A hospital demand and capacity intervention approach for COVID-19

Van Yperen, James and Campillo-Funollet, Eduard and Inkpen, Rebecca and Memon, Anjum and Madzvamuse, Anotida (2023) A hospital demand and capacity intervention approach for COVID-19. PLoS One, 18 (5): e0283350. ISSN 1932-6203

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Abstract

The mathematical interpretation of interventions for the mitigation of epidemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of the number of infections to manage impact. Whilst these methods may work in theory, in order to implement effectively they may require information which is not likely to be available in the midst of an epidemic, or they may require impeccable data about infection levels in the community. In reality, testing and cases data can only be as good as the policy of implementation and the compliance of the individuals, which implies that accurately estimating the levels of infections becomes difficult or complicated from the data that is provided. In this paper, we demonstrate a different approach to the mathematical modelling of interventions, not based on optimality or cases, but based on demand and capacity of hospitals who have to deal with the epidemic on a day to day basis. In particular, we use data-driven modelling to calibrate a susceptible-exposed-infectious-recovered-died type model to infer parameters that depict the dynamics of the epidemic in several regions of the UK. We use the calibrated parameters for forecasting scenarios and understand, given a maximum capacity of hospital healthcare services, how the timing of interventions, severity of interventions, and conditions for the releasing of interventions affect the overall epidemic-picture. We provide an optimisation method to capture when, in terms of healthcare demand, an intervention should be put into place given a maximum capacity on the service. By using an equivalent agent-based approach, we demonstrate uncertainty quantification on the likelihood that capacity is not breached, by how much if it does, and the limit on demand that almost guarantees capacity is not breached.

Item Type:
Journal Article
Journal or Publication Title:
PLoS One
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1100/1100
Subjects:
?? research articleresearch and analysis methodsphysical sciencesmedicine and health sciencespeople and placescomputer and information sciencesgeneral agricultural and biological sciencesgeneral biochemistry,genetics and molecular biologygeneral medicineagri ??
ID Code:
193076
Deposited By:
Deposited On:
23 May 2023 12:25
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 12:02