ArticleScientific reports2015
Incorporating Contact Network Structure in Cluster Randomized Trials.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Review of the Ring Trial Design for Evaluating Ring Interventions for Infectious Diseases.Epidemiologic reviews · 2022Pooled it
- Clustering and classification of soybean leaves based on angle features.Frontiers in plant science · 2026Article
- Tracing and testing multiple generations of contacts to COVID-19 cases: cost-benefit trade-offs.Royal Society open science · 2022Article
- Article
- Edge Overlap in Weighted and Directed Social Networks.Network science (Cambridge University Press) · 2021Article
- Bayesian method for inferring the impact of geographical distance on intensity of communication.Scientific reports · 2020Article
- Article
- Choices in vaccine trial design in epidemics of emerging infections.PLoS medicine · 2018Article
- Exposure, hazard, and survival analysis of diffusion on social networks.Statistics in medicine · 2018Article
- Impact of stochastically generated heterogeneity in hazard rates on individually randomized vaccine efficacy trials.Clinical trials (London, England) · 2018Article
- Impact of degree truncation on the spread of a contagious process on networks.Network science (Cambridge University Press) · 2018Article
- Risk ratios for contagious outcomes.Journal of the Royal Society, Interface · 2018Article
- Simulations for designing and interpreting intervention trials in infectious diseases.BMC medicine · 2017Article
- Review of Recent Methodological Developments in Group-Randomized Trials: Part 1-Design.American journal of public health · 2017Review
- Leveraging contact network structure in the design of cluster randomized trials.Clinical trials (London, England) · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Whenever possible, the efficacy of a new treatment is investigated by randomly assigning some individuals to a treatment and others to control, and comparing the outcomes between the two groups. Often, when the treatment aims to slow an infectious disease, clusters of individuals are assigned to each treatment arm. The structure of interactions within and between clusters can reduce the power of the trial, i.e. the probability of correctly detecting a real treatment effect. We investigate the relationships among power, within-cluster structure, cross-contamination via between-cluster mixing, and infectivity by simulating an infectious process on a collection of clusters. We demonstrate that compared to simulation-based methods, current formula-based power calculations may be conservative for low levels of between-cluster mixing, but failing to account for moderate or high amounts can result in severely underpowered studies. Power also depends on within-cluster network structure for certain kinds of infectious spreading. Infections that spread opportunistically through highly connected individuals have unpredictable infectious breakouts, making it harder to distinguish between random variation and real treatment effects. Our approach can be used before conducting a trial to assess power using network information, and we demonstrate how empirical data can inform the extent of between-cluster mixing.
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