Tildesley Michael J, Vassall Anna, Riley Steven, Jit Mark, Sandmann Frank, Hill Edward M, Thompson Robin N, Atkins Benjamin D, Edmunds John, Dyson Louise, Keeling Matt J
The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.
Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London WC1H 9SH, UK.
R Soc Open Sci. 2022 Aug 10;9(8):211746. doi: 10.1098/rsos.211746. eCollection 2022 Aug.
Even with good progress on vaccination, SARS-CoV-2 infections in the UK may continue to impose a high burden of disease and therefore pose substantial challenges for health policy decision makers. Stringent government-mandated physical distancing measures (lockdown) have been demonstrated to be epidemiologically effective, but can have both positive and negative economic consequences. The duration and frequency of any intervention policy could, in theory, be optimized to maximize economic benefits while achieving substantial reductions in disease. Here, we use a pre-existing SARS-CoV-2 transmission model to assess the health and economic implications of different strengths of control through time in order to identify optimal approaches to non-pharmaceutical intervention stringency in the UK, considering the role of vaccination in reducing the need for future physical distancing measures. The model is calibrated to the COVID-19 epidemic in England and we carry out retrospective analysis of the optimal timing of precautionary breaks in 2020 and the optimal relaxation policy from the January 2021 lockdown, considering the willingness to pay (WTP) for health improvement. We find that the precise timing and intensity of interventions is highly dependent upon the objective of control. As intervention measures are relaxed, we predict a resurgence in cases, but the optimal intervention policy can be established dependent upon the WTP per quality adjusted life year loss avoided. Our results show that establishing an optimal level of control can result in a reduction in net monetary loss of billions of pounds, dependent upon the precise WTP value. It is vital, as the UK emerges from lockdown, but continues to face an on-going pandemic, to accurately establish the overall health and economic costs when making policy decisions. We demonstrate how some of these can be quantified, employing mechanistic infectious disease transmission models to establish optimal levels of control for the ongoing COVID-19 pandemic.
即使在疫苗接种方面取得了良好进展，英国的新冠病毒感染可能仍会继续带来沉重的疾病负担，因此给卫生政策决策者带来重大挑战。政府强制实施的严格物理距离措施（封锁）已被证明在流行病学上是有效的，但可能会产生正负两方面的经济后果。从理论上讲，任何干预政策的持续时间和频率都可以进行优化，以在大幅减少疾病的同时实现经济效益最大化。在此，我们使用一个现有的新冠病毒传播模型来评估不同控制强度随时间推移对健康和经济的影响，以便确定英国非药物干预严格程度的最佳方法，同时考虑疫苗接种在减少未来物理距离措施需求方面的作用。该模型已根据英格兰的新冠疫情进行校准，我们对2020年预防性解除封锁的最佳时机以及2021年1月封锁后的最佳放松政策进行了回顾性分析，同时考虑了为改善健康状况的支付意愿（WTP）。我们发现，干预措施的精确时机和强度在很大程度上取决于控制目标。随着干预措施的放松，我们预计病例会再次出现，但可以根据避免的每质量调整生命年损失的支付意愿来确定最佳干预政策。我们的结果表明，根据精确的支付意愿值，建立最佳控制水平可使净货币损失减少数十亿英镑。在英国解除封锁但仍面临持续疫情之际，在制定政策决策时准确确定总体健康和经济成本至关重要。我们展示了如何利用机械传染病传播模型来量化其中一些成本，从而为正在进行的新冠疫情确定最佳控制水平。
