4 ms·
[edited to add newer doc] The UK NERVTAG had other measures of transmissability that got them to the conclusion it did have higher transmissability; https://kh
by trebligdivad 6y ago
[edited to add newer doc]
The UK NERVTAG had other measures of transmissability that got them to the conclusion it did have higher transmissability;
https://khub.net/documents/135939561/338928724/SARS-CoV-2+variant+under+investigation%2C+meeting+minutes.pdf/962e866b-161f-2fd5-1030-32b6ab467896?t=1608470511452 https://khub.net/documents/135939561/338928724/SARS-CoV-2+va...
and have a newer one where they're more confident:
https://app.box.com/s/3lkcbxepqixkg4mv640dpvvg978ixjtf/file/756964987830 https://app.box.com/s/3lkcbxepqixkg4mv640dpvvg978ixjtf/file/...
- sigil 6y agoThey discuss these in that TWiV episode as well!
- randomsearch 6y agoWorth noting that you can’t test a hypothesis from the data you used to formulate it. I haven’t seen any work on this variant that doesn’t fall into that trap.
- disgruntledphd2 6y agoI would really, really hope that they are using a good cross-validation strategy (as they'll definitely need it).
- randomsearch 6y agocross validation won't save you in this situation. it's a subtle point, but you can't say "omg this strain is increasing and it must therefore be more contagious" and then show that it is more contagious by showing it is increasing... this is counter-intuitive even to most scientists, in my experience. I remember when I learnt this during my PhD. I suspect many people high up in academia don't understand this point.
- randomsearch 6y agoan observation that may help: as your stats at time t+1 are dependent on stats at time t, you cannot separate your validation set from the set you used to perform exploratory data analysis - they are highly interdependent.