Evidence map›Paper›PMID 26070348›Full record

ArticleJournal of mathematical biology2016

Stochastic SIR epidemics in a population with households and schools.

Tanneke Ouboter, Ronald Meester, Pieter Trapman

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Tanneke OuboterRadboud University, Nijmegen, The Netherlands.
Ronald MeesterVrije Universiteit, Amsterdam, The Netherlands.
Pieter TrapmanStockholm University, Stockholm, Sweden. ptrapman@math.su.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We study the spread of stochastic SIR (Susceptible [Formula: see text] Infectious [Formula: see text] Recovered) epidemics in two types of structured populations, both consisting of schools and households. In each of the types, every individual is part of one school and one household. In the independent partition model, the partitions of the population into schools and households are independent of each other. This model corresponds to the well-studied household-workplace model. In the hierarchical model which we introduce here, members of the same household are also members of the same school. We introduce computable branching process approximations for both types of populations and use these to compare the probabilities of a large outbreak. The branching process approximation in the hierarchical model is novel and of independent interest. We prove by a coupling argument that if all households and schools have the same size, an epidemic spreads easier (in the sense that the number of individuals infected is stochastically larger) in the independent partition model. We also show by example that this result does not necessarily hold if households and/or schools do not all have the same size.

Indexed as

EpidemicsChildCommunicable DiseasesComputer SimulationFamily CharacteristicsHumansMathematical ConceptsModels, BiologicalPopulation DensitySchoolsStochastic ProcessesBranching processesCouplingSIR epidemicsStructured populations

Identifiers

PMID26070348
PMCPMC4767871

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.