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Why so? You think the two week gap has that much statistical power? That would only be over a short timespan.
I would've thought a stronger argument would be that the vaccination wears off after a few months. I'm happy with vaccines that protect for decades but not the annual flu shot. IMO the two shouldn't share the same word. It's like calling a Bradley or a BMP a 'tank'. They're like tanks in that they have turrets, tracks, guns and armour. But the role is different, real tanks have bigger guns, heavier armour are less mobile and don't transport infantry.
"Two weeks after the second shot" isn't a two week gap, it's a four week or more gap.
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How much fake efficacy can be created this way depends on both how many people are infected in the beginning and the current rate at which the disease is spreading. Running a toy SIR model of a 0% mortality disease with R0 1.14 (that's apparently the median estimate for wild-type Covid under Western lockdown) and 100 people, 10 of which are infected at the start, you end up with a total of 46 infected people after 10 weeks.
If you apply the accounting trick and only count infections starting after week 2, you instead get 29 total infections, so even a saline injected population would imply a vaccine efficacy of ~40% simply by counting this way. If R0 were 0.85 instead, you'd get 50% VE, if only 2 of 100 start out as infected it'd be 20%, if 10 people were already recovered at the start of the study you'd get 60% etc. pp. Point is: how much of an effect this can have depends a lot on the initial conditions of the population you're studying.
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