COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care: computer simulation study

Richard M Wood; Christopher J McWilliams; Matthew J Thomas; Christopher P Bourdeaux; Christos Vasilakis

The COVID-19 hospital admission process is modelled as a multi-channel queuing system operating with loss. That is, patients requiring hospitalisation are rejected if there is no available service channel (bed). In Kendall's notation (Kendall, 1953) this is an ( ) | | | queuing system: that is, in turn, a time-inhomogeneous Poisson arrivals process representing the epidemic curve for cases requiring hospitalisation; a general service distribution approximating patient length of stay in hospital; C service channels; and a total system capacity of C patients, i.e. no space for waiting. For rejected admissions (lost arrivals), death occurs with probability and survival with probability 1 − . The model can be applied in the context of general acute beds or intensive care beds, assuming the parameters are calibrated accordingly. Implementation of this model is through the iterative three-phased method of discrete event simulation (Pidd, 1998) . In the case of this study, the types of simulation event consist of: a. Arrival of patient requiring hospital admission (unconditional event) b. Patient admitted (conditional event) c. Patient discharged (unconditional event) d. Patient admission rejected and patient died (conditional event) e. Patient admission rejected and patient survived (conditional event)