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

Regarding future use of the tool and as the COVID-19 pandemic evolves and more empirical data become available, it will be possible to derive more accurate assessments of hospital length of stay and projected cases requiring hospitalisation. Given efforts to promote user-friendliness of the tool (by way of execution through a simple purpose-built function in R), any such changes to input parameter values can be readily addressed by running a small number of additional simulation runs (thus helping to ensure results remain in line with the latest data and forecasts). For the intensive care application considered here, the tool may also be used at a later stage of the pandemic in order to understand when elective cardiac surgery may safely resume following any projected reduction in COVID-19 intensive care occupancy. Further development of the model may also unlock the ability to assess the implication of different intensive care admission criteria on aggregate measures of mortality (as suggested in Utley et al, 2011 and White & Lo, 2020) . In such case the model may be used to understand the effects of rejecting intensive care admissions from patients of cohorts known to have negligible survival likelihood, in the interests of maintaining available beds for those known to have more favourable chances.