Earlier quoted context omitted.
The conclusions from the first critical code review cited: All papers based on this code should be retracted immediately. Imperial’s modelling efforts should be reset with a new team that isn’t under Professor Ferguson, and which has a commitment to replicable results with published code from day one. On a personal level, I’d go further and suggest that all academic epidemiology be defunded. This sort of work is best…
That was a shitty code review. Seeding issues like the ones cited don't affect the results of a Monte Carlo simulation, and there are tests in the repo, just not automated ones. The section you quoted shows the reason for the review's sloppiness. The reviewer set out to find a way to justify their own beliefs instead of to actually read the code.
Doing a Monte Carlo simulation means you adjust the seeds to get different runs. It doesn't mean your program can read uninitialised memory or reuse variables that weren't reset to zero and still be correct.
Where are people getting this idea that you can just average away the results of out-of-bounds reads and race conditions?