It’s certainly true that these measures have been “tried and tested”. Universal masking was tried from January 2020 in Hong Kong, seeing almost complete compliance outside the home; the world’s highest Covid fatality rate was recorded there in March of this year. South Korea was long hailed for its “successful test-and-trace system” that “beat the pandemic”; the strategy was abandoned in February because of record Omicron infections. Of course, both masking and test-and-trace have been tried in various combinations across high-income countries, including the UK — and yet in spite of this, the Office of National Statistics estimated in April that over 70% of Britons had been infected by Covid.

None of this is surprising: there never really was a scientific case for universal masking. This was obvious based on the pre-pandemic literature, which is why the WHO (alongside the CDC and high-profile public health experts such as Anthony Fauci) initially advised against mass masking; subsequent studies have confirmed that “existing data do not support universal, often improper, face mask use in the general population as a protective measure against Covid-19”. Even the New York Times has at least partially accepted this, running a piece on 31 May entitled “Why Masks Work, but Mandates Haven’t”. As for contact tracing, the pre-2020 consensus was even more trenchant, with the WHO’s 2019 report on “Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza” claiming that “under no circumstances” should it be adopted, due to its limited effectiveness. (There is also no evidence that lockdowns had any enduring influence on the spread of Covid-19. In fact, they may have worsened it.)

At this point, it really isn’t clear what advocates of these “tried and failed” restrictions hope they will achieve, given that — even in conjunction with several doses of the Covid vaccines — they haven’t been able to prevent the vast majority of people contracting Covid. As Edinburgh University’s Professor of Epidemiology Mark Woolhouse wrote in The Year the World Went Mad, lockdowns and associated non-pharmaceutical interventions cannot eliminate a virus, or even prevent infections — they can only delay them, and even then just for a short while.

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And yet, earlier this week, junior UK health minister Lord Kamall said restrictions could return if the NHS struggles to cope in the wake of increasing Covid cases. In Italy, meanwhile, the junior health minister Andrea Costa also failed to rule out the reintroduction of Covid restrictions in the face of rising cases, just saying that they would not return “for the moment”. We are seeing a resurgence of Covid fearmongering — which has done so much to inhibit a rational debate about the best ways to deal with the pandemic. The object of fear du jour is the latest Omicron subvariant, BA.5, which appears to be more contagious than any previous variant. If that’s the case, it simply means that non-pharmaceutical interventions would prove even more futile in containing its spread, meaning that reintroducing restrictions would be utterly illogical.

There’s also no evidence to claim, as a recent Daily Beast article asserted, that this new variant “is the most dangerous yet”. The most recent study (pre-print) concludes that “[d]isease severity was similar amongst diagnosed Covid-19 cases in the BA.4/BA.5 and BA.1 periods in the context of growing immunity against SARS-CoV-2 due to prior infection and vaccination, both of which were strongly protective”, while another one (under review) found that “[n]ewly emerged Omicron lineages BA.4/BA.5 continue to show reduced clinical severity compared to previous variants, as observed for Omicron BA.1”. Dr David Dowdy, an epidemiologist at the Johns Hopkins Bloomberg School of Public Health, told Business Insider: “Just as the virus is adapting, so too are our bodies.” He continued: “It’s not like with every variant things are getting worse. If anything, our bodies are getting smarter and we’re seeing fewer and fewer serious infections.”

Still, many argue that previous infection confers practically no immunity against BA.5 — and that, therefore, we should all be ready for another round of vaccination. In fact, the data shows no such thing; population-level data shows us unequivocally that prior infection confers immunity. The most recent study on the subject, published in the world-leading New England Journal of Medicine, shows that prior Covid infection conferred better protection against symptomatic Omicron (BA.1 and BA.2 subvariants) more than a year after infection than three doses of vaccine more than one month after the final dose.

However, the Covid fearmongers have another string to their bow. While the number of Covid deaths remains flat, there is increasing attention being given to “long Covid” (LC) as a debilitating condition that requires new restrictions, and yet another round of mass vaccination, in order to prevent more people from being afflicted by it. Should our leaders be listening?

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The first question that has to be answered is: how serious a condition is LC? As with pretty much anything Covid-related, opinion is polarised — and, as so often, the truth is likely somewhere in the middle. While some studies have suggested that it occurs in as many as 30% of people infected with the virus, others have found the number to be 7% overall. One of the most in-depth studies yet, published in May 2022 in the Annals of Internal Medicine, was unable to find any biological explanation for LC symptoms. This, of course, doesn’t mean that LC is all in people’s head, as the researchers who conducted the study were keen to stress. (Indeed, we know people close to us who are suffering from it, so we can testify to the fact that it’s a serious issue.) The study does however suggest that LC might be a much more complex phenomenon than we imagine.

Indeed, the existence of LC in children and adolescents has been the subject of much debate due to the difficulty in ascertaining whether the most common symptoms usually associated with LC — sadness, tension, anger, depression, anxiety, fatigue, sleep disorders — are due to Covid itself or to other (co-)factors. One of the earliest cohort studies on LC, published in August 2021, concluded that:

“It is possible the symptoms associated with Long Covid are in fact a mixture of factors relating to the pandemic and lockdown as a whole rather than the viral infection itself. For example, factors such as social isolation, anxiety, depression or educational concerns may be the root cause of these symptoms in children and young people both with and without SARS-CoV-2 infection”.

Given the devastating and well-documented effects of lockdowns and school closures on the mental health of children, this doesn’t seem unreasonable.

