it would last. In any case, whether or not it is achievable, the immediate focus should be on minimising fatalities.
William Hanage, Associate Professor of Epidemiology at the Harvard T. H. Chan School of Public Health, told me that, while eventual achieving herd immunity is “plausible”, “it is how you get there that matters.” A path with no restrictions is bound to ultimately maximise deaths.
Hanage specified that, although it “looks like immunity is achieved, it is not clear how long it lasts”. He also criticised the Oxford model for making “a lot of assumptions about severity, for which the true numbers are just not known”.
“The most important thing about any model is that it should be able to capture the surge of severe cases that we have seen in Italy, Spain and other places around the world, and you will see shortly in the UK,” Hanage added. Few models have achieved this. “We shouldn’t waste time on the exact case fatality rate when hospitals are going to be overwhelmed in weeks. Again too many are stroking their chins about the true fatality rate rather than thinking about how many people are going to die from other things once the ICUs [intensive care units] are overflowing.”
More and earlier social distancing, he argues, will help. He points to Japan as an important case to learn from because its “curve is radically different and they’ve had cases since early on”.
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