Bristol Medical School, University of Bristol, 5 Tyndall Avenue, Bristol, BS8 1UD, UK.
Modelling and Analytics, UK National Health Service (BNSSG CCG), 360 Bristol, Marlborough Street, BS3 1NX, UK.
Int J Qual Health Care. 2022 May 13;34(2). doi: 10.1093/intqhc/mzac031.
Managing high levels of acute COVID-19 bed occupancy can affect the quality of care provided to both affected patients and those requiring other hospital services. Mass vaccination has offered a route to reduce societal restrictions while protecting hospitals from being overwhelmed. Yet, early in the mass vaccination effort, the possible impact on future bed pressures remained subject to considerable uncertainty.
The aim of this study was to model the effect of vaccination on projections of acute and intensive care bed demand within a 1 million resident healthcare system located in South West England.
An age-structured epidemiological model of the susceptible-exposed-infectious-recovered type was fitted to local data up to the time of the study, in early March 2021. Model parameters and vaccination scenarios were calibrated through a system-wide multidisciplinary working group, comprising public health intelligence specialists, healthcare planners, epidemiologists and academics. Scenarios assumed incremental relaxations to societal restrictions according to the envisaged UK Government timeline, with all restrictions to be removed by 21 June 2021.
Achieving 95% vaccine uptake in adults by 31 July 2021 would not avert the third wave in autumn 2021 but would produce a median peak bed requirement ∼6% (IQR: 1-24%) of that experienced during the second wave (January 2021). A 2-month delay in vaccine rollout would lead to significantly higher peak bed occupancy, at 66% (11-146%) of that of the second wave. If only 75% uptake was achieved (the amount typically associated with vaccination campaigns), then the second wave peak for acute and intensive care beds would be exceeded by 4% and 19%, respectively, an amount which would seriously pressure hospital capacity.
Modelling influenced decision-making among senior managers in setting COVID-19 bed capacity levels, as well as highlighting the importance of public health in promoting high vaccine uptake among the population. Forecast accuracy has since been supported by actual data collected following the analysis, with observed peak bed occupancy falling comfortably within the inter-quartile range of modelled projections.
管理大量的急性 COVID-19 病床占用率可能会影响到受影响患者和需要其他医院服务的患者的护理质量。大规模疫苗接种为减轻社会限制同时保护医院免受不堪重负提供了一条途径。然而，在大规模疫苗接种的早期，对未来床位压力的可能影响仍然存在很大的不确定性。
本研究的目的是在位于英格兰西南部的一个拥有 100 万居民的医疗保健系统中，建立一个接种疫苗对急性和重症监护床位需求预测的模型。
根据当地数据，直到 2021 年 3 月初，我们拟合了一种易感性-暴露性-感染性-恢复性的年龄结构传染病模型。模型参数和接种方案是通过一个由公共卫生情报专家、医疗保健规划人员、流行病学家和学者组成的全系统多学科工作组进行校准的。根据英国政府的预期时间表，假设社会限制会逐步放宽，所有限制将在 2021 年 6 月 21 日之前解除。
到 2021 年 7 月 31 日，实现 95%的成年人疫苗接种率将无法避免 2021 年秋季的第三次浪潮，但会使 2021 年 1 月的第二次浪潮期间的中位高峰期床位需求降低 6%（IQR：1-24%）。如果疫苗推出延迟 2 个月，将会导致高峰期床位占用率显著升高，达到第二次浪潮的 66%（11-146%）。如果仅达到 75%的接种率（通常与疫苗接种活动相关），那么急性和重症监护床位的第二次浪潮高峰将分别超过 4%和 19%，这将严重影响医院的容量。
建模影响了高级管理人员在设定 COVID-19 床位容量水平方面的决策，同时也凸显了公共卫生在促进人群中高疫苗接种率方面的重要性。自分析以来，实际数据的收集一直支持着预测的准确性，实际观察到的高峰期床位占用率恰好落在模型预测的四分位区间内。