A more recent study conducted by the Italian Society of Pediatrics found that “physical symptoms due to SARS-CoV-2, even if persisting after 4 weeks from infection, tend to regress spontaneously or under treatment in few months, whereas mental problems can persist for a longer time”. Given that “[s]everal factors indicate that mental health problems depend on the stress conditions children underwent during pandemic”, the researchers concluded that, “what has been reported for pediatric long Covid, further suggesting that most of the clinical manifestations characterising long Covid depend on the pandemic and not directly on the infection”.

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One thing is clear: we still know too little about LC, which means we need to step up research into the condition — as sufferers have been demanding for a long time. But it would be unacceptable to weaponise the very real distress of those sufferers in order to justify new non-pharmaceutical interventions that have failed on all possible accounts, or a new round of coercive mass vaccination.

The received wisdom from the political-scientific establishment over the past year or so has been that universal vaccination will lead to herd immunity, and therefore to the end of infection (and, hence, of LC). However, given that the European Union has, to date, ordered 4.2 billion doses of Covid-19 vaccines, most of them from Pfizer — that’s almost 10 doses for every man, woman and child of all ages in the EU — it’s clear that even this establishment never thought that universal vaccination would lead to herd immunity (or at least not quickly). Now, though, even the political authorities (and other figures such as Bill Gates) acknowledge that the vaccines will not get rid of infections and don’t provide protection for long. A huge May 2022 study of more than 13 million people published in Nature Medicine has also found that “long Covid risk falls only slightly after vaccination”. Cases are rising, and there is pressure to “do something”. But if neither vaccines nor non-pharmaceutical interventions can’t prevent Covid infection, and if even some people who are not hospitalised develop LC symptoms, what is the solution?

Here, it’s worth returning to the first months of the pandemic, when there was no certainty that a Covid vaccine would ever be found. In those early months, treatments were considered by many to be every bit as hopeful a prospect as vaccines. You may remember the furore around Hydroxychloroquine, the anti-malarial which was quickly touted as “Trump’s cure” — but which Didier Raoult, one of France’s most cited scientists (and one of the 400 most-cited scientists in the world), also claimed to have used to great effect in the treatment of Covid symptoms early in the pandemic. You may also remember the controversies around Ivermectin.

These treatments were controversial, yes, but some scientists believed initially (and still believe) that effective treatments exist for early-stage Covid; surely, this is an avenue worth exploring? While enormous amounts of money have been spent on the Covid vaccines, much less has been invested in developing early-stage treatments — when treatments have been approved by regulators, such as Remdesivir, they tend to be late-stage courses.

Of course, vaccines are key in preventing serious illness and death in those at great risk from Covid — but this was always, in truth, a comparatively small section of the population, as study after study has shown. Now that it is clear that vaccines do not prevent infection, it’s time to shift the focus to the kind of early-stage treatments that are vital in preventing potential LC from developing. Insisting on the same restrictions and vaccine-centric strategy of the past few years and expecting a different result is, as Einstein might have said, simply insane.

I am an associate professor of epidemiology and biostatistics, as well as a practising physician, and I firmly believe that it would be a mistake to censor Rogan under the guise of combating “misinformation”.

Rogan is not a scientist, and, like everyone else, he has his biases. But he is open-minded, sceptical, and his podcast is an important forum for debate and dialogue. It is not enough, moreover, to simply dismiss Malone and McCullough as conspiracy theorists. They are controversial and polarising figures, but they do have real credentials. Malone is a physician who has worked in molecular biology and drug development for decades, while McCullough was, until recently, an academic cardiologist and researcher.

Both speakers made accurate and useful points on Rogan’s podcast — as well as unsupported, speculative, alarmist, and false ones. The correct way to deal with incorrect ideas in biomedicine, if they rise to a level of prominence that warrants rebuttal, is to rebut them.

In what follows, I attempt to assess their main claims, explaining what they get right and what they get wrong. I cannot address every point that the two of them made — both episodes are close to three hours long — but I hope that I can provide some clarity in a debate that often lacks it.

Claim: The risks of mRNA vaccination are underdiscussed and boosters should be debated

Early in his interview, Malone is critical of the scientific and media discussion of vaccine safety, noting that “no discussion of risk is allowed”. Later, he says that the pejorative label of “anti-vaxxer” is used to stifle legitimate debate over vaccines. Malone and McCullough both warn that mRNA vaccines, such as Pfizer and Moderna, can cause myocarditis, especially in young men who are at low risk from the virus. Given these and other alleged risks, they warn against recommending — or requiring — boosters for the general population.

I believe they are correct in these sentiments. In April 2021, the first reports of myocarditis were noted in Israel, with the majority of cases occurring in young men who had recently received an mRNA vaccine. Since then, the evidence for vaccine-related myocarditis has grown. We know now that boys are more likely to be affected than girls. We know that Moderna has higher rates than Pfizer. We know that dose two causes more myocarditis than dose one. The precise estimate of risk is now thought to be between 1 in 3,000 to 6,000 for males in the target range (roughly age 12 to 30), and researchers have shown that the CDC’s method to study this underestimates myocarditis risk.

Such concerns are not limited to the fringe. Marion Gruber and Phil Krause, the former director and deputy director, respectively, at the US Food and Drug Administration, resigned last autumn over White House pressure to green-light boosters. Paul Offit, a prominent vaccine advocate and the director of vaccine communication at the Children’s Hospital of Philadelphia, recently told the Atlantic that he advised his own 20-something son not to get boosted. Other nations are taking the myocarditis concern seriously, too. Several have banned or discouraged the use of Moderna in young men. Others advise two doses spaced further apart, and some have held off on a second dose entirely for younger age groups.

