Evidence map›Paper›PMID 33476332›Full record

ArticlePLoS computational biology2021

Post-lockdown abatement of COVID-19 by fast periodic switching.

Michelangelo Bin, Peter Y K Cheung, Emanuele Crisostomi, Pietro Ferraro, Hugo Lhachemi, Roderick Murray-Smith, Connor Myant, Thomas Parisini, Robert Shorten, Sebastian Stein and 1 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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  13. Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies.medRxiv : the preprint server for health sciences · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Michelangelo BinDepartment of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0003-2645-1064
Peter Y K CheungDyson School of Design Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0002-8236-1816
Emanuele CrisostomiDepartment of Energy, Systems, Territory and Constructions Engineering, University of Pisa, Pisa, Italy.ORCID 0000-0002-7973-6357
Pietro FerraroDyson School of Design Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0002-9195-3880
Hugo LhachemiL2S, CentraleSupélec, Gif-sur-Yvette, France.ORCID 0000-0002-2782-4208
Roderick Murray-SmithSchool of Computing Science, University of Glasgow, Glasgow, Scotland.ORCID 0000-0003-4228-7962
Connor MyantDyson School of Design Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0003-4705-4009
Thomas ParisiniDepartment of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0001-5396-9665
Robert ShortenDyson School of Design Engineering, Imperial College London, London, United Kingdom.ORCID 0000-0002-9239-2499
Sebastian SteinSchool of Computing Science, University of Glasgow, Glasgow, Scotland.ORCID 0000-0003-1828-4008
Lewi StoneMathematics, School of Science, RMIT University, Melbourne, Australia.ORCID 0000-0002-6465-579X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Models, StatisticalCommunicable Disease ControlComputational BiologyCOVID-19HumansSARS-CoV-2Software

Identifiers

PMID33476332
PMCPMC7861565

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.