Evidence map›Paper›PMID 34437531›Full record

ArticlePLoS computational biology2021

Mitigating COVID-19 outbreaks in workplaces and schools by hybrid telecommuting.

Simon Mauras, Vincent Cohen-Addad, Guillaume Duboc, Max Dupré la Tour, Paolo Frasca, Claire Mathieu, Lulla Opatowski, Laurent Viennot

Open access · goldAbstract 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 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.5field-weighted citation impact, top 18% of its field
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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
    Pooled it
  2. Measures implemented in the school setting to contain the COVID-19 pandemicThe Cochrane database of systematic reviews · 2022
    Pooled it
  3. Article
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  7. Real-time updating of dynamic social networks for COVID-19 vaccination strategies.Journal of ambient intelligence and humanized computing · 2023
    Article
  8. Article
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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

8 authors at 5 institutions in 1 country.

Simon MaurasUniversité de Paris, CNRS, IRIF, Paris, France.ORCID 0000-0003-4080-3118
Vincent Cohen-AddadSorbonne Universite, UPMC Univ Paris 06, CNRS, LIP6, Paris, France.
Guillaume DubocDépartement Informatique, ENS de Lyon, Lyon, France.ORCID 0000-0002-6795-9545
Max Dupré la TourUniversité de Paris, CNRS, IRIF, Paris, France.
Paolo FrascaUniv. Grenoble Alpes, CNRS, Inria, Grenoble INP, Gipsa-lab, Grenoble, France.ORCID 0000-0003-0962-3119
Claire MathieuUniversité de Paris, CNRS, IRIF, Paris, France.ORCID 0000-0002-0517-112X
Lulla OpatowskiUniversité Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France.ORCID 0000-0001-8348-700X
Laurent ViennotINRIA, IRIF, Université de Paris, Paris, France.ORCID 0000-0003-3657-6979
Centre National de la Recherche Scientifique · FRÉcole Normale Supérieure de Lyon · FRInstitut national de recherche en sciences et technologies du numérique · FRInstitut polytechnique de Grenoble · FRUniversité Paris-Sud · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 epidemic has forced most countries to impose contact-limiting restrictions at workplaces, universities, schools, and more broadly in our societies. Yet, the effectiveness of these unprecedented interventions in containing the virus spread remain largely unquantified. Here, we develop a simulation study to analyze COVID-19 outbreaks on three real-life contact networks stemming from a workplace, a primary school and a high school in France. Our study provides a fine-grained analysis of the impact of contact-limiting strategies at workplaces, schools and high schools, including: (1) Rotating strategies, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off strategies, where the whole group alternates periods of normal work interactions with complete telecommuting. We model epidemics spread in these different setups using a stochastic discrete-time agent-based transmission model that includes the coronavirus most salient features: super-spreaders, infectious asymptomatic individuals, and pre-symptomatic infectious periods. Our study yields clear results: the ranking of the strategies, based on their ability to mitigate epidemic propagation in the network from a first index case, is the same for all network topologies (workplace, primary school and high school). Namely, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day. Moreover, our results show that below a certain threshold for the original local reproduction number [Formula: see text] within the network (< 1.52 for primary schools, < 1.30 for the workplace, < 1.38 for the high school, and < 1.55 for the random graph), all four strategies efficiently control outbreak by decreasing effective local reproduction number to [Formula: see text] < 1. These results can provide guidance for public health decisions related to telecommuting.

Indexed as

SARS-CoV-2TeleworkingBasic Reproduction NumberComputational BiologyComputer SimulationContact TracingCOVID-19Disease OutbreaksEducation, DistanceFranceHumansModels, BiologicalPersonnel Staffing and SchedulingPublic HealthSchoolsStochastic Processes

Identifiers

PMID34437531
PMCPMC8389398
OpenAlexW3195766053

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.