Evidence map›Paper›PMID 33292095›Full record

ArticleJournal of the Royal Society, Interface2020

Disease control across urban-rural gradients.

Konstans Wells, Miguel Lurgi, Brendan Collins, Biagio Lucini, Rowland R Kao, Alun L Lloyd, Simon D W Frost, Mike B Gravenor

Open access · hybridAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
0.5field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Reversed urban-rural gradient in COVID-19 seroprevalence and related factors in a nationally representative survey, Poland, 29 March to 14 May 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
    Article
  6. Review
  7. Observational
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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 2 countries.

Konstans WellsDepartment of Biosciences, Swansea University, Swansea SA2 8PP, UK.
Miguel LurgiDepartment of Biosciences, Swansea University, Swansea SA2 8PP, UK.
Brendan CollinsDepartment of Public Health and Policy, University of Liverpool, Liverpool L69 3GB, UK.
Biagio LuciniDepartment of Mathematics, Swansea University, Swansea SA2 8PP, UK.
Rowland R KaoRoyal (Dick) Veterinary School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK.
Alun L LloydBiomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA.
Simon D W FrostMicrosoft Research Lab, Redmond, Washington, WA 98052, USA.
Mike B GravenorSwansea University Medical School, Swansea University, Swansea SA2 8PP, UK.
Swansea University · GBNorth Carolina State University · USUniversity of Edinburgh · GBUniversity of Liverpool · GBUniversity of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an 'urban-rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

Indexed as

SARS-CoV-2Asymptomatic InfectionsCommunicable Disease ControlComputer SimulationContact TracingCOVID-19HumansModels, BiologicalPandemicsPhysical DistancingRural PopulationSocial InteractionUrban PopulationWalesdisease spreadepidemiological metapopulation dynamicspandemic controlsource–sink dynamics

Identifiers

PMID33292095
PMCPMC7811581
OpenAlexW3111880169

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.