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

As with any modelling study, a number of simplifying assumptions were made. There is the assumption that death occurs immediately if a bed in the required setting is not available. Realistically death will not be immediate (World Health Organization, 2020 ), yet at this early stage of the pandemic there exist no reliable data to capture this parameter in the model in a meaningful way. This has no effect on the ultimate number of deaths estimated, but will affect their specific timing and the thus, the peak daily number. This should therefore be considered if seeking validation against actual number deaths over time (i.e. it should be expected that there will be a lag). It should also be acknowledged that the model does not mechanistically capture delays to discharge or transfer, which are commonplace in hospital patient flow (Landeiro et al, 2019 ). An example for the application considered here would be the inability to discharge a patient from intensive care due to the lack of an available acute bed. While this has not been modelled (this would be possible at the cost of additional complexity, see Wood & Murch, 2019) , the effects can be understood by adjusting the length of stay distribution used within the simulation according to estimated or hypothetical delay times. Finally, it is assumed in this study that all intensive care beds are available for newly-arriving COVID-19 patients. While elective procedures requiring post-operative intensive care have been cancelled, there remains other sources of non-elective non-COVID-19 intensive care demand. Estimations of this, once the effect of societal isolation becomes appreciable (e.g. any reduced road traffic accidents, alcohol-related injuries), can be incorporated within the model parameter for capacity simply by deducting the average beds occupied by such patients.