Norovirus transmission dynamics: a modelling review.
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Published version
Author(s)
Gaythorpe, KAM
Trotter, CL
Lopman, B
Steele, M
Conlan, AJK
Type
Journal Article
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.
Date Issued
2017-12-22
Date Acceptance
2017-11-06
Citation
Epidemiology and Infection, 2017, 146 (2), pp.147-158
ISSN
0950-2688
Publisher
Cambridge University Press (CUP)
Start Page
147
End Page
158
Journal / Book Title
Epidemiology and Infection
Volume
146
Issue
2
Copyright Statement
OPYRIGHT: © Cambridge University Press 2017
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
PII: S0950268817002692
Subjects
Basic reproduction number
estimating disease prevalence
mathematical modelling
norovirus
transmission
Publication Status
Published