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It is perfectly valid to question the wisdom of boosters, at least in young people, though I do think they are beneficial for older and more vulnerable people. Like Malone, I have seen researchers smeared as “anti-vaxxers” for simply suggesting that myocarditis is a real safety concern, or that we don’t know the optimal duration and dosing strategy of vaccination, particularly for young and healthy people and those who have recovered from infection. Malone and Rogan are correct that the media dismisses concerns over myocarditis by claiming that most cases are “mild”, when in fact it is too early for us to know the full effects.  And I agree that this is an area of live debate that has not been adequately covered by the media.

Claim: Vaccines have lots of other dangerous side effects

At other points in his interview, Malone alludes to many potential side effects of vaccination, claiming it can result in seizure and paralysis, and that the menstrual irregularities associated with the vaccine suggest it is a “major threat to reproductive health” for women. He suggests that vaccination can suppress T cells, raising the risk of unusual cancers.

To date, I have seen no evidence to support any of these claims, and I believe it is a mistake to raise them. First, they are irresponsible — Malone’s rhetoric verges on fear-mongering — and second, they distract from his legitimate points on myocarditis in young men.

McCullough suggests that vaccine-related deaths and injuries in the US are severely underreported by the Vaccine Adverse Event Reporting System (VAERS). While I agree that there are problems with VAERS, I find it difficult to believe the numbers McCullough offers of 45,000 dead and 1 million injured. Here is why.

VAERS is a voluntary collection network that is prone to two types of biases. First, it may undercount vaccine-related events because providers did not recognise them or lacked motivation to report them. But it can also overcount them. Bad things can happen after vaccination, such as heart attack, that are entirely coincidental but that still might be reported.

Trying to find safety signals due to vaccination requires comparison against base rates, or how many events are expected to occur without vaccination. Even very unusual events, such as the blood clots that happened after the Johnson & Johnson vaccine, stand out fast. Similarly, elevated myocarditis rates in young men, especially after dose two of Moderna, jump out of the data.

Death signals are trickier to parse, and require knowledge of the ages and medical problems of people getting vaccinated. Even then, they must be weighed against data that shows vaccines reduce a big cause of death — death from Covid-19. For these reasons, I think it is premature and misleading to talk suggest that the vaccine caused 45,000 deaths. If McCullough wishes to make this case, the best forum would a scholarly publication, where other researchers can examine and critique his methodology.

Claim: US vaccine policy ignores the science on natural immunity

Malone and McCullough both make valid points that vaccine policy has not accommodated scientific knowledge of natural immunity. Should vaccines be required for people who have already been infected with Covid? If a healthy young person had one dose of the vaccine and then got Omicron, do they need a second? What if a person had two doses and Omicron — should they need to receive a booster, as some workplaces now require? These are open and legitimate questions.

Proponents of vaccines and boosters for those with a prior Covid-19 infection often point to antibody titers — blood tests showing that a recently vaccinated or boosted person has higher levels of Covid-19 antibodies than someone with natural immunity. But this is not persuasive.

Antibodies are a means to a clinical end, which is preventing someone from getting re-infected, becoming very sick, becoming hospitalised, or dying. Antibodies, especially in the short term, are bound to be higher the more you dose an individual, but the scientific burden is to show that these doses further improve the clinical endpoint in randomised studies. This burden has not yet been met.

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Yet, here too, Malone goes over the top. He and Rogan refer to “multiple studies” showing that those who get vaccinated after being infected with Covid are at a two-to four-times greater risk of having an adverse reaction to the vaccine; later, Malone describes Rogan’s friends who are encouraging him to get vaccinated as asking Rogan to put himself “at higher risk” and “take more risk for your health in order to join their club”. There is a dialogue to be had about whether Rogan might benefit from zero, one, or two doses, but the overall risks of vaccination remain low, particularly for a 54-year-old man such as Rogan.

At times, Malone refers to accurate studies, but I worry the audience draws the wrong inference. Malone, for instance, claims that natural immunity is six to 13 times more effective than the vaccine at preventing hospitalisation and 27 times more effective against developing symptomatic disease. I assume he is referring to this August 2021 study from Israel. This study does indeed suggest that natural immunity is more protective than vaccines against the Delta variant, though it also suggests that natural immunity plus a single vaccine dose is more protective than natural immunity alone.

While this has implications for the number of doses a Covid-19 survivor might consider getting, it should not be misconstrued to mean that infection is preferable to vaccination for an adult who has yet to experience either. Vaccination is almost surely preferable for most un-immune adults.

At one point in his interview, Malone says: “Think twice about giving these jabs to your kids.” While I can understand how many will be angered by this statement, the truth is other nations, such as the United Kingdom, are thinking twice — at least for healthy 5 to 11-year-olds, the group with the lowest risk of bad outcomes from Covid. As of this moment, the UK’s advisory panel has said that only 5 to 11-year-olds with comorbidities should get vaccinated.

Claim: Effective early treatments, including hydroxychloroquine and ivermectin, are being suppressed

McCullough and Malone are proponents of early treatment for Covid-19, specifically with ivermectin and hydroxychloroquine. Both allege that public health authorities have intentionally suppressed the use of these drugs. McCullough states that early in the pandemic, “there was no focus on sick patients”, while Malone speculates that hospitals don’t want early treatments because they profit when people are hospitalised and claims that “probably half a million excess deaths” have happened in the United States through the intentional blockade of early treatments.

