Regional Maximum Hospital Capacity Estimation for COVID-19 Pandemic Patient Care in Surge Through Simulation
Estimating the capacity of a region to serve pandemic patients in need of hospital services is crucial to regional preparedness for pandemic surge conditions. This paper explores the use of techniques of stochastic discrete event simulation for estimating the maximum number of pandemic patients with intensive care and/or in-patient, isolation requirements that can be served by a consortium of hospitals in a region before requesting external resources. Estimates from the model provide an upper bound on the number of patients that can be treated if all hospital resources are re-allocated for pandemic care. The modeling approach is demonstrated on a system of five hospitals each replicating basic elements (e.g. number of beds) of the five hospitals in the Johns Hopkins Hospital System in the Baltimore-Washington, D.C. Metropolitan area under settings relevant to the COVID-19 pandemic.