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Comment by firesteelrain | Hacker News Reader

It’s still not as clear cut as patient in and gets bed. There was some tweaking that had to be done to triage patients better then determine who most likely needed a bed. At UF Hospitals, they used discrete event simulation to figure out how to streamline this process. Not sure how many others went through the same thing. Point is, hospitals share some of the blame too

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Discrete event simulations is used to get better utilization of a constrained resource. The fact that hospitals were using it just reinforces that ICU capacity was considered a serious constraint by policymakers. Discrete event simulation will give policy makers more confidence in capacity models but doesn’t improve patient outcomes or reduce treatment time.

Hospital protocols also improved over time to reduce the need for respirators and the disease moderated but there was no magic protocol that really reduced disease progression or duration. Out of my social circle there were anti-vaxers that contracted covid late in the pandemic and spent weeks in the hospital (four total, two deaths) even with late stage protocols.

It is not for constrained resources. You might be thinking of linear programming. It deals in constraints to achieve an objective. Discrete event simulation deals in queues.

In this case the queue was wait time for an ICU bed and the simulation allowed them to better model how events (infection, admission, resolution) would impact ICU wait times. This allowed policymakers to better understand the tipping point where ICU wait times went non-linear.

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