These are entirely false and insulting allegations, and Malone’s in particular are flat-out conspiratorial. Academic hospitals attempted all sorts of disparate treatment protocols in the hopes of helping sick patients. Many physicians did not wait for randomised control trials — the gold standard of medicine — to act; they simply acted. In fact, a Harvard hospital recommended hydroxychloroquine prior to randomised data.

The problem was not that there was no appetite for early treatment. The problem was that when the randomised trial data came in, they suggested the drugs favored by Malone and McCullough were ineffective. A pooled analysis of all such studies by Axfors and colleagues suggests patients treated with chloroquine and hydroxychloroquine had increased risk of death.

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And ivermectin has not shown persuasive evidence of benefit in randomised trials to date. Of course, a randomised trial cannot prove that a therapy can never work under any circumstances, just as you cannot prove that Santa Claus doesn’t exist. But the burden is on proponents to show when and how their therapy helps, and they have not met it.

Rogan, Malone and McCullough are wrong to claim that ivermectin and hydroxychloroquine are known to be secretly effective, but they are correct that these drugs have been unfairly demonised. The truth is that they are neither particularly dangerous nor effective. The media labelling ivermectin a “horse drug” or “horse dewormer” was particularly absurd. Ivermectin is a well-known drug taken by humans all over the world.

Claim: Public debate over Covid-19 is often unfairly censored

Malone, Rogan, and McCullough are all correct on one topic: there is an effort to suppress information and censor debate on social media. The clearest example is that for more than a year, Facebook banned all discussion of the lab-leak hypothesis, until articles by Nicholson Baker, Nicholas Wade, and Donald McNeil broke the dam. This was a remarkable suppression of free speech.

Previously, I investigated the mechanism by which Facebook polices pandemic “misinformation” through third-party investigators. I found, in several cases, that the expert designated to fact-check a claim had already stated their opinion on it prior to being selected. This is a deeply problematic mechanism, as the person who selects the fact-checkers can scour the Internet to an expert who agrees with them, and there is no external review, appeal or oversight.

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Malone discusses a controversial October 2020 email from National Institutes of Health director Francis Collins to Anthony Fauci in response to the Great Barrington Declaration. In it, Collins called three of the declaration’s authors “fringe” epidemiologists and demanded a “quick and devastating published take down of its premises”. I completely agree this was problematic.

As I have argued elsewhere, 2020 was a time of deep uncertainty about the science surrounding Covid-19 and the appropriate policy response to the pandemic. Collins is not an epidemiologist, and he has no standing to decide what counts as a “fringe” view within that field. As NIH director, his job is to foster dialogue among scientists and acknowledge uncertainty. Instead, he attempted to suppress legitimate debate with petty, ad hominem attacks.

***

The efforts to censor Malone and McCullough have massively backfired, with both men gaining prominence and publicity from the attempts to shut down their speech. More generally, I strongly disagree with efforts to censor scientists, even if they are incorrect, and no matter the implications of their words, as I believe the harms of censorship far exceed any short-term gains.

One problem, which has been on full display in this controversy, is that censorship may draw more attention to incorrect ideas. Another is that in the middle of any crisis, the answers to many scientific and policy questions will be uncertain. Disagreement on these questions is natural, and attempts to suffocate “harmful” speech run the risk of stifling critical debates, including by silencing third parties who may have important contributions but who fear the professional or reputational consequences of speaking up.

Perhaps the most serious objection to censorship is that the censors themselves are not fit for the task. Censors are unaccountable. They may be biased, misinformed or undereducated. They may lack perspective. In short, they are as fallible as the people they are trying censor. This is especially true in science, where, as history shows us, consensus views can turn out to be false, while controversial or heretical ideas can be vindicated.

Finally, in the modern world, where the censor is so often a giant technology company, there is tremendous potential for abuse. The same tools used to suppress scientific “misinformation” may someday be used to solidify political power and stifle dissent.

The Chinese-controlled results sparked global accusations of a whitewash and further corroded confidence in the WHO. Few experts give much credibility to claims the pandemic was imported on a packet of chilled pork or slab of frozen pangolin sold at a market. And demands are growing for the leak hypothesis to be taken more seriously. Wuhan, after all, is the major research centre for bat coronaviruses in Asia, where there are secretive labs, known biosafety concerns and high-risk experiments being conducted.

It has now emerged that Feng, deputy head of China’s Centre for Disease Control and Prevention (CDC) and an expert on emergency health responses, performed an even more sinister role as the pandemic played out. He was one of four names copied on a CDC memo sent out in February 2020 ordering China’s scientists not to share any data, documents or specimens relating to the epidemic and to “prioritise the interests of the country”. The memo warned that anyone violating the request would be “dealt with severely in accordance with discipline, laws and regulations” — a threat to be taken seriously in a country ruled by fear.

The document, originally obtained by Associated Press last year among a cache labelled “not to be made public”, was a key plank in President Xi Jinping’s campaign to regain control of the pandemic narrative by silencing dissenting scientific voices and shutting down internal debate. It was sent out following the publication of report by two Chinese scientists which concluded “the coronavirus probably originated from a laboratory”, as well as a series of investigations by local media and citizen reporters into pandemic failings. The scientific report was swiftly withdrawn and journalists jailed on grounds such as “picking quarrels and provoking trouble”.

This nugget about Dr Feng’s disturbing dual role — as a voice of the WHO study into pandemic origins while also party to a Communist dictatorship’s clampdown on unfettered scientific discussion — was dug out by an Indian architect and film-maker, who shared it earlier this month on social media under his moniker ‘The Seeker’. “I know how to use a search engine,” he told me.

