Evidence map›Paper›PMID 23209168›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2013

What limits the evolutionary emergence of pathogens?

S Gandon, M E Hochberg, R D Holt, T Day

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Article
  2. Review
  3. Preventing Disease Emergence Following Eradication: Application to Mpox.bioRxiv : the preprint server for biology · 2026
    Article
  4. Zika Virus: A Tale of Two Lineages.Pathogens (Basel, Switzerland) · 2025
    Review
  5. Superspreading and the evolution of virulence.PLoS computational biology · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  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

4 authors.

S GandonCEFE, CNRS, 1919 route de Mende, Montpellier 34293, France. sylvain.gandon@cefe.cnrs.fr
M E Hochberg
R D Holt
T Day

Funding

Sigma virus in Drosophila: a model system for the evolution of virulenceR01GM083192 · NIGMS · UNIVERSITY OF FLORIDA · PI WAYNE, MARTA L · 2009 to 2012
$1.2M
European Research Council 243054NIGMS NIH HHS GM083192NIGMS NIH HHS R01 GM083192
6 · The paper itself

Abstract

The ability of a pathogen to cause an epidemic when introduced in a new host population often relies on its ability to adapt to this new environment. Here, we give a brief overview of recent theoretical and empirical studies of such evolutionary emergence of pathogens. We discuss the effects of several ecological and genetic factors that may affect the likelihood of emergence: migration, life history of the infectious agent, host heterogeneity, and the rate and effects of mutations. We contrast different modelling approaches and indicate how details in the way we model each step of a life cycle can have important consequences on the predicted probability of evolutionary emergence. These different theoretical perspectives yield important insights into optimal surveillance and intervention strategies, which should aim for a reduction in the emergence (and re-emergence) of infectious diseases.

Indexed as

Adaptation, BiologicalEvolution, MolecularHost SpecificityAnimal MigrationAnimalsDemographyEcosystemHumansModels, BiologicalMutationMutation RatePopulation DensityVirus DiseasesViruses

Identifiers

PMID23209168
PMCPMC3538453

What OpenQuestion holds

Textmetadata
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.