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

Managing a co-ordinated response to pandemics such as COVID-19 is critical. Unchecked, with a basic reproduction rate (R0) estimated at between 2 and 3 (Ferguson et al, 2020 and an estimated 4.4% of those infected requiring hospitalisation (Ferguson et al, 2020) , the virus can propagate rapidly through a population , leading to peaks in demand for hospital care which are simply not possible to match with existing or otherwise available capacity (Ferguson et al, 2020 , Instituto Superiore Di Sanita, 2020 . If, at such times, patients are unable to access the bedded care required then otherwise-avoidable death is likely to result (White & Lo, 2020) . The likelihood of this is particularly heightened when intensive care beds are required, since the necessary invasive ventilation and organ support cannot readily or safely be delivered in other settings (Ñamendys-Silva, 2020) . Early case fatality rates from Wuhan would not be expected to appreciate these capacitydependent deaths (i.e. deaths that can be attributed to a patient unable to access the care they need due to lack of available capacity), since drastic efforts were taken by authorities to avoid health services becoming overwhelmed, in enforcing restrictions on movement and rapidly upscaling capacity through the building of two new hospitals (Khan et al, 2020) . Without improved treatment options, there is little that can be done to reduce COVID-19 deaths occurring when the patient has otherwise been cared for in the most appropriate hospital setting, and so planners should focus on keeping to a minimum the capacity-dependent deaths that are within their influence. That is, efforts should be made to ensure the right level of care is available to patients at the right time.