The role of duration of infectiousness in SIR models
My question concerns the way that $d$ enters the SIR model, because I
  find it not so plausible:
  
  
  to consider all persons that are infected today and take a fraction $ν$ of them that will have recovered tomorrow.
  


Well, it is in fact not very 'realistic' as you point out, but in the assumptions of the model, we see that the population has no structure (it is well-mixed, constant) and there are no birth-death events. So, in this case, it is not so problematic to take $v$ as a constant across the entire simulation, because what you are trying to calculate is the rate at which the three sub-fractions of $N$ ($s$, $i$, and $r$) change, not really which individuals are moving from one class to another (which you cannot really know anyways, if you talk about fractions of $N$). 


  Wouldn't it be much more plausible
  
  
  to consider all persons that became infected $d$ days ago and let    these be recovered tomorrow?
  


So, considering my previous comment, it would not make much sense really to take a time-delay form on $d$, because you cannot really know which individuals got infected at any given point, you can only talk about fractions of $N$ (there is no population structure, as they say in the model formulation). So, the fact that your formulation seems to have a slower dynamics might not be very informative, because what you did is simply applying $d$ to a fraction-of-the-fraction of the population classes, so it makes sense mathematically that it runs slower, but as per the model formulation it does not make much sense, unless you have population structure defined from the beginning (which in this case is not), and unless you can explicitely know individual-per individual class transitions. In fact, I believe that taking the fraction-of-the-fraction would lead to an artifactual 'undercounting' of these individuals that actually needed to be in the $i$ class (and overcounting of the other classes).