ArticleJournal of mathematical biology2018
Mean-field models for non-Markovian epidemics on networks.
Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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.
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.
- Tracking Dynamics of Superspreading Through Contacts, Exposures, and Transmissions in Edge-Based Network Epidemics.Bulletin of mathematical biology · 2026Article
- Network structure induced bias in estimates of intrinsic generation times.PLoS computational biology · 2026Article
- Compartmental Models Driven by Renewal Processes: Survival Analysis and Applications to SVIS Epidemic Models.Scientific reports · 2025Article
- Towards Inferring Network Properties from Epidemic Data.Bulletin of mathematical biology · 2023Article
- Endemic state equivalence between non-Markovian SEIS and Markovian SIS model in complex networks.Physica A · 2022Article
- Balancing Quarantine and Self-Distancing Measures in Adaptive Epidemic Networks.Bulletin of mathematical biology · 2022Article
- The role of connectivity on COVID-19 preventive approaches.PloS one · 2022Article
- The role of connectivity on COVID-19 preventive approaches.medRxiv : the preprint server for health sciences · 2021Article
- Non-Markovian recovery makes complex networks more resilient against large-scale failures.Nature communications · 2020Article
- Equivalence and its invalidation between non-Markovian and Markovian spreading dynamics on complex networks.Nature communications · 2019Article
- Epidemic threshold in pairwise models for clustered networks: closures and fast correlations.Journal of mathematical biology · 2019Article
- A stochastic SIR network epidemic model with preventive dropping of edges.Journal of mathematical biology · 2019Article
- Disease persistence on temporal contact networks accounting for heterogeneous infectious periods.Royal Society open science · 2019Article
- Pairwise approximation forProceedings. Mathematical, physical, and engineering sciences · 2018Article
- The relationships between message passing, pairwise, Kermack-McKendrick and stochastic SIR epidemic models.Journal of mathematical biology · 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
4 authors.
Funding
Abstract
This paper introduces a novel extension of the edge-based compartmental model to epidemics where the transmission and recovery processes are driven by general independent probability distributions. Edge-based compartmental modelling is just one of many different approaches used to model the spread of an infectious disease on a network; the major result of this paper is the rigorous proof that the edge-based compartmental model and the message passing models are equivalent for general independent transmission and recovery processes. This implies that the new model is exact on the ensemble of configuration model networks of infinite size. For the case of Markovian transmission the message passing model is re-parametrised into a pairwise-like model which is then used to derive many well-known pairwise models for regular networks, or when the infectious period is exponentially distributed or is of a fixed length.
Indexed as
Identifiers
What OpenQuestion holds
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.