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 ability to use a mathematical or computer model to experiment with "what if" scenarios involving these levers is crucial to planners on the ground, in ensuring deaths over the course of the pandemic can be kept at a minimum. Public health authorities need to know what effect their policies on social distancing, home isolation and school closures (i.e. policies to reduce the effective R0) can have on decreasing or changing the shape over time of demand and, in turn, capacity-dependent deaths. Healthcare service planners and managers need to be cognisant of the likely benefits of their options around the flexing of bedded capacity, especially regarding the allocation between acute and intensive care beds (where the substantial efforts involved in increasing the latter must be well justified). With an appropriate model and accompanying software tool, the effect of these scenarios can be projected and used to make better informed strategic decisions when planning the response to a COVID-19 pandemic.