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Infectious Disease and Group Size: More than Just a Numbers Game

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Nunn, Charles L., Jordán, Ferenc, McCabe, Collin M., Verdolin, Jennifer L., Fewell, Jennifer H.·2015·Philosophical Transactions of the Royal Society B: Biological Sciences
DOI 10.1098/rstb.2014.0111PMC PMC4410377
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Abstract

Increased risk of infectious disease is assumed to be a major cost of group living, yet empirical evidence for this effect is mixed. We studied whether larger social groups are more subdivided structurally. If so, the social subdivisions that form in larger groups may act as barriers to the spread of infection, weakening the association between group size and infectious disease. To investigate this ‘social bottleneck’ hypothesis, we examined the association between group size and four network structure metrics in 43 vertebrate and invertebrate species. We focused on metrics involving modularity, clustering, distance and centralization. In a meta-analysis of intraspecific variation in social networks, modularity showed positive associations with network size, with a weaker but still positive effect in cross-species analyses. Network distance also showed a positive association with group size when using intraspecific variation. We then used a theoretical model to explore the effects of subgrouping relative to other effects that influence disease spread in socially structured populations. Outbreaks reached higher prevalence when groups were larger, but subgrouping reduced prevalence. Subgrouping also acted as a ‘brake’ on disease spread between groups. We suggest research directions to understand the conditions under which larger groups become more subdivided, and to devise new metrics that account for subgrouping when investigating the links between sociality and infectious disease risk.

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  • High-density living and increased contact can increase pathogen transmission rates among hosts.

    “High-density living and increased contact can increase pathogen transmission rates among hosts (Nunn et al. 2015).”

    From Red fox viromes in urban and rural landscapes (2020) · cites this paper as Nunn et al. 2015

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Authors
Nunn, C. L., Jordán, F., McCabe, C. M., Verdolin, J. L., & Fewell, J. H.
Affiliations
  • Duke University (US)
  • University of Trento (IT)
  • Harvard University (US)
  • Arizona State University (US)
Corresponding author
Nunn, Charles L.
ORCID
Venue
Philosophical Transactions of the Royal Society B: Biological Sciences
Publisher
The Royal Society
Published
2015-05-26
Volume
370
Issue
1669
Pages
20140111
ISSN
  • 0962-8436 (ISSN-L)
  • 1471-2970
DOI
10.1098/rstb.2014.0111
PMC
PMC4410377
OpenAlex
W1966269069
Cited by
192
References
0
Citations by year
2026: 11 · 2025: 9 · 2024: 16 · 2023: 12 · 2022: 13 · 2021: 27 · 2020: 27 · 2019: 15 · 2018: 26 · 2017: 17 · 2016: 14 · 2015: 5
FWCI
2.50
Type
journal article
Language
en
Open access
Licence
royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
Locations
  • Philosophical Transactions of the Royal Society B Biological Sciences (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Animal Behavior and Reproduction
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords
infectious diseases, group size, social networks, network modularity, network distance, network centralization, network clustering, disease spread, sociality, animal social structure, vertebrates, invertebrates
MeSH terms
Animals, Behavior, Animal, Communicable Diseases, Invertebrates, Models, Biological, Population Density, Risk Factors, Social Behavior, Species Specificity, Vertebrates

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