Evidence map›Paper›PMID 33292919›Full record

ArticleEpidemiology and infection2020

Quarantine and the risk of COVID-19 importation.

J Arino, N Bajeux, S Portet, J Watmough

Abstract read
In one paragraph

Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Effect of Movement on the Early Phase of an Epidemic.Bulletin of mathematical biology · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Managing the risk of a COVID-19 outbreak from border arrivals.Journal of the Royal Society, Interface · 2021
    Article
  10. Article
  11. Article
  12. Article
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

4 authors.

J ArinoDepartment of Mathematics & Data Science NEXUS, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada.ORCID 0000-0001-6409-5027
N BajeuxDepartment of Mathematics, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada.
S PortetDepartment of Mathematics & Data Science NEXUS, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada.
J WatmoughDepartment of Mathematics & Statistics, University of New Brunswick, Fredericton, New BrunswickE3B 5A3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using a stochastic model, we assess the risk of importation-induced local transmission chains in locations seeing few or no local transmissions and evaluate the role of quarantine in the mitigation of this risk. We find that the rate of importations plays a critical role in determining the risk that case importations lead to local transmission chains, more so than local transmission characteristics, i.e. strength of social distancing measures (NPI). The latter influences the severity of the outbreaks when they do take place. Quarantine after arrival in a location is an efficacious way to reduce the rate of importations. Locations that see no or low-level local transmission should ensure that the rate of importations remains low. A high level of compliance with post-arrival quarantine followed by testing achieves this objective with less of an impact than travel restrictions or bans.

Indexed as

QuarantineComputer SimulationCOVID-19Markov ChainsModels, BiologicalPhysical DistancingPoisson DistributionProbabilityRisk FactorsStochastic ProcessesTravelTreatment Adherence and ComplianceCOVID-19importation riskmathematical modellingquarantine

Identifiers

PMID33292919
PMCPMC7783093

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.