ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2013
Cocirculation of infectious diseases on networks.
Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2013. 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
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.
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.
- Behavioural change models for infectious disease transmission: a systematic review (2010-2015).Journal of the Royal Society, Interface · 2016Pooled it
- Strength and weakness of disease-induced herd immunity in networks.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.PLoS computational biology · 2021Article
- Interplay between competitive and cooperative interactions in a three-player pathogen system.Royal Society open science · 2020Article
- Coevolution spreading in complex networks.Physics reports · 2019Review
- Multiple peaks patterns of epidemic spreading in multi-layer networks.Chaos, solitons, and fractals · 2018Article
- Mutually cooperative epidemics on power-law networks.Physical review. E · 2017Article
- Host population structure impedes reversion to drug sensitivity after discontinuation of treatment.PLoS computational biology · 2017Article
- Evolution and emergence of infectious diseases in theoretical and real-world networks.Nature communications · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
We consider multiple diseases spreading in a static configuration model network. We make standard assumptions that infection transmits from neighbor to neighbor at a disease-specific rate and infected individuals recover at a disease-specific rate. Infection by one disease confers immediate and permanent immunity to infection by any disease. Under these assumptions, we find a simple, low-dimensional ordinary differential equations model which captures the global dynamics of the infection. The dynamics depend strongly on initial conditions. Although we motivate this Rapid Communication with infectious disease, the model may be adapted to the spread of other infectious agents such as competing political beliefs, or adoption of new technologies if these are influenced by contacts. As an example, we demonstrate how to model an infectious disease which can be prevented by a behavior change.
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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.