Evidence map›Paper›PMID 28373567›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2017

Unraveling the disease consequences and mechanisms of modular structure in animal social networks.

Pratha Sah, Stephan T Leu, Paul C Cross, Peter J Hudson, Shweta Bansal

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
59.7field-weighted citation impact, top 1% 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

70 citing papers in PubMed, 187 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Movement decisions driving metapopulation connectivity respond to social resources in a long-lived ungulate, bighorn sheep (Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. How behavioural ageing affects infectious disease.Neuroscience and biobehavioral reviews · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

10 more citing papers are in PubMed but not listed here.

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

5 authors at 4 institutions in 1 country.

Pratha SahDepartment of Biology, Georgetown University, Washington, DC 20057; ps875@georgetown.edu shweta.bansal@georgetown.edu.ORCID 0000-0001-8936-5871
Stephan T LeuDepartment of Biology, Georgetown University, Washington, DC 20057.
Paul C CrossNorthern Rocky Mountain Science Center, US Geological Survey, Bozeman, MT 59715.
Peter J HudsonDepartment of Biology, Pennsylvania State University, University Park, PA 16802.
Shweta BansalDepartment of Biology, Georgetown University, Washington, DC 20057; ps875@georgetown.edu shweta.bansal@georgetown.edu.
Georgetown University · USNational Institutes of Health · USPennsylvania State University · USUnited States Geological Survey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

Indexed as

Disease SusceptibilityModels, TheoreticalSocial NetworkingAnimalsBehavior, AnimalCommunicable DiseasesDisease OutbreaksPopulation Densitycommunity structureinfectionmodularitysocialitywildlife disease

Identifiers

PMID28373567
PMCPMC5402400
OpenAlexW2604612116

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.