ArticlePloS one2011
Community structure in social networks: applications for epidemiological modelling.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Behavioural change models for infectious disease transmission: a systematic review (2010-2015).Journal of the Royal Society, Interface · 2016Pooled it
- Cultural change beyond adoption dynamics: Evolutionary approaches to the discontinuation of contraception.Evolutionary human sciences · 2021Review
- Modeling and analysis of epidemic spreading on community networks with heterogeneity.Journal of parallel and distributed computing · 2018Article
- On the impact of epidemic severity on network immunization algorithms.Theoretical population biology · 2015Article
- Link removal for the control of stochastically evolving epidemics over networks: a comparison of approaches.Journal of theoretical biology · 2015Article
- Multi-scale modeling for the transmission of influenza and the evaluation of interventions toward it.Scientific reports · 2015Article
- Suppression of epidemic spreading in complex networks by local information based behavioral responses.Chaos (Woodbury, N.Y.) · 2014Article
- Towards multiscale modeling of influenza infection.Journal of theoretical biology · 2013Article
- Community structure in the phonological network.Frontiers in psychology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During an infectious disease outbreak people will often change their behaviour to reduce their risk of infection. Furthermore, in a given population, the level of perceived risk of infection will vary greatly amongst individuals. The difference in perception could be due to a variety of factors including varying levels of information regarding the pathogen, quality of local healthcare, availability of preventative measures, etc. In this work we argue that we can split a social network, representing a population, into interacting communities with varying levels of awareness of the disease. We construct a theoretical population and study which such communities suffer most of the burden of the disease and how their awareness affects the spread of infection. We aim to gain a better understanding of the effects that community-structured networks and variations in awareness, or risk perception, have on the disease dynamics and to promote more community-resolved modelling in epidemiology.
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Registered trials
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.