As shown in [ 22] for "Royal Road fitness landscape", if the error rate is beyond the error-threshold of the fittest, the population can still be localized in sequence space albeit at a lower fitness level, for which a new error-threshold again exists.
Beyond the error threshold, the population is delocalized over the whole sequence space.
When either the amplification factor or the robustness of some mutant Hamming classes is changed, the population distribution beyond the error threshold departs from the uniform distribution.
In any case, neither the delocalization beyond the error threshold nor the loss of the master sequence can be associated to a critical loss of information.
We will now study how the population distribution beyond the error threshold changes when the robustness of some Hamming classes is modified.
In light of the results and interpretations presented in this paper, we think that is quite inaccurate to speak of any kind of crisis beyond the error threshold.
Beyond the error threshold, a quasispecies is delocalized over the sequence space in such a way as to produce a uniform population distribution.
Moreover, beyond the error thresholds, changing the quality factor of some sequences modifies the population distribution at the error catastrophe, displacing it towards the flatter regions of the mutant phenotype.
On the other hand, the population distribution at error catastrophe is displaced to greater or lesser Hamming distances, so the average Hamming distance beyond the error threshold increases with respect to the case q1 = q2.
Therefore the selection coefficient is positive beyond the error threshold, which means that beyond that value of q the mutant phenotype has a selective advantage over the master phenotype.
That we will be unable to defeat viruses by learning to push them beyond the error catastrophe threshold.
