Evidence map›Paper›PMID 20361048›Full record

ArticlePLoS computational biology2010

The impact of contact tracing in clustered populations.

Thomas House, Matt J Keeling

Abstract read
In one paragraph

Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. User Privacy, Surveillance and Public Health during COVID-19 - An Examination of Twitterverse.Information systems frontiers : a journal of research and innovation · 2022
    Article
  5. Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  6. Article
  7. Contact tracing - Old models and new challenges.Infectious Disease Modelling · 2021
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Spread of competing viruses on heterogeneous networks.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2017
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Conflicts of interest during contact investigations: a game-theoretic analysis.Computational and mathematical methods in medicine · 2014
    Article
  18. Social encounter networks: characterizing Great Britain.Proceedings. Biological sciences · 2013
    Article
  19. Article
  20. 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

2 authors.

Thomas HouseWarwick Mathematics Institute and Department of Biological Sciences, University of Warwick, Coventry, United Kingdom. T.A.House@warwick.ac.uk
Matt J Keeling

Funding

Medical Research Council G0701256Wellcome Trust
6 · The paper itself

Abstract

The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard "mass action" models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease.

Indexed as

Cluster AnalysisModels, BiologicalPopulation DynamicsComputer SimulationContact TracingHumansPrevalenceSexually Transmitted Diseases

Identifiers

PMID20361048
PMCPMC2845652

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.