Evidence map›Paper›PMID 29268812›Full record

ReviewEpidemiology and infection2018

Norovirus transmission dynamics: a modelling review.

K A M Gaythorpe, C L Trotter, B Lopman, M Steele, A J K Conlan

Abstract readReview
In one paragraph

Review in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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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

5 authors.

K A M GaythorpeDepartment of Veterinary Medicine,University of Cambridge,Cambridge,UK.
C L TrotterDepartment of Veterinary Medicine,University of Cambridge,Cambridge,UK.
B LopmanDepartment of Epidemiology,Emory University,Atlanta, Georgia,USA.
M SteeleDepartment of Epidemiology,Emory University,Atlanta, Georgia,USA.
A J K ConlanDepartment of Veterinary Medicine,University of Cambridge,Cambridge,UK.

Funding

Graduate and Postdoctoral Training in ToxicologyT32ES012870 · NIEHS · EMORY UNIVERSITY · PI Carmen Joseph Marsit · 2004 to 2026
$9.1M
Medical Research Council MR/R015600/1NIEHS NIH HHS T32 ES012870
6 · The paper itself

Abstract

Norovirus is one of the leading causes of viral gastroenteritis worldwide and responsible for substantial morbidity, mortality and healthcare costs. To further understanding of the epidemiology and control of norovirus, there has been much recent interest in describing the transmission dynamics of norovirus through mathematical models. In this study, we review the current modelling approaches for norovirus transmission. We examine the data and methods used to estimate these models that vary structurally and parametrically between different epidemiological contexts. Many of the existing studies at population level have focused on the same case notification dataset, whereas models from outbreak settings are highly specific and difficult to generalise. In this review, we explore the consistency in the description of norovirus transmission dynamics and the robustness of parameter estimates between studies. In particular, we find that there is considerable variability in estimates of key parameters such as the basic reproduction number, which may mean that the effort required to control norovirus at the population level may currently be underestimated.

Indexed as

Caliciviridae InfectionsDisease OutbreaksGastroenteritisHumansModels, TheoreticalNorovirusBasic reproduction numberestimating disease prevalencemathematical modellingnorovirustransmission

Identifiers

PMID29268812
PMCPMC5851036

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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.