Evidence map›Paper›PMID 21120484›Full record

ArticleJournal of mathematical biology2011

Epidemic growth rate and household reproduction number in communities of households, schools and workplaces.

Lorenzo Pellis, Neil M Ferguson, Christophe Fraser

Abstract readComparative Study
In one paragraph

Article in Journal of mathematical biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  8. Measurability of the epidemic reproduction number in data-driven contact networks.Proceedings of the National Academy of Sciences of the United States of America · 2018
    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.

Lorenzo PellisMedical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary's Hospital, Norfolk Place, London, W2 1PG, UK. l.pellis05@imperial.ac.uk
Neil M Ferguson
Christophe Fraser

Funding

Training, Outreach & Diversity ComponentU54GM088491 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ROBERTS, MARK STENIUS · 2009 to 2018
$16.7M
Medical Research Council G0800596NIGMS NIH HHS U54 GM088491
6 · The paper itself

Abstract

In this paper we present a novel and coherent modelling framework for the characterisation of the real-time growth rate in SIR models of epidemic spread in populations with social structures of increasing complexity. Known results about homogeneous mixing and multitype models are included in the framework, which is then extended to models with households and models with households and schools/workplaces. Efficient methods for the exact computation of the real-time growth rate are presented for the standard SIR model with constant infection and recovery rates (Markovian case). Approximate methods are described for a large class of models with time-varying infection rates (non-Markovian case). The quality of the approximation is assessed via comparison with results from individual-based stochastic simulations. The methodology is then applied to the case of influenza in models with households and schools/workplaces, to provide an estimate of a household-to-household reproduction number and thus asses the effort required to prevent an outbreak by targeting control policies at the level of households. The results highlight the risk of underestimating such effort when the additional presence of schools/workplaces is neglected. Our framework increases the applicability of models of epidemic spread in socially structured population by linking earlier theoretical results, mainly focused on time-independent key epidemiological parameters (e.g. reproduction numbers, critical vaccination coverage, epidemic final size) to new results on the epidemic dynamics.

Indexed as

Family CharacteristicsModels, StatisticalSchoolsWorkplaceBasic Reproduction NumberComputer SimulationHumansInfluenza, HumanMarkov ChainsStochastic Processes

Identifiers

PMID21120484
PMCPMC3786716

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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.