The prime minister, with his chief science and medical advisers behind him. (Photo by Frank Augstein-WPA Pool/Getty Images)

March 17, 2020   12 mins

Last Thursday, the UK government announced a shift in its coronavirus strategy, moving from a “contain phase” to a “delay phase.” The new guidance included encouragement for people to self-quarantine at home if they develop relevant symptoms, and that schools would be asked to end foreign trips. To say that these fell short of the countermeasures implemented in other countries would be an understatement. 

The government also indicated that the amount of testing would be restricted to serious cases and that many showing mild symptoms would no longer be tested. Most notably, the government’s strategy also outlined countermeasures that they had not recommended (school closures or restrictions of mass gatherings), with the idea that the population would become fatigued by social distancing measures. (Yesterday, however, they announced a scaling up of testing.)

The Chief Scientific Adviser, Sir Patrick Vallance, Chief Medical Officer, Professor Chris Whitty, and the government’s science adviser Dr David Halpern indicated that the government’s strategy was to allow the virus to pass through the population, to allow individuals to “acquire herd immunity” at a delayed speed, while vulnerable groups were “cocooned.” This strategy, however, was subsequently contradicted by health secretary Matt Hancock, who insisted that “herd immunity is not our goal or policy”.

The quick reversals did not end there, as a ban was announced on mass gatherings just a day after the government’s initial claims that it was not the right time for such measures. On Saturday, the government briefed select journalists on “wartime measures” to quarantine the elderly at home or in care homes, away from any contact with the rest of the population; earlier than such measures were expected to be announced.

Finally, it was revealed yesterday afternoon that the Prime Minister had decided to dramatically step up countermeasures, and switch entirely to a strategy of containment as a result of advice from an expert response team at Imperial College London, which concluded that the strategy of delay would likely cause “hundreds of thousands” of avoidable deaths.

The initial plans — to establish herd immunity based on research on social fatigue and assumptions that effective vaccines would not be developed — contradicted the guidance from the World Health Organisation (WHO), and the wealth of evidence in the fields of epidemiology, behavioural science and immunology, so it is unsurprising that countless experts have already questioned and criticised the strategy, including epidemiologists, immunologists, and behavioural scientists.

Given reports that President Macron of France and the Netherland’s PM are considering the same strategy, and secret briefings suggesting that the crisis would have lasted until spring next year given the current plan, it remains necessary to explain in detail why the strategy of “herd immunity” proposed by the UK could be dangerously fatalistic and contradicted by the majority of expert opinion and scientific evidence on COVID-19; and why its enormous damage was predictable from the beginning.

A central concept to understand in epidemiology is the basic reproduction number (R0), which is the number of people that are expected to be infected by an individual case, in a population that is susceptible to infection.

This means that if a virus has an R0 of 2, for example, an individual case is expected to infect 2 other people, who are expected to infect a further 2 people each, and so on. In general, a virus with a larger R0 spreads more rapidly in a population. As a consequence, the R0 determines whether a pathogen will remain endemic in a population (if it is >1) or die out (if it is <1). During early stages of the pandemic in Wuhan in January, research from different labs estimated an R0 of 2.54 on average (with a 95% confidence interval between 2.17-2.91).

Crucially, the R0 is not an inherent or fixed property of a pathogen: the expected number of people who will be infected by a case depends on the behaviour of individuals in a population and their environmental context, such as the length of time that cases are infectious, the number of susceptible people they are in contact with, and their general infectiousness.

This is the reason that reducing the number of contacts that individuals have (such as by social distancing) works, as does handwashing and effective treatment — these strategies reduce the R0 of a pathogen.

Countermeasures in Wuhan and elsewhere have already reduced the local R0 of COVID-19, with research suggesting the R0 was reduced all the way down to 0.32 in Wuhan in early February after extensive testing and containment measures. In Italy, which implemented aggressive countermeasures fairly late into their local epidemic, preliminary analysis suggests the R0 was reduced from 3 in late February to 1.7 in early March and the number of new cases has dramatically slowed down. 

According to an analysis published in the Lancet, approximately 95% of the Wuhan population remained uninfected by the virus at the end of January, after the peak of their crisis, as a result of aggressive countermeasures. These data on their own indicate that herd immunity is not an inevitable outcome, nor is the possibility that up to 80% of the UK population will be infected within the next year, as was claimed by Professor Chris Whitty.

