The British variant of SARS-CoV-2 and the poverty of epidemiology

Summary

• B.1.1.7, a variant of SARS-CoV-2 that emerged in England last year and has been spreading rapidly everywhere since the beginning of the year, is claimed to be far more transmissible than the historical lineage. For instance, based on the early expansion of B.1.1.7 in France, Gaymard et al. (2021) found that it was between 50% and 70% more transmissible, which was used to recommend more stringent restrictions since if that were accurate a massive surge of incidence would be inevitable unless transmission were significantly reduced.

• However, this estimate is based on fitting a simple exponential growth model to 2 data points in January and is extremely sensitive to the assumptions made about the generation time distribution, about which I argue there is considerable uncertainty. When I replicate Gaymard et al.’s analysis but properly take into account this uncertainty by trying a wider range of possible assumptions about the generation time distribution, which I was able to do no thanks to them since not only did they not publish their code but they also didn’t reply when I asked them for it, I find that B.1.1.7 could be anywhere between 21% and 72% more transmissible, a much wider range than what is reported by Gaymard et al.

• If I fit the same type of model but use more recent data instead of relying only on the growth rate of B.1.1.7 in January, I find that B.1.1.7’s transmissibility advantage ranges from 16% to 42% depending on what assumptions I make about the generation time distribution, which is much lower than Gaymard et al.’s 50%-70% range. However, this conclusion is based on the assumption that B.1.1.7 has been growing exponentially in France since the beginning of the year, a view that is clearly falsified by the data even though some epidemiologists inexplicably continue to hold it.

• Most epidemiologists probably realize that, but argue that the explosion they predicted in January fail to materialize thanks to the decision to advance the curfew from 8pm to 6pm in January and the school holidays in February. So rather than assume a simple exponential growth model, I try to model the effect of government interventions and school holidays on transmission in a way similar to what the epidemiologists who advise the French government are doing, except that I use that model to estimate B.1.1.7’s transmissibility advantage instead of assuming it’s between 50% and 70% more transmissible. This approach leads to the conclusion that, depending on what assumptions we make about the generation time distribution, B.1.1.7’s transmissibility is somewhere between 22% and 53% more transmissible.

• I explain that, even if B.1.1.7’s transmissibility advantage had remained constant (which this approach implicitly assumes), this estimate would not be reliable because, as I argue elsewhere, this kind of model rests on strong and totally unrealistic mechanistic assumptions. So I also try an econometric approach to estimate B.1.1.7’s transmissibility advantage, which also assumes that it has remained constant, but is agnostic on the underlying mechanism. However, the estimates are even more all over the place than with the previous approach, with B.1.1.7’s transmissibility advantage ranging from -12% to 98% depending on what model I use and what assumptions I make about the generation time distribution.

• Thus, even if we assume, as epidemiologists systematically do (but rarely acknowledge explicitly), that B.1.1.7’s transmissibility advantage has remained constant, Gaymard et al.’s claim that it’s 50% to 70% more transmissible is completely unwarranted, since there is far more uncertainty than that. However, I show that B.1.1.7’s transmissibility advantage has not remained constant in France since the beginning of the year, but has rapidly fallen as this lineage rose in prevalence and I estimate that it’s now only 11% more transmissible than the historical lineage.

• Unfortunately, epidemiologists apparently couldn’t be bothered to check that B.1.1.7’s transmissibility advantage has remained constant, they just assumed it was and plugged Gaymard et al.’s 50% to 70% estimate into the models they use to make their projections, which unsurprisingly predicted that incidence would soon blow up like never before. Of course, this didn’t happen, but instead of admitting they were wrong and revising their assumption that B.1.1.7’s transmissibility advantage has remained constant, they just offered ad hoc rationalizations for why the projections didn’t come true even though they were right and continued to advocate for stringent restrictions.

The number of COVID-19 cases has recently started to increase again in several countries on both sides of the Atlantic. If you listen to epidemiologists in the media, the culprit is B.1.1.7, a variant of SARS-CoV-2 that first appeared in the UK and which they claim is far more transmissible than the historical lineage. Since it has rapidly expanded everywhere it’s been introduced, there is no doubt that B.1.1.7 is more transmissible or at least that it initially was. But how much more? Depending on the study, epidemiologists give various ranges of estimates, but B.1.1.7’s transmissibility advantage is always estimated to be very high. For instance, according to this study based on British data, this advantage is estimated to be somewhere between 43% and 90%. In this post, I will focus on Gaymard et al. (2021), another recent study based on French data that puts B.1.1.7’s transmissibility advantage between 50% and 70%, with a central estimate at 59%. Moreover, epidemiologists don’t merely claim that B.1.1.7 is far more transmissible than the historical lineage, they claim that this transmissibility advantage is constant.

They don’t just make those claims in scientific publications, but also in the media, where they often don’t show any caution about their estimates. For instance, after that French study was published, one of the co-authors, who also happens to sit on the scientific council that advises the French government on the pandemic, gave an interview to Le Monde, in which one would be hard pressed to find any trace of doubt about the validity of their estimates. It is thus unsurprising that journalists and commentators talk about the hypothesis that B.1.1.7 has a constant transmissibility advantage in that range as if this were established fact. However, not only is this hypothesis not established fact, but I think at this point it’s overwhelmingly unlikely to be true. Unfortunately, most epidemiologists don’t seem very interested in discussing the data that are hard to reconcile with that hypothesis, so in this post I will take a closer look at Gaymard et al. (2021) to explain how they concluded that B.1.1.7 was 50% to 70% more transmissible than the historical lineage and show that it’s not very serious.

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