Last year, he made an even more significant discovery: a thesis that discussed how three miners died of a mysterious respiratory disease, eerily similar to Covid 19, they caught while clearing out bat droppings in a cave network in Yunnan, southern China. The trio were infected in an abandoned copper mine where scientists from Wuhan Institute of Virology sampled RaTG13, the closest known relative of Sars-Cov-2.

‘The Seeker’ is a member of Drastic, an informal guerilla group of internet sleuths, scientists and data experts who have spent the past year scouring a multitude of digital sources for such vital pieces of evidence. Some members have expertise in areas such as microbiology, genetics and virology. Others are data specialists, engineers or simply obsessed with discovering the truth about the origin of this wretched pandemic. Some hide their identities; others are open. They have been accused of hacking and fiercely deny it. Occasionally they hurtle down blind alleys.

Yet there is no doubt their collective efforts — and some of the illuminating evidence they have uncovered — have been crucial in challenging both China and the scientific establishment to ensure the lab leak theory is properly investigated. “We have exposed so many things they wanted to cover up, while there has been too much geo-politics around the issues,” said Gilles Demaneuf, a French data scientist who works at a New Zealand bank and is another Drastic member. “Many people now accept there is a possibility that a lab leak was the cause of the pandemic and that this is not a conspiracy theory as claimed at the outset.”

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It has been fascinating to see, in the course of my investigations over the past year, how this group of activists — in tandem with few brave scientists — has forced the lab leak hypothesis from the shadows. Note how the UK was one of 14 nations that reacted so strongly to the dismal WHO report by accusing China of “withholding access to complete, original data and samples”, while Anthony Blinken, the new US secretary of state, criticised China’s cover-up and called for deeper investigation at the weekend. Even Tedros Adhanom Ghebreyesus, the WHO’s director-general and a long-time Beijing crony from his days as a minister in an Ethiopian autocracy, had to insist that “further data and studies will be needed to reach more robust conclusions”.

Typical of Drastic’s work was the way Demaneuf stumbled across an interview in the Chinese magazine Health Times with Yu Chuanhua, professor of biostatistics at Wuhan University and compiler of China’s official case database. The Beijing line, rubber-stamped in the WHO report, claims the first confirmed Covid case was on December 8, 2019 with no evidence of the virus in Wuhan before then — although this conflicts with research published in medical journals, media reports and claims made by the US State Department that Wuhan scientists were possibly infected in the autumn. Yet Prof Chuanhua told the magazine there were 47,000 cases on his database by late February, which included one suspected fatality — a patient who had fallen ill on September 29, 2019 — followed by two suspected cases on November 14 and 21.

This interview took place on the same day that Chinese health authorities issued their scientist gag. Prof Chuanhua subsequently contacted his interviewer to retract what he had said, claiming the onset dates may have been entered wrongly. Now go back to that memo tied to Dr Feng: it ordered experts to withdraw and redo any papers or “progress reports” that had not been sanctioned. Is this a coincidence — or another sign of China’s appalling cover-up, now endorsed by the WHO?

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Another key figure in Drastic is Yuri Deigin, a biotech entrepreneur. Early in 2020, he started to doubt the conventional wisdom that the lab leak hypothesis was some kind of crazy conspiracy. And the more he delved, the more his doubts grew. He published his thoughts in a long analysis last April, first in Russian and then two weeks later in English. This prompted private discussion groups with fellow sceptics on social media, which evolved into the informal grouping with its determination to challenge a complacent scientific consensus that the pandemic was, beyond doubt, a natural spillover event.

Later, Deigin published a paper with Austrian-based microbiologist Rossana Segreto given the blunt title “The genetic structure of Sars-CoV-2 does not rule out a laboratory origin”. The Canadian-Russian scientist continues to press his case, having just published a pre-print paper with researchers from Canada, Japan and Spain highlighting the existence of undisclosed coronaviruses at Wuhan Institute of Virology, and expressing fresh concerns over its biosafety.

He has come under fire from other scientists. “They attacked my credibility,” he tells me, “my competence and me personally but I’ve destroyed critics with solid arguments.” Another scientist in the group, an academic in the US, was less fortunate. He lost his research post, which he says followed a complaint and warning to stay silent from his university’s corporate partner when he aired his dissenting views in the media.

Drastic has 26 core members divided into sub-groups exploring aspects such as biosafety, missing databases, coronavirus vaccine development, tracing and translating deleted documents, along with its own website. The co-ordinator, who adopts a mischievous style on social media, calls himself “Billy Bostickson”. He admits to feeling a duty to carry out the investigations, “out of respect for so many old folks who died and the terrible effect on local economies”.

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Another member of the team is Monali Rahalkar, an Indian microbiologist, who wondered why prominent scientists seemed so certain the virus had natural zoonotic origins. So she started ploughing through scientific papers during her lockdown in Pune last March. “I read one paper that argued Sars-CoV-2 could not have come from a lab,” she says, “yet I could see they were doing lots of work on various coronaviruses in Wuhan.”

Rahalkar learned about the miners’ deaths and high-risk “gain of function” research carried out in Wuhan that forces viruses to evolve fast in order to assist vaccine development, but which some experts have long warned risk sparking a pandemic. Working with her husband, a fellow scientist, she carried out “blast” tests on genetic sequences taken from another strain of bat coronavirus found by Professor Shi Zhengli — the celebrated Wuhan-based virologist known as “Batwoman” for her expeditions to gather samples in caves where the mammals roost hundreds of miles from her lab. This strain came from samples collected in Yunnan and was identified in 2016, yet there was no link made to the miners. The pair were puzzled by their findings since it showed such similarity to RaTG13, so they posted a paper about their research.