A common rebuttal to social distancing strategies is that the policies to implement them may backfire. For example, on Thursday’s BBC Newsnight, one of the Government’s advisors claimed that shutting down schools or cancelling football matches would simply lead people to gather in other ways — such as by children infecting their parents and grandparents as they return home, or by spectators gathering to watch matches at the pub, respectively.

It is difficult to imagine a scenario in which a child would sustain more contacts while returning to and staying with their family, than if they encountered additional hundreds of children at school every day, or to imagine a scenario whereby spectators would gather in pubs and homes at an equivalent level and density as if a football match was cancelled.

Fortunately, there is substantial literature on this topic from across the world, which the government should have looked towards. It includes historical successes in pandemic control and current countermeasures across the world, such as by South Korea, Hong Kong, and Singapore. Given the way case statistics in the UK are progressing, it will increasingly include recent measures taken in Italy.

Nicholas Christakis, a professor at Yale University who specialises in research on social networks and contagion, calls school closures “one of the most beneficial ‘non-pharmaceutical interventions’ that can be employed, more effective even than reactive quarantines or banning of public gatherings,” in part because “parents also stay home as a result”. He cites evidence from six studies based on data from Japan, Italy, China, the UK and the US which converge on the conclusion that school closures, especially early ones, reduce the total number of cases and delay the peak of epidemics.

Confusingly, the Government also appeared to admit that social distancing policies would be effective, according to their own models, despite not recommending them. They stated that school closures for at least 13 weeks would reduce the peak of COVID-19 by 10-15%, that self-isolation would reduce it by up to 20%, and that restricting mass gatherings would reduce it by 5%.

To be clear, in any field of research, these would be considered massive effects individually, and if they are insufficient on their own, it was unclear why the government had not considered implementing them all together — as many other European countries had already done – aside from increasing the strain on healthcare workers with children.

In addition, the government initially claimed that the population would encounter “fatigue” if countermeasures are implemented early, and would get tired of self-quarantining, and that “nudges” to encourage people to wash their hands more frequently were sufficient. At the time this piece was published, over 500 behavioural scientists had signed an open letter urging the government to publish their evidence for this claim, stating that they are “not convinced that enough is known about ‘behavioural fatigue’ or to what extent these insights apply to the current exceptional circumstances.”

The evidence that emerged was surprising. On Friday, one of the government’s advisors explained that the idea of social fatigue, which was used as a rationale to delay quarantine, was based on a literature review of the psychological impacts of quarantine.

But crucially, the literature review made no mention or recommendations of how early quarantines should be implemented. It also stated explicitly that only a few of the papers it included directly compared quarantined versus unquarantined patients, which makes it difficult to establish whether quarantine would cause more panic and social fatigue in an epidemic than the absence of quarantine.

The other paper cited as “influential” in the government’s strategy was in fact a working paper that was published a single day before the government’s delays to quarantines were announced. As with the previous paper, it made no recommendations as to when quarantines should be implemented. 

There may be real and substantial psychological, medical and economic side effects of quarantine measures, and of a pandemic more generally, regardless of whether individuals are quarantined or not. But given the exponential nature of the disease’s spread, these effects should be mitigated alongside countermeasures, not traded off for them. If the government believed that individuals would feel fatigued by taking self-isolation procedures and social distancing measures, they should have provided top-down assistance and coordination to alleviate this.

And if these papers represent the basis for the government’s strategy to delay quarantine, they should be seriously questioned. Substantial social distancing measures are recommended by WHO and the CDC to be implemented as soon as possible if there is evidence for local community transmission of COVID-19.

The government’s unsubstantiated claims did not end there, however, as the question remains of whether acquired “herd immunity” from infection was feasible or even desirable. Some further background may help to judge the justification for those claims. 

Vaccination (the prototypical source of herd immunity) reduces the number of people who are susceptible to a pathogen, which reduces its effective reproduction number. The R0 value can also be used to estimate the proportion of the population that would have to be immunised to prevent further spread of the virus. In general, this proportion is estimated using the formula: 1 – 1/R0. Immunised in this sense refers to being unsusceptible to infection, which can result from acquired immunity (which may develop from a previous infection by a pathogen) or by active immunity (which may develop from a vaccine).

Using this as a guide, the government suggested that its strategy was to allow the virus to spread until “herd immunity” was achieved by the population getting infected, rather than by vaccination. David Halpern, an adviser to the government, indicated that vulnerable groups will be “cocooned” until the population has “acquired immunity” to the virus (comments that were reflected by the Chief Scientific Officer) and the spread of the virus would supposedly be slowed down to reduce the strain on hospitals, as part of a long-term strategy that predicts the epidemic will substantially return several months from now, during the winter. 

