Post-lockdown abatement of COVID-19 by fast periodic switching.
Post-lockdown abatement of COVID-19 by fast periodic switching.
复制标题
通过快速周期性切换减少Covid-19。
DOI：
10.1371/journal.pcbi.1008604
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发表时间：
2021-01
影响因子：
4.3
通讯作者：
Stone L
中科院分区：
文献类型：
--
作者：
Bin M;Cheung PYK;Crisostomi E;Ferraro P;Lhachemi H;Murray-Smith R;Myant C;Parisini T;Shorten R;Stein S;Stone L
COVID-19 缓解策略存在风险和不确定性，可能导致感染浪潮反复出现。作为基于严格数学证据的概念证明，我们表明，周期性、高频率的封锁和解除封锁有效地减轻了第二波影响，同时允许经济活动继续进行，尽管有所减少。周期性赋予（i）可预测性，这对于经济可持续性至关重要，以及（ii）稳健性，因为短期内的不确定测量不会激活锁定期。反过来，这种快速转换政策虽然不能消除病毒，但随着时间的推移是可持续的，它可以减轻感染，直到疫苗或治疗方法出现，同时减轻与长期封锁相关的社会成本。通常，该政策的形式可能是每周工作 1 天，然后每周锁定 6 天（或者可能工作 2 天，休息 5 天），并且可以根据在较长时间范围内过滤的测量结果以缓慢的速度进行修改。我们的结果强调了高频转换干预措施在缓解封锁后的潜在功效。所有代码均可在 Github 上获取：https://github.com/V4p1d/FPSP_Covid19。还开发了一个软件工具，以便感兴趣的各方可以探索概念验证系统。为什么？由于许多国家（例如西班牙、法国、英国、意大利、以色列等）出现了新的继发性病毒浪潮，而且其中一些国家正在努力重新引入全面封锁措施，因此在疫苗尚未上市的情况下设计封锁后缓解政策已迫在眉睫。我们做什么并发现什么？我们提出了基于控制理论的有效且可实现的方法，以驯服 COVID-19 在充分混合的人群中的复杂行为。我们通过定期快速间歇性锁定间隔的政策来实现这一目标。我们阐述了我们的方法如何为设计全面封锁政策中的 COVID-19 退出策略提供了一个全新的视角。我们的理论结果也非常通用，适用于广泛的流行病学模型。这些发现意味着什么？与许多其他拟议的减排战略不同，这些战略具有可能导致多波感染的风险和不确定性，我们证明我们提出的政策有潜力抑制病毒的爆发，同时允许经济活动持续进行。这些政策虽然具有实际意义，但却建立在严格的理论结果之上，据我们所知，这些理论结果在数学流行病学领域是全新的。使用详细的流行病模型进行了广泛的验证，该模型根据来自意大利的真实 COVID-19 数据进行了验证，并于最近发表在《自然医学》上。
COVID-19 abatement strategies have risks and uncertainties which could lead to repeating waves of infection. We show—as proof of concept grounded on rigorous mathematical evidence—that periodic, high-frequency alternation of into, and out-of, lockdown effectively mitigates second-wave effects, while allowing continued, albeit reduced, economic activity. Periodicity confers (i) predictability, which is essential for economic sustainability, and (ii) robustness, since lockdown periods are not activated by uncertain measurements over short time scales. In turn—while not eliminating the virus—this fast switching policy is sustainable over time, and it mitigates the infection until a vaccine or treatment becomes available, while alleviating the social costs associated with long lockdowns. Typically, the policy might be in the form of 1-day of work followed by 6-days of lockdown every week (or perhaps 2 days working, 5 days off) and it can be modified at a slow-rate based on measurements filtered over longer time scales. Our results highlight the potential efficacy of high frequency switching interventions in post lockdown mitigation. All code is available on Github at https://github.com/V4p1d/FPSP_Covid19. A software tool has also been developed so that interested parties can explore the proof-of-concept system. Why? The design of post-lockdown mitigation policies while vaccines are still not available is pressing now as new secondary waves of the virus have emerged in many countries (for example, in Spain, France, UK, Italy, Israel, and others), and as several of these countries grapple with the reintroduction of full lockdown measures. What do we do and find? We propose efficacious and realisable methods based on control theory to tame the complex behaviour of COVID-19 in well mixed populations. We achieve this through a policy of fast intermittent lockdown intervals with regular period. We illustrate how our approach offers a fundamentally new perspective on ways to design COVID-19 exit strategies from policies of total lockdown. Our theoretical results are also very general and apply to a wide range of epidemiological models. What do these findings mean? Unlike many other proposed abatement strategies, which have risks and uncertainties possibly leading to multiple waves of infection, we demonstrate that our proposed policies have the potential to suppress the virus outbreak, while at the same time allowing continued economic activity. These policies, while of practical significance, are built on rigorous theoretical results, which are to the best of our knowledge, new in mathematical epidemiology. An extensive validation is carried out using a detailed epidemic model validated on real COVID-19 data from Italy and published very recently in Nature Medicine.
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影响因子：
16.6
作者：
Della Rossa F;Salzano D;Di Meglio A;De Lellis F;Coraggio M;Calabrese C;Guarino A;Cardona-Rivera R;De Lellis P;Liuzza D;Lo Iudice F;Russo G;di Bernardo M
通讯作者：
di Bernardo M
影响因子：
3
作者：
Casella, Francesco
通讯作者：
Casella, Francesco
影响因子：
56.9
作者：
Kissler, Stephen M.;Tedijanto, Christine;Lipsitch, Marc
通讯作者：
Lipsitch, Marc
影响因子：
4
作者：
Keeling, MJ;Rohani, P;Grenfell, BT
通讯作者：
Grenfell, BT
影响因子：
9.3
作者：
Jarvis, Christopher I.;Van Zandvoort, Kevin;Edmunds, W. John
通讯作者：
Edmunds, W. John