Following their criticism, Prof Shi published an addendum to her paper in Nature, admitting these were the same virus and also linked to the miners’ deaths — and that she also has genetic sequences from seven other unidentified viruses sampled there. Inevitably, her reaction has fuelled concerns over the Wuhan labs, especially since this prominent scientist has admitted her first thought on learning about a novel coronavirus outbreak in the central Chinese city was that it could be a lab leak.

Drastic’s members have also found evidence of virus databases being deleted, anomalies in scientific papers and published statements, details of pathogenic experiments on humanised mice with modified coronaviruses, scrubbed lab website pages, even details about patents for bat breeding cages at Wuhan Institute of Virology.

There is still no conclusive explanation for the origin of this devastating pandemic. But science, like journalism, should always follow the trail of evidence to wherever it leads. This crucial issue was clouded by Donald Trump’s aggressive intervention on the subject, since his toxicity made it easier for experts to dismiss concerns of a lab leak as a conspiracy theory; it enabled respected scientific journals to close down debate and for reporters to ignore glaring conflicts of interest among key figures.

Yet the significance of these sleuths goes beyond even the task of unravelling the origins of a new virus that has killed almost 3 million people worldwide and raising uncomfortable questions over closed minds, let alone posing the question of whether scientists themselves might have accidentally sparked this global disaster. Ultimately, their digging is a reminder that in the digital age even the most powerful states, even an Orwellian dictatorship such as China under Xi Jinping, cannot erase everything from the past and hide all truths, however hard it tries.

They’re unsettling, disgusting things, threadworms: or they were to me, when I first came across them. But – luckily – they’re easily treated. A cheap, over-the-counter medicine, mebendazole, kills the lot. You have to dose the whole family, clean your linen, and dose again two weeks later, because the eggs (god, I’m shuddering just typing this) survive for a couple of weeks; but basically there is a simple, nuke-them-all-from-orbit cure.

Threadworms are just one species of intestinal worms, also known as helminths; there are hookworms, pinworms, tapeworms, whipworms, others. And they’re common — not just in north London, but around the world. The US Centres for Disease Control estimate that Ascaris lumbricoides is present in the intestinal tracts of about 1 billion people around the world. Usually, the infection has no symptoms, but in children it can lead to malnutrition, slow growth and impaired learning.

Luckily, again, these helminths can be killed with the same drug, mebendazole, or a related one, albendazole. Just as with the threadworms that cause itchy bottoms in the rich west, the Ascaris that cause childhood stunting in the developing world can be nuked, effectively and cheaply. A course of albendazole costs a few cents.

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By Tom Chivers

Dosing someone who’s been diagnosed with helminths, then, is a no-brainer. It’s cheap and easy and effective. But over the past 20 years or so, there’s been a row going on about doing more than that: about giving the drugs to entire schools’ worth of children, regardless of whether they’ve been diagnosed with worms or not. 

In the late 1990s, two economists, Edward Miguel of Berkeley and Michael Kremer of Harvard, ran a study. They took 75 schools in Kenya, and gave albendazole to all the kids in 50 of them. Their results were impressive: absenteeism dropped by a quarter; children did better at school. The benefits also seemed to spread to nearby schools which hadn’t been treated, presumably by disrupting the spread of worms in the region. The whole thing cost $3.50 per pupil.

Where it got really interesting, though, was a follow-up study, a decade later. It found that the children in the schools not only did better at school — when they left school, the benefits continued. They earned more — about 15% more, on average — than those who had not been dosed. That is a huge benefit for a tiny cost. So everyone — including the WHO — got on board with deworming programmes. (Apparently, Cherie Blair even dressed up as a giant worm at Davos and chased people around.)

Then it all went a bit crazy. Two epidemiologists at the London School for Hygiene and Tropical Medicine reanalysed Michael and Kremer’s data, and found errors in the code, and some missing information, which led them to severely downgrade the findings: notably, the effect on surrounding schools disappeared. (It’s worth noting that there’s no suggestion of malpractice, and the LSHTM team and others have been full of praise with M&K for sharing their code and data so fully.) They also noted that the study wasn’t properly randomised or blinded. Then the well-respected Cochrane Collaboration released a report saying that there was little evidence that deworming programmes show benefit. Now a new study, again by M&K, claims that the economic benefits are still continuing.

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If you want to read about the whole saga, which came to be known as the Worm Wars, I recommend Tim Harford’s thoughtful take on it, and Ben Goldacre’s more sceptical one. There is a lot of back-and-forth, with defenders of M&K saying that the statistical techniques used by the LSHTM team made it almost impossible for the programmes to find a benefit. “To be quite frank, you have to throw so much crazy shit at Miguel-Kremer to make the result go away that I believe the result even more than when I started,” said one professor of public policy. On the other hand, one researcher into evidence-based charity told me “no one believes this but the economists”.

This all came up when I was writing my last book — which, somewhat incongruously, was about artificial intelligence, and whether it would destroy the human race. The two topics don’t necessarily seem connected, but they are.

The effective altruism community is a loosely affiliated group of people and organisations who try to find the best way of donating and spending charitable money, so it will do the most good in the world. For instance, imagine you want to help people who have visual impairment. You’re deciding whether to donate to a guide dog charity, or to a charity which provides surgery for trachoma in the developing world. As the effective altruism charity Giving What We Can points out, it costs about $50,000 to breed and train a guide dog, but you can restore many trachoma sufferer’s vision with an operation costing about $1,000. “For the same amount of money as training one guide dog to help one person,” they say, “we could instead cure about 50 cases of severe vision impairment.” That seems a fairly straightforward decision.

