Evidence map›Paper›PMID 30937531›Full record

ArticleJournal of mathematical biology2019

A stochastic SIR model on a graph with epidemiological and population dynamics occurring over the same time scale.

Pierre Montagnon

Abstract read
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In one paragraph

Article in Journal of mathematical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Spread of Epidemic Disease on Edge-Weighted Graphs from a Database: A Case Study of COVID-19.International journal of environmental research and public health · 2021
    Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Pierre MontagnonCMAP, École Polytechnique, Route de Saclay, 91128, Palaiseau Cedex, France. pierre.montagnon@polytechnique.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We define and study an open stochastic SIR (Susceptible-Infected-Removed) model on a graph in order to describe the spread of an epidemic on a cattle trade network with epidemiological and demographic dynamics occurring over the same time scale. Population transition intensities are assumed to be density-dependent with a constant component, the amplitude of which determines the overall scale of the population process. Standard branching approximation results for the epidemic process are first given, along with a numerical computation method for the probability of a major epidemic outbreak. This procedure is illustrated using real data on trade-related cattle movements from a densely populated livestock farming region in western France (Finistère) and epidemiological parameters corresponding to an infectious epizootic disease. Then we exhibit an exponential lower bound for the extinction time and the total size of the epidemic in the stable endemic case as a scaling parameter goes to infinity using results inspired by the Freidlin-Wentzell theory of large deviations from a dynamical system.

Indexed as

Models, BiologicalAnimal HusbandryAnimalsBasic Reproduction NumberCattleCattle DiseasesCommerceDisease SusceptibilityEpidemicsFrancePopulation DynamicsStochastic ProcessesBasic reproduction numberContinuous-time multitype branching processesEndemicityEpidemic and demography over the same time scaleEpidemic extinction timeEpidemic total sizeMajor outbreak probabilityMarkovian processMultitype SIR modelReal network

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.