Saturday, 23 January 2021

Time to ditch relative risk in media reports

The Winton Centre for Risk and Evidence Communication at the University of Cambridge has done some sterling work in developing guidelines for communicating risk to the general public. In a short video,  David Spiegelhalter explains how relative risk can be misleading when the baseline for a condition is not reported. For instance, he noted that many women stopped taking a contraceptive pill after hearing media reports that it was associated with a doubling in the rate of thrombo-embolism. In terms of absolute risk the increase sounds much less alarming, going from 1 in 7000 to 2 in 7000. 

One can understand how those who aren't scientifically trained can get this wrong. But we might hope that,  in a pandemic, where public understanding of risk is so crucial, particular care would be taken to be realistic without being alarmist. It was, therefore, depressing to see a report on Channel 4 news last night where two scientists clearly explained the evidence on Covid variants in terms of absolute risk, impeccably reflecting the Winton Centre's advice, only to have the reporters translate the numbers into relative risk. I have transcribed the relevant sections: 

0:44 Reporter: "The latest evidence from the government's advisers is that this new variant is more deadly. And this is what it means:"

Patrick Vallance: "If you took somebody in their sixties, a man in their sixties, the average risk is that for 1000 people who got infected, roughly ten would be expected to unfortunately die with the virus. With the new variant, with 1000 people infected, roughly 13 or 14 people might be expected to die." 

Reporter: "That’s a thirty to forty per cent increase in mortality." 

5:15 Reporter (Krishnan Guru-Murthy): "But this is a high percent of increase, isn't it. Thirty to forty percent increase of mortality, on a relatively small number." 

Neil Ferguson: "Yes. For a 60-year-old at the current time, there's about a one in a hundred risk of dying. So that means 10 in 1000 people who get the infection are likely to die, despite improvements in treatment. And this new variant might take that up to 13 or 14 in a 1000." 

The reporters are likely to stoke anxiety when they translate clear communication by the scientists into something that sounds a lot more scary. I hope this is not their intention: Channel 4 is one of the few news outlets that I regularly watch and in general I find it well-researched and informative. I would urge the reporters to watch the Winton Centre video, which in less than 5 minutes makes a clear, compelling case for dropping relative risk altogether in media reports. 

 

This blogpost has been corrected to remove the name of Anja Popp as first reporter. She confirmed was not in this segment.  My apologies.

3 comments:

  1. There are occasions where the opposite is true. Some have argued that the vaccine efficacy rate, VER, (see https://errorstatistics.com/2021/01/17/s-senn-beta-testing-the-pfizer-biontech-statistical-analysis-of-their-covid-19-vaccine-trial-guest-post/ for an explanation) should be expressed in terms of absolute risk reduction and that when you do this, the values are unimpressive. The VER is not a great measure, in my opinion but it is far better than risk reduction for discussing vaccines. The point is that it is plausible that the VER, which was measured at a time when background infection rates were low would be pretty similar for different background risks. This means that the risk reduction would be much more impressive when the pandemic was raging but that is precisely what we want the vaccines for. Thus, the VER should most definitely not be replaced by risk differences.

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  2. Thanks Dorothy and Stephen for this, I will be sharing the link with my students.

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  3. A somewhat stupid question but if we have an incidence rate of zero and it suddenly leaps to 1, what would be the more or less correct way to express this?

    Colloquially, I'd call it a 100% increase but mathematically that seems ridiculous.

    Thanks.

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