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The inhuman politics of artificial intelligence

By jon cruddas

Sometimes it’s not so clear. Is extending someone’s life by a year worth more or less than providing secondary education for a child? Is funding research into a Covid vaccine more or less effective than supporting democratic movements in authoritarian countries? But often, since most of us give to charity in fairly un-thought-through ways, it’s easy to improve the good we do. The simplest method is what William MacAskill, a professor of ethics at Oxford and founding member of the effective altruism movement, calls the “100x multiplier”: if you donate to a charity that works in the developing world, you can roughly expect to do 100 times as much good as if you donate to one that does a similar thing in the rich West. 

Effective altruist organisations such as GiveWell and Giving What We Can give lists of the most efficient charities to give to: the standout ones are about malaria. GiveWell estimates that roughly every $2,300 spent on bednets coated in insecticide will save one child’s life.

What I find interesting, though, is that both organisations recommend the Deworm the World Initiative and other deworming programmes. The effective altruism movement isn’t unaware of the Worm Wars controversy: GiveWell discusses it all in two lengthy, stats-heavy blog posts. They mention various reasons why the Cochrane review might have missed something — notably, it only looked at weight gain and school performance, not future earnings. But they also note that the children Miguel & Kremer’s research looked at had abnormally high levels of infestation, and that there are no obvious short-term mechanisms which could explain the long-term benefits — which should make us less confident that there’s anything real going on.

But they still recommend it — because, in short, they think the gamble is worth it.

There’s a concept in probability theory called “expected value”. That is, how much, on average, you can expect some action to return. Say someone offers to flip a coin with you: on heads they pay you £2, on tails you pay them £1. Your expected value is (2-1)/2, or 50p: if you played the game lots of times, you’d expect to make an average of 50p per throw.

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With deworming, effective altruists are doing exactly the same thing. There’s a strong possibility that deworming has no effect whatsoever on future earnings, or at least a hugely reduced one. But there is a small possibility that it has a huge, overwhelming impact, at a very low cost. The expected value of deworming — the impact multiplied by the probability, minus the cost — is huge, even taking into account the possibility that it doesn’t work at all. GiveWell assumes that its impact is 100 times less than the Miguel-Kremer study claims, and, even at that level, finds that it is cost-effective.

This is all very straightforward and I think most people would get on board with it. But the same reasoning leads you to stranger places, which is where AI comes in.

Nick Bostrom, the philosopher and AI researcher, points out in his book Superintelligence: Paths, Dangers, Strategies that there are a lot of humans who are yet to live. I discussed exactly how he works it out in an earlier post, so I won’t go over it again, but he ends up with 10^58 humans (one followed by 58 zeroes; a big number) before we run out of universe. That would be a very great positive — assuming that we think that human life is a positive thing, and that we would, all else being equal, prefer more happy lives than fewer.

So ensuring that humans don’t go extinct (a rogue AI or a bioengineered pandemic are considered the most likely ways that will happen) has a huge potential upside: quintillions and septillions of lives, unthinkably huge numbers. So even if there’s only a one-in-a-billion chance that he’s right, or one in 10 billion, it doesn’t matter. Those numbers are so huge that the expected value of anything that might improve the chance even by a fraction of a percent make the expected value — the benefit times the probability — spectacularly large. 

So, for large parts of the effective altruism community, the most effective way to do good in the world is to donate to organisations that will reduce the chance of an AI apocalypse, and to ensure that any superintelligent AIs we do build will work to help humanity survive, in a form that we would want.

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Are economists really this stupid?

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This sort of reasoning can take you to some very strange places, but it’d be too easy to wash your hands of it and say it’s all crazy. It’s not; if anything I rather admire the tendency to follow the reasoning where it leads, and not simply pull up short and say “OK now we’re getting weird.” My own instincts are that concern about existential risk is pretty sensible and that AI is a reasonably likely way that we could blow ourselves up. And most effective altruism is of the much more worldly, small-scale “antimalarial bed nets” calibre.

This latest Miguel/Kremer study, for what it’s worth, doesn’t seem to have shifted opinions much in the Worm Wars. The evidence-based charity researcher I spoke to points out that it is essentially a continuation of the previous studies, so all the problems that existed in the first studies are still there now. More than that, it follows the same group of people as the previous ones — it would be frankly weird if they had all suddenly become poor, after years of being richer.  “Same shit, different year,” the researcher said, succinctly. More importantly, this person says, there is a chance — which as far as I know has not been studied — that mass dosing with deworming drugs could cause worms to evolve a resistance to those drugs, like antibiotics create antibiotic-resistant bacteria. It is not inconceivable that the actual impact is negative, which would affect the calculations somewhat. 

Miguel Kremer, meanwhile, has won a Nobel prize in economics. “So we know who won the Worm Wars,” my source says. “I’m sure that will end all the arguments;” that last said with heavy sarcasm.

I’ve broken the omertà; if you don’t hear from me again, I’ve been silenced by the parent mafia. Only parents and developmental economists are allowed to talk about de-worming. But now you know how itchy bottoms relate to the AI apocalypse.

Then, this weekend, it was the turn of Professor Neil Ferguson to answer the Swede’s critique that his overly pessimistic forecasts had tilted the Government into Chinese-style dirigisme. He cut a very different figure — more cautious, more media-trained, lacking the charismatic heft of the Professor Emeritus but making up for it with precise deployment of the facts and figures. Much as he’d love to be proved wrong, he said, the UK fatality rate of Covid-19 is likely to be 0.8-0.9%, which means that even letting out only the young and healthy will lead to more than 100,000 deaths later this year. We need to prepare for a long fight, a new socially-distanced normal, potentially for years to come.

