Evidence map›Paper›PMID 24416152›Full record

ArticlePloS one2014

Commuter mobility and the spread of infectious diseases: application to influenza in France.

Segolene Charaudeau, Khashayar Pakdaman, Pierre-Yves Boëlle

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces.International journal of environmental research and public health · 2023
    Article
  7. How regularly do people visit service places?Computers, environment and urban systems · 2023
    Article
  8. Article
  9. Urban mobility patterns and the spatial distribution of infections in Santiago de Chile.Transportation research. Part A, Policy and practice · 2022
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. What drives disease flows between locations?Transactions in GIS : TG · 2020
    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

3 authors.

Segolene CharaudeauINSERM, UMR S 707, Paris, France ; Université Pierre et Marie Curie - Paris 6, Paris, France ; Institut Jacques Monod, Paris, France ; Université Denis Diderot, Paris, France.
Khashayar PakdamanInstitut Jacques Monod, Paris, France ; Université Denis Diderot, Paris, France.
Pierre-Yves BoëlleINSERM, UMR S 707, Paris, France ; Université Pierre et Marie Curie - Paris 6, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Commuting data is increasingly used to describe population mobility in epidemic models. However, there is little evidence that the spatial spread of observed epidemics agrees with commuting. Here, using data from 25 epidemics for influenza-like illness in France (ILI) as seen by the Sentinelles network, we show that commuting volume is highly correlated with the spread of ILI. Next, we provide a systematic analysis of the spread of epidemics using commuting data in a mathematical model. We extract typical paths in the initial spread, related to the organization of the commuting network. These findings suggest that an alternative geographic distribution of GP accross France to the current one could be proposed. Finally, we show that change in commuting according to age (school or work commuting) impacts epidemic spread, and should be taken into account in realistic models.

Indexed as

TransportationAge FactorsCommunicable DiseasesComputer SimulationFranceGeographyHumansIncidenceInfluenza, HumanSchoolsWorkplace

Identifiers

PMID24416152
PMCPMC3886984

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Registered trials

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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.