I agree, but understanding probability distributions is actually key to this simulation that they've performed. The results would differ, greatly, by running it with a uniform vs normal vs binomial distribution, or by tuning their parameters.
So the number of deaths in a hospital is just
sum([random()<deathRate for i in range(numPeople)])
In the code above the random number is uniform(0,1), the standard random number in most languages. So each individual death is Bernouilli, although you don't need to know the word Bernouilli. Then this leads to a binomial distribution for a hospital as a whole.
But the binomial assumption doesn't need to be known or explicitly built into the model. It's effectively an emergent property of the individual deaths.