What does this entail, practically? Using an R0 estimate of 2.5 and the formula mentioned above, the government has said that this means at least 60% of the population would have to be infected and acquire immunity to the virus. That was an estimated 40 million individuals that government advisors claimed would “inevitably” be required to succumb to the virus, in order to protect the remaining vulnerable groups.

This was perhaps the most egregious claim made by the Government, and it is important to understand the many reasons why. 

One reason is our understanding of the grave severity of the disease: statistics from WHO indicate that the global case fatality rate (CFR) is approximately 3.8%, meaning that 3.8% of globally confirmed cases eventually died from the disease. This rate varies by age group: 0.2% between the ages of 20-39, 0.4% between the ages of 40-49, and 1.3% between the ages of 50-59. The rate increases rapidly with age, reaching 14.8% above the age of 80.

The fatality rates for young to middle-aged cases may sound low at first, but they are over a hundred times greater than those of influenza, and the CFR alone may obscure the seriousness of the illness in the patients who survive. Patient data from China indicates that apart from the 2.3% of cases in China who died, 5% of cases were critical (meaning that they suffered from “respiratory failure, septic shock, and/or multiple organ dysfunction or failure”), 14% of cases were severe (meaning that they suffered from “shortness of breath, respiratory frequency ≥ 30/minute, blood oxygen saturation ≤93%, PaO2/FiO2 ratio <300,30 and/or lung infiltrates >50% within 24–48 hours.”) and 81% of cases were mild. 

What does “mild” mean here, exactly? As a WHO expert explained, it includes anything short of requiring supplemental oxygen: ranging from asymptomatic cases to fever and coughing to mild pneumonia – that is, the definition of a “mild” case of COVID-19 is not equivalent to that of a mild cold. And if you thought that was all, it isn’t: case report data shows that some patients who fully recover from the disease still exhibit weakened lung capacity and organ damage.

Part of the Government’s strategy was to “flatten the curve” of new cases to reduce the strain on the NHS, and relied on an assumption that just 5% of symptomatic cases will require hospitalisation. Given the numbers above and the initial lack of aggressive social distancing measures to achieve such a “flattening,” it was unclear how that figure could be possible. Instead of increasing the amount of testing, the government said that they would restrict testing to serious cases and would turn away mild cases from hospitals for self-quarantining even if they have tested positive for the virus. 

Perhaps most surprisingly, until yesterday the policy was that confirmed cases were required to self-quarantine at home, but household members of these confirmed cases (such as their spouses and flatmates) were still not required to quarantine themselves in hospitals or even at home, despite being at risk of acquiring the virus from their cohabitants and subsequently spreading it to others in society. In addition, government advice was to self-quarantine for 7 days if relevant symptoms arise, even though research shows that individuals are infectious for between 2-14 days and recommends 14 days as the length of quarantine. That, as well, was changed yesterday.

Four epidemiologists from Harvard and Boston University’s schools of public health modelled the number of ICU beds that would be required by the population during the peak of the crisis, assuming the government’s strategy is achieved.

Even while these researchers use highly generous assumptions to the government’s plan (e.g. if full cocooning is achieved), at the peak of the crisis, twice as many ICU beds would be required than are available in the NHS, even if the proportion of detected cases was only 8%, and even if we only considered 20-40 year olds. In total, the degree of failure is expected to be far greater than this, considering individuals of all ages.

The epidemiologists title their paper: “The direction of the UK Government strategy on the COVID-19 pandemic must change immediately to prevent catastrophe.” In an article published in the Observer on Sunday, one of the authors of the same paper, Harvard epidemiologist William Hanage, states plainly that he “assumed that reports of the UK policy were satire” and explains his alarm to the government’s strategy in much greater detail. Note that the report from the response team at Imperial predicted much of the same.

Meanwhile, reports had arisen on the weekend that hospitals were already being overwhelmed by the crisis, that the virus was spreading far quicker than the government’s models predicted, and that Boris Johnson was already considering an acceleration in aggressive measures.

The media coverage regarding “flattening the curve” (delaying its peak) may be misleading. Hospitals would quickly be overwhelmed by severe cases, which would spiral exponentially out of control, to say nothing of the damage that would have been unleashed when patients with unrelated chronic diseases who require ICU beds and hospital care were displaced by the coronavirus crisis.

