Welp: Sweden withdraws study suggesting that one-third of Stockholm's population may have been infected

It seemed like a bad sign last night when even an ignoramus like me was able to spot a problem with one of their claims. According to Forbes, Sweden’s top epidemiologist said at a press conference that “the study indicates that for every confirmed case of COVID-19, a further 999 people are likely to have been infected with the virus without knowing it.” But the country’s public health agency later contradicted him and said that’s not true. Why?

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Probably because, with 15,000 confirmed cases already, a potential 1,000-to-one ratio of actual infections to confirmed cases would require a population of 15 million people. Around five million more than the actual population of Sweden.

The study’s now been temporarily withdrawn, per Forbes:

The Swedish Public Health Agency made international headlines yesterday by estimating that one-third of Stockholm residents would be infected with the coronavirus by May 1. Less than 24 hours later, the Agency has taken a dramatic u-turn and withdrawn the report.

The decision was announced via Twitter: “We have discovered an error in the report and so the authors are currently going through the material again. We will republish the report as soon as it is ready.”

Everyone makes mistakes, but I’m curious to see if the error involved something obvious, like the 1,000-to-one ratio, which would force a correction because the public is already aware of it or if it’s something more subtle, in which case withdrawing the study to get it right would be a show of good faith. If it turns out that this particular mistake just so happened to make Sweden’s “herd immunity” strategy appear more effective than the data supports, that confirmation bias will make it harder to trust them going forward.

This wasn’t the only study out of Sweden to be withdrawn yesterday either. “Another Swedish report on the coronavirus spread in the capital has also been withdrawn by its authors,” Forbes adds. “The preliminary findings by researchers at Karolinska University Hospital and the Karolinska Institute estimated that at least 11 out of 100 blood donors in Stockholm had already developed antibodies to the coronavirus.” An 11 percent attack rate seems superficially plausible for a city like Stockholm that hasn’t closed schools or issued lockdown orders. There’s no hint as to what went wrong with that study, although the fact that the government’s study suggested that one-third of Stockholm has been infected rather than 11 percent leaves a large and significant gap between the two.

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Sweden does have some encouraging hard data to report, though. I noted myself in last night’s post that the refusal to lock down there hasn’t produced an apocalyptic runaway epidemic (yet), even if the country does have a relatively high number of deaths. Sweden has taken a middle-ground approach, avoiding stay-at-home orders but avoiding business as usual as well. People are encouraged to be responsible in distancing from others and large gatherings are banned. That’s enough to avert the worst-case scenario so far, notes an author writing in the Spectator:

Perhaps more important is the situation at our hospitals and their intensive care wards. The main ambition of suppression policies, after all, has been to avoid hospitals getting overwhelmed by patients they cannot treat because of shortages of staff, equipment and intensive care beds. Modellers in Sweden that have followed an Imperial College type approach have suggested demand will peak at 8,000 to 9,000 patients in intensive care per day. But actual numbers are telling a very different story. Yes, the situation is stressful, but – mercifully – the growth in intensive care patients has slowed down remarkably and the number of patients currently in intensive care has flatlined.

We now have about 530 patients in intensive care in the country: our hospital capacity is twice as high at 1,100. Stockholm now averages about 220 critical care patients per day and its hospitals, far from being overwhelmed, have capacity for another 70. Stockholm also reports that it has several hundred inpatient care beds unoccupied and that people shouldn’t hesitate to seek hospital care if they feel sick. A new field ward has been set up in Stockholm for intensive and inpatient care and some predicted it would start getting patients two weeks ago. It hasn’t received any patients yet.

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How much added value are other western countries getting from their “social distancing + lockdowns” strategy relative to Sweden’s “social distancing only” approach? Two different pieces circulating today looked at that question and concluded: Not much. One comes from Wilfred Reilly at Spiked, who compared different nations and different U.S. states to see whether the lockdown jurisdictions performed meaningfully better at containing the epidemic than non-lockdown ones. The only meaningful variable in western countries was population, says Reilly: Places like New York, where there are more people and those people are more concentrated, are going to have a tougher time of it. Asian cities like Hong Kong with huge populations have done spectacularly well at holding down their outbreaks, Reilly allows, but it’s apples-and-oranges with western cities because Asian countries have experience containing epidemics early thanks to SARS.

The other piece, titled “Lockdowns Don’t Work,” comes from Lyman Stone and looks at how outbreaks in different countries developed time-wise relative to the lockdown orders issued in each. Stone found that the curve began to flatten *sooner* than we’d expect in each country if lockdowns were driving the drop in infections, in light of what we know about how long COVID cases take to develop and run their course. That is, it appears that people were beginning to voluntarily stay home and take precautions while out and about to limit transmission even before the government stepped in and required them to shelter in place.

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My findings are striking: for every eight days (including weekends) since school cancellations began, a county tends to have one less death per 100,000 people. For every nine days a ban on gatherings over 500 people has been in place, there’s one less death per 100,000 people. These policies work. But the correlation flips for bans on gatherings of fifty people or for stay-at-home orders. For every two weeks a stay-at-home order is in place, the death rate rises by one person per 100,000. For bans of gatherings of fifty people, it’s every eleven days.

It’s counterintuitive that a sustained lockdown might cause deaths to slowly *rise.* We can speculate that because people have different thresholds for how much self-isolation they can take, some who are forced into staying home for longer than they’re comfortable might eventually rebel and engage in reckless mass gatherings. (Ahem.) But that cuts both ways. Logically, one would think, there are people at the beginning of an epidemic who’ll refuse to take it seriously even after much of the rest of the population is already social distancing voluntarily. See, e.g., the spring break crowd in Florida last month. Stay-at-home orders are going to keep some of them away from each other, limiting transmission.

The “lockdowns don’t work” debate won’t really begin to rage until some states reopen up, see a predictable uptick in transmission, and their governors are then forced to decide whether to undertake a second lockdown to limit them. Reilly and Stone would presumably say no — but note that Stone, at least, is a fan of all sorts of lesser social distancing measures. “[O]ther policies — travel restrictions, large-assembly limits, centralized quarantine, mask requirements, and school cancellations — do work,” he stresses, with special emphasis on the effectiveness of school closings to limit contagion. (Are we willing and able to provide centralized quarantine?) His anti-lockdown position is *not* a claim that the threat from the virus is overstated or that aggressive action isn’t needed. It is. But indefinite stay-at-home orders may be a bridge too far, a draconian measure that simply doesn’t pay off in terms of saving lives.

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