In theory, theirs is a purely scientific disagreement that boils down to Infection Fatality Ratios, seroprevalence assays, and R0 numbers — and one or other of them will eventually be proved right. But somehow I suspect there will always be enough controversy around how deaths are counted and the economic and health impacts of lockdown to defer that judgement indefinitely. It’s also quite possible that one of them could end up being right in spirit while wrong on the numbers.

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All eyes on the Swedish coronavirus experiment

By Freddie Sayers

Alongside all the metrics, and the vital assessments of the human cost of different policies, where you stand on this wretched virus also comes down to attitude — your world view. Are you more Giesecke or Ferguson? The expert that most resonates is unlikely to be entirely down to your assessment of the science — more likely a complex combination of your politics, your own life experience, your attitude to risk and mortality and your relationship to authority. Perhaps each of us have elements of both instinct within us — but what do they really represent?

What they are not, despite the attempts of some social media voices to make it so, are good and evil. Clearly, both experts are highly accomplished scientists doing their best to understand a complex threat. Likewise, the wider debate around lockdown is not a contest between rational, good people who value life on the one hand and the cavalier and cynical who care only about economics or themselves on the other. If the do-gooder class try to push that narrative, they will simply lose the argument.

There is not even an in-principle disagreement about the sacredness of every human life, despite attempts to slur those in favour of a speedier timetable out of lockdown as “pro-death”. The principle that some level of increase in infection, and therefore more deaths, is tolerable for the wider good is not often said publicly but is already accepted on both sides of the argument. Denmark, the poster-nation for early and stringent lockdown, has now brought back junior schools alongside published modelling that showed what level of increased infection (and therefore deaths) they expected it to lead to. Nobody raised an eyebrow, because the education of children is so obviously a moral good. It’s really a question of where you fall on a spectrum: how much death would you tolerate, for which wider goods?

In UK policy terms, the ‘landing zone’ now lies in the space between these two experts. At the Giesecke end, we would define success simply in terms of ensuring the NHS is not overwhelmed — this means slowing the spread and protecting vulnerable people as much as practically possible but moving to lift lockdown measures and only reintroducing them if the health service is challenged. At the Ferguson end, we would attempt to keep the outbreak at such low levels that we can wage a long-term ‘test, track and trace’ suppression of the virus, with elements of social distancing to minimise transmission until a vaccine is found.

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The appeal of the first of these options is that it has a clear rationale and an end-point when the virus has passed and life can return to normal. But it suffers from seeming callous and is highly dependent on the quantum of deaths. If we have 100,000 additional Covid deaths within the year, as Professor Ferguson warned, but could get fully back to normal after that, would that be acceptable? At two people in every thousand, most people would then know somebody who died. What about only 20,000 more? Or 200,000?

The Ferguson end of things will likely be more attractive to politicians as, while sidestepping this difficult question, it carries with it a clearer sense of virtue and action. As Gov Cuomo of New York is now fond of saying, “we’re not going to accept the premise that human life is disposable.” There is a strong appeal to society pulling together to protect our most vulnerable, and we know from polls that the public continues to support the more cautious approach.

But it is dangerous because it has no clear measure of success, and no way out: if the goal is just to “keep transmission low”, how low is low enough? Any move away from total lockdown potentially takes you further from your goal, and back towards a relentless fear of cases starting to creep up once again.

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In the ‘Giesecke’ worldview, this would amount not to a victory but to a surrender. The world becomes a place of indefinite anxiety, with the constant threat of curtailment hovering over all that is best and most human in life — family get-togethers, religious worship, children playing, plans for the future, creative projects – it risks becoming a conscribed, smaller, more fearful world. At its most extreme, a long-term ‘suppression state’ really could start to feel like oppressive regimes of history, from the Puritans to the Communists, that misguidedly tried to remake the whole natural order in pursuit of a single definition of virtue. People who recoil from any move in this direction can hardly be dismissed, or called immoral.

Somewhere in between these two opposing instincts lies a wise way forward; a path has to be found between not just different assessments of the facts but different world views.

In between his careful words, I detected something of the idealist about Neil Ferguson — the younger of the two scientists was keen to break new ground and win a battle. “We’re in a horrible place, aren’t we,” I said, expecting him to agree, but he immediately countered that, on the contrary, the world has achieved what he never thought he would see in this century, and has collectively stopped a highly infectious respiratory virus in its tracks. The South Korean model offers hope for an unprecedented new technology-driven response to an epidemic. For an expert who has spent years looking at fatality rates and modelling outcomes this must feel like huge progress: the entire world united against a disease.

Meanwhile, somewhat ironically given the laser-targeted threat of this disease on the old and vulnerable, the Giesecke approach felt imbued with the more philosophical perspective of later life. He has seen many pandemics; we live in a world full of various threats and dangers, and we can’t stop everything to try to run from one new one. Young people must be allowed to do what young people do, and older people, without the luxury of unlimited years ahead of them, must be allowed to choose to go back to seeing their grandchildren and living a full life even knowing the risks.

Whether you’re more Giesecke or Ferguson, it’s time to stop pretending that our response to this threat is simply a scientific question, or even an easy moral choice between right and wrong. It’s a question of what sort of world we want to live in, and at what cost.

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.

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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.

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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. 

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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.

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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.