The battle of the Covid super-forecasters heats up

Can science be as divisive as politics? Katie Strick reports on the war of the macho modellers looking into Covid’s crystal ball
Dr. Fauci Testifies To Senate Health Committee On Country's COVID-19 Response
Getty Images

The UK could hit a million Covid cases a week. The pandemic will be over by October. The next Covid variant could kill one in three people and we’ll be living with the virus forever. These statements might sound contradictory, but they’re actually all predictions put out by some of the country’s top epidemiological modellers in the last month.

Since the start of the pandemic, the UK’s pandemic predictors have become the closest the Government has to a crystal ball. Already, the work of these super-forecasters has become instrumental in shaping policies, from lockdown to vaccinations. The future the economy, our arts and culture is all dependent on what these forecasters say about the risk of Covid.

“If 2020 isn’t enough of a galvanising shock to say we ought to take science and technology seriously… then I don’t know what would be,” Dominic Cummings said to MPs earlier this year (in one of his more practical comments). But science can be political too — and the super-forecasters do not always agree. Their ages, political biases and even romantic histories have all been suggested as reasons for their varying predictions as well as the competitive nature of this field, with scientists and academics competing for funding and positions during a rare moment in the spotlight.

The latest row is global. It sees Nate Silver, the founder of American opinion poll analysis giant FiveThirtyEight, who correctly predicted the outcome of all 50 states in the 2012 election, up against Professor Neil Ferguson of Imperial College London, in a macho modelling bun fight. Silver started it, saying: “Covid cases have fallen to 33,000 per day (seven-day average) since Neil Ferguson, perhaps the UK’s most prominent epidemiologist, said it was ‘almost inevitable’ that cases would hit 100,000 a day. I don’t care that the prediction is wrong, I’m sure this stuff is hard to predict. It’s that he’s consistently so overconfident. Now he says he’s ‘positive’ the pandemic will be over by October. Well, probably. But there are downside risks: new variants, waning immunity, etc.”

Canadian-American political science writer Philip Tetlock (and the author of the Cummings-endorsed book Superforecasting), weighed in: “Expect even top forecasters to make lots of mistakes. When smart forecasters are consistently overconfident, start suspecting they’re not playing a pure-accuracy game.” In other words, just because predictions are bold, that doesn’t mean they are correct.

Dr Neil Ferguson
Thomas Angus, Imperial College London

So who is to be believed? And how correct can we expect these modellers to be, anyway? From the professors duelling over lockdown to the controversial herd immunity debate, this is how the modellers are going to war.

One of the longest-standing Covid culture wars has been between those for and against any form of lockdown. On one side is Ferguson, a mathematical epidemiologist at Imperial College London. The slim, bespectacled 51-year-old has a CV dating back to the foot-and-mouth crisis and quickly became the mastermind of UK lockdown modelling alongside Sage (Scientific Advisory Group for Emergencies), his forecasts leading to the introduction of the first stay-at-home restrictions and social distancing (even though he is now saying it will be over by October). He has locked horns with Dr Sunetra Gupta, 56, a theoretical epidemiologist at the University of Oxford and one of the most divisive figures in the debate, who believes herd immunity is the way forward. The distinguished academic and romantic novelist — she has written four —has been labelled Professor Reopen for her calls for the immediate resumption of “life as normal” for everyone except the “vulnerable”, set out in her so-called Great Barrington Declaration, co-authored with fellow professors Jay Bhattacharya and Martin Kulldorff. Both Ferguson and Gupta say their models are based on science — so how much of their contrast in forecasts comes down to politics?

The future of the economy, our arts… is dependent on what these forecasters say about the risk of Covid

Gupta has denied “smears” claiming she is affiliated with Right-wing groups or that her work is pseudo-science, insisting she’s “more Left than Labour” and that her Declaration represents both Right and Left-wing politics. Ferguson’s Twitter feed, meanwhile, suggests he’s more comfortable on the Left. He congratulated Lib Dem MP Layla Moran on her election victory in 2017 and the woman he was caught breaking lockdown to have an affair with last year, Antonia Staats, is a Left-wing campaigner. Others believe there were wider politics involved in Ferguson and Gupta’s nerd-off. Mike Hulme, a professor of human geography at Cambridge, suggests Sage’s “panicked” lockdown policy with Ferguson was influenced by its own “at-risk” members — just look to their average age, he pointed out in October last year. Another controversial area of the modellers is herd immunity.

“There’s a lot of evidence suggesting that immunity plays a role in bringing down epidemics,” Gupta said in an interview last year. Scientists initially estimated that 60 to 70 per cent of the population needed to gain resistance to the virus to banish it — it’s still the figure cited by the World Health Organisation — and April saw scientists from UCL, led by Professor Karl Friston, claim Britain would achieve herd immunity (73.4 per cent of the population) in a matter of days. Friston’s prediction was quickly disputed and over time the herd immunity debate has grown increasingly murky. According to Stefan Baral, associate professor in epidemiology at Johns Hopkins University, there is a “tremendous amount of fear in the scientific community” when it comes to speaking out against bodies such as WHO. The modellers can of course change their ideas.

Meanwhile Dr Anthony Fauci, an infectious diseases expert and adviser to the US President, has started shifting his herd-immunity estimate upwards. He now thinks it might take closer to 90 per cent immunity to stop the virus. “Things are going to get worse,” he told the Wall Street Journal, pointing to the more contagious Delta variant. Now, many are calling for a new definition of herd immunity. “We need to define herd immunity carefully as we think about the future,” said Professor Christl Donnelly, of Oxford University and Imperial College. But how much hope can we invest in that future?

8831195 Scientists from Harvard, Oxford and Stanford write letter slamming COVID-19 lockdown policies and calling for herd immunity
Dr Jay Bhattacharya of Stanford University, Dr Sunetra Gupta of Oxford University and Dr Martin Kulldorff of Harvard University
The Great Barrington Declaration

“I’m positive that by late September/October time we will be looking back at most of the pandemic,” Ferguson told BBC Radio 4 at the end of last month. He has largely been known for his pessimistic predictions, so should this give the UK public hope?

Not quite, according to statistician Silver. Writing on Twitter, he noted that Ferguson was “consistently so overconfident”, warning of the risks of new variants and waning immunity. Tetlock explained that a phrase like “serious possibility” might mean a 20 per cent chance to one person and an 80 per cent chance to another.

There is a tremendous amount of fear in the scientific community when it comes to speaking out

Silver and Tetlock are not alone in their concerns. Ferguson’s prediction sits in stark opposition to a recent Sage warning of a “risky” autumn and, more worryingly, that a new variant could kill up to one in three people is a “realistic possibility”. Meanwhile, similarly-named rival Niall Ferguson, a history professor at Harvard, told Bloomberg he believes we should be ready to live with Covid “forever”. “We may still be languishing in the second quarter of this pandemic — or maybe it’s early in the second half,” he said.

Tetlock claims there is an inverse correlation between the fame of forecasters and their ability to predict outcomes. Certainly, one thing’s for sure: the Covid crystal ball is murkier than it seems.

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