ArticleAnnals of epidemiology2016
Interdependent effects of cohesion and concurrency for epidemic potential.
Article in Annals of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Comparing transmission potential networks based on social network surveys, close contacts and environmental overlap in rural Madagascar.Journal of the Royal Society, Interface · 2022Article
- Concurrency measures in the era of temporal network epidemiology: a review.Journal of the Royal Society, Interface · 2021Review
- Concurrency and reachability in treelike temporal networks.Physical review. E · 2019Article
- Article
- Epidemic potential by sexual activity distributions.Network science (Cambridge University Press) · 2017Article
- NEW SURVEY QUESTIONS AND ESTIMATORS FOR NETWORK CLUSTERING WITH RESPONDENT-DRIVEN SAMPLING DATA.Sociological methodology · 2017Article
- Exit, cohesion, and consensus: social psychological moderators of consensus among adolescent peer groups.Social currents · 2017Article
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.
Funding
Abstract
purposeNetwork diffusion depends on both the pattern and timing of relations, but the relative effects of timing and structure remain unclear. Here, we first show that concurrency (relations that overlap in time) increases epidemic potential by opening new routes in the network. Because this is substantively similar to adding contact paths, we next compare the effects of concurrency by observed levels of path redundancy (structural cohesion) to determine how the features interact.
methodsWe establish that concurrency increases exposure analytically and then use simulation methods to manipulate concurrency over observed networks that vary naturally on structural cohesion. This design allows us to compare networks across a wide concurrency range holding constant features that might otherwise conflate concurrency and cohesion. We summarize the simulation results with general linear models.
resultsOur results indicate interdependent effects of concurrency and structural cohesion: although both increase epidemic potential, concurrency matters most when the graph structure is sparse, because the exposure created by concurrency is redundant to observed paths within structurally cohesive networks.
conclusionsConcurrency works by opening new paths in temporally ordered networks. Because this is substantively similar to having additional observed paths, concurrency in sparse networks has the same effect as adding relations and will have the greatest effect on epidemic potential in sparse networks.
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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.