As Timothy Gowers, a Royal Society Research Professor, explains: “flattening the peak to the point where the health service can cope is approximately as hard as trying to stop the spread altogether.” The evidence and guidance from WHO is clear – soft measures to flatten the curve and delay its peak are not a viable long-term strategy, containment must be the goal: “Not testing alone. Not contact tracing alone. Not quarantine alone. Not social distancing alone. Do it all.”

One question you may be wondering about at this point is how the Government’s models diverged from the estimates made by epidemiologists and reality so quickly.  

Part of the reason may be that these (as-of-yet unpublished) models were rumoured to be built on assumptions from influenza pandemics: that a second peak would arise due to its seasonal nature and that the population would experience social fatigue from the countermeasures. This, as well, was indicated by reports yesterday.

There are many differences between influenza viruses and coronaviruses that are relevant here. One is that the case fatality rate of COVID-19 is over a hundred and fifty times higher than influenza fatalities in a typical year, as mentioned previously. Another is that the influenza virus mutates rapidly, which is why WHO recommends three vaccine formulations that are produced every year, each containing vaccines for 3-4 strains. In comparison, COVID-19 and coronaviruses in general mutate relatively slowly, explains Trevor Bedford, scientist-developer of the platform Nextstrain, which has tracked mutations in the virus since the first genomes were published. 

Another difference is that the influenza virus exhibits clear evidence of seasonality, while evidence shows only a weak relationship for coronaviruses. An analysis by Harvard epidemiologists uses data from provinces across China and finds “a slight negative relationship” between temperature and the R0 of COVID-19. It concludes that “weather alone (i.e., increase of temperature and humidity as spring and summer months arrive in the North Hemisphere) will not necessarily lead to declines in case counts without the implementation of extensive public health interventions.”

Finally, there is a lack of evidence that lasting herd immunity to COVID-19 was possible in humans when acquired by infection, and that recovered cases would be prevented from reinfection. “Typically coronaviruses don’t make long-lasting antibody responses,” tweeted Brian Ferguson, an immunologist at Cambridge University, adding, “if this is a deliberate approach it’s not scientifically based and irresponsible.”

Research based on the previous SARS virus supports this conclusion: the quantity of SARS-specific antibodies declines substantially after around 6 months of infection, until it is undetectable 2-3 years after disease onset. Several additional things must be considered: we don’t know how similar the antibody responses to this virus will be compared to the SARS virus; there is scant research on whether these antibody responses will prevent re-infection in practice; we simply don’t know how the immune system would respond to a reinfection.

The initial report used by the Imperial team assumed lifetime immunity to re-infection, and deviations from the assumption would mean that an even greater proportion of the population would need to be infected than their strategy assumed (which was already 60%).

The Government’s chief medical advisor claimed that part of the reason he believed cases in China had declined was because 20% of the Wuhan population had been infected by the virus and had acquired herd immunity and because a large proportion of cases were asymptomatic. 

But as mentioned previously, evidence from researchers at the London School of Hygiene & Tropical Medicine estimated that 94.8% of the Wuhan population were still susceptible to infection at the end of January (i.e. had not been infected by the virus) and that “there was evidence that the majority of cases were symptomatic.” Daniel Falush, a statistical geneticist at the University of Bath, tweeted that these claims were contradictory, adding that “unfortunately, tragically, this error is driving UK policy right now.”

Much of the damage could have been avoided if aggressive countermeasures had been taken earlier: the longer the inaction, the greater the spread of the virus and the greater the response required. Given the evidence outlined above, it is perplexing why the government preferred softer and delayed measures, which would have continued to exponentially increase the number of cases, compared to aggressive and immediate ones that would force the new number of cases down.

Aggressive measures would buy time to acquire and scale up diagnostic tests from other countries that could be rolled out more widely, time to continue identifying existing antivirals that may be effective against the virus,” against the virus, and time to test vaccines.

The evidence was not conflicted, it was clear: the Government’s strategy of delaying the peak and inducing herd immunity was unscientific, unfeasible and dangerous. It is hugely unfortunate that the Government delayed aggressive social distancing measures, which will have already caused avoidable deaths and suffering, but it is encouraging that they quickly reconsidered many of their initial plans — for the damage must be mitigated swiftly. Countries around the world  considering the British strategy should seriously reconsider. Containment is possible. Containment is necessary. Containment must be the goal.

Saloni Dattani is a PhD student in psychiatric genetics at King’s College London.