Mathematical Institute, University of Oxford, Woodstock Road, Oxford OX2 6GG, UK.
Christ Church, University of Oxford, St Aldates, Oxford OX1 1DP, UK.
Proc Biol Sci. 2020 Aug 12;287(1932):20201405. doi: 10.1098/rspb.2020.1405.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
全球范围内采取了高强度的非药物干预措施(封锁)组合来降低 SARS-CoV-2 的传播。许多政府已经开始实施放松限制的退出策略,同时试图控制病例激增的风险。数学模型在指导干预措施方面发挥了核心作用,但在持续传播的情况下设计最佳退出策略的挑战是前所未有的。在这里,我们报告了 2020 年 5 月 11 日至 15 日在艾萨克·牛顿研究所举行的“退出策略模型”研讨会的讨论情况。我们邀请了来自世界各地的为政府提供证据的不同领域的建模者,要求他们确定如果回答了哪些主要问题,将能够更准确地预测不同退出策略的效果。基于这些问题,我们提出了一个路线图,以促进开发可靠的模型来指导退出策略。该路线图需要科学界和政策制定者的全球合作,包括三个部分:(i)改善对关键流行病学参数的估计;(ii)了解人群中异质性的来源;(iii)关注数据收集的要求,特别是在中低收入国家。这将为平衡社会经济利益和公共卫生需求的退出策略规划提供重要信息。