Author: Richard M Wood; Christopher J McWilliams; Matthew J Thomas; Christopher P Bourdeaux; Christos Vasilakis
Title: COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care: computer simulation study Document date: 2020_4_6
ID: e79k4q76_5
Snippet: There has been much interest in the quantitative and mathematical modelling of COVID-19 for purposes of epidemiological forecasting (Ferguson et al, 2020 , Kucharski, 2020 , Roosa et al, 2020 , risk prediction (Vihinen, 2020) , and health system vulnerability (Gilbert et al, 2020) . However, to the best of the authors' knowledge there has been no explicit modelling of capacity-dependent deaths based on predicted demand. While Ferguson et al (2020.....
Document: There has been much interest in the quantitative and mathematical modelling of COVID-19 for purposes of epidemiological forecasting (Ferguson et al, 2020 , Kucharski, 2020 , Roosa et al, 2020 , risk prediction (Vihinen, 2020) , and health system vulnerability (Gilbert et al, 2020) . However, to the best of the authors' knowledge there has been no explicit modelling of capacity-dependent deaths based on predicted demand. While Ferguson et al (2020) provide a detailed model of demand and the resulting deaths under various mitigation strategies, their work assumes a fixed mortality rate that is not dependent on the available capacity of the healthcare system. The modelling in this paper addresses this limitation by predicting the excess mortality resulting from demand exceeding intensive care capacity under several mitigation scenarios.
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