In response to “What does 70% more infectious mean?”, I found this slide deck, with the relevant part on slide 17, which I will reproduce below (N501Y is the name of the relevant mutation):
For example, under the additive assumption, an area with an Rt of 0.8 without the new variant would have an Rt of 1.19 [1.04-1.35] if only N501Y was present
...
For example, under the multiplicative assumption assumption, an area with an Rt of 0.8 without the new variant would have an Rt of 1.18 [1.02-1.40] if only N501Y was present
TL;DR: it appears “up to 70% more infectious” is based on observed data, so that if you previously observed an Rt of 0.8, you should expect to observe a new Rt of somewhere between 1.0 and 1.4 with the new strain, ceteris paribus.
EDIT: I previously included this bottom section, which MichaelLowe points out doesn’t make sense and I also realized is wrong; see comment thread below.
I found the Wikipedia article on the new strain to have the most clear explanation of the calculation, that this is the result of the observed doubling time being reduced from 6.5 days to 6.4 days; I’ll quote the relevant bit:
Data seen by NERVTAG included a genomic analysis showed that the relative prevalence odds of this variant doubled every 6.4 days. With a presumed generational interval of 6.5 days, this resulted in a selection coefficient of
ln(2)⋅6.5/6.4=+0.70(+70%)
They also found a correlation between higher reproduction rate and detection of lineage B.1.1.7. While there may be other explanations, it is likely that this variant is more transmissible; laboratory studies will clarify this.
Thanks for the explanation. I do not understand the formula however. As I read your explanation, if both strains had the exact same doubling time of 6.5 days, one strain would still be ln(2) *6.5/6.5 = 0.69 more infectious than the other one, so I must be misunderstanding.
We are trying to solve for the selection coefficient, which I interpret as “how much of an advantage does this strain have over the previous strain”.
It is here that I realize I don’t know how the Wikipedia editor found the 6.4 number, I couldn’t find it anywhere in the citation. The calculation they perform with the log odds comes from the YouTube video, which in the cited segment is actually talking about a different lineage, B.1.177 (this is different from B.1.1.7 ! Did the editor confuse these two?)
Logistic growth model indicates VUI grows +71% (95%CI: 67%-75%) faster per generation (6.5 days)
Limitations: Sample frequency is noisy & overdispersed in ways not captured by this model
So it turns out that this log odds calculation is not relevant to how we get this “70%” number, it was actually simply interpolated from the data by performing a logistic regression.
EDIT: I have now edited Wikipedia to remove the original calculation using the log odds.
In response to “What does 70% more infectious mean?”, I found this slide deck, with the relevant part on slide 17, which I will reproduce below (N501Y is the name of the relevant mutation):
TL;DR: it appears “up to 70% more infectious” is based on observed data, so that if you previously observed an Rt of 0.8, you should expect to observe a new Rt of somewhere between 1.0 and 1.4 with the new strain, ceteris paribus.
EDIT: I previously included this bottom section, which MichaelLowe points out doesn’t make sense and I also realized is wrong; see comment thread below.
I found theWikipedia articleon the new strain to have the most clear explanation of the calculation, that this is the result of the observed doubling time being reduced from 6.5 days to 6.4 days; I’ll quote the relevant bit:Data seen by NERVTAG included a genomic analysis showed that the relative prevalence odds of this variant doubled every 6.4 days. With a presumed generational interval of 6.5 days, this resulted in a selection coefficient ofln(2)⋅6.5/6.4=+0.70 (+70%)
They also found a correlation between higher reproduction rate and detection of lineage B.1.1.7. While there may be other explanations, it is likely that this variant is more transmissible; laboratory studies will clarify this.Thanks for the explanation. I do not understand the formula however. As I read your explanation, if both strains had the exact same doubling time of 6.5 days, one strain would still be ln(2) *6.5/6.5 = 0.69 more infectious than the other one, so I must be misunderstanding.
Good catch! I watched the section of the YouTube video linked by the citation on Wikipedia, and the original formula they give is this:
ddtlog(odds_ratio)=selection_coefficientgeneration_time
We are trying to solve for the selection coefficient, which I interpret as “how much of an advantage does this strain have over the previous strain”.
It is here that I realize I don’t know how the Wikipedia editor found the 6.4 number, I couldn’t find it anywhere in the citation. The calculation they perform with the log odds comes from the YouTube video, which in the cited segment is actually talking about a different lineage, B.1.177 (this is different from B.1.1.7 ! Did the editor confuse these two?)
Reading the slide deck more closely, it says:
So it turns out that this log odds calculation is not relevant to how we get this “70%” number, it was actually simply interpolated from the data by performing a logistic regression.
EDIT: I have now edited Wikipedia to remove the original calculation using the log odds.