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The use of capture-recapture methods to provide better estimates of the burden of norovirus outbreaks from seafood in England, 2004-2011

Lookup NU author(s): Professor Sarah O'Brien

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Norovirus (NoV) is the greatest cause of infectious intestinal disease in the UK. The burden associated with foodborne outbreaks is underestimated in part because data are dispersed across different organisations. Each looks at outbreaks through a different lens. To estimate the burden of NoV from seafood including shellfish we used a capture-recapture technique using datasets from three different organisations currently involved in collecting information on outbreaks. The number of outbreaks of NoV related to seafood including shellfish in England was estimated for the period of 2004–2011. The combined estimates were more than three times as high (N = 360 using Chao's sample coverage approach) as the individual count from organisation three (N = 115), which captured more outbreaks than the other two organisations. The estimates were calculated for both independence and dependence between the datasets. There was evidence of under-reporting of NoV outbreaks and inconsistency of reporting between organisations, which means that, currently, more than one data source needs to be used to estimate as accurately as possible the total number of NoV outbreaks and associated cases. Furthermore, either the integration of reporting mechanisms or simplifying the process of reporting outbreaks to organisations is essential for understanding and, hence, controlling disease burden.


Publication metadata

Author(s): Hardstaff JL, Clough HE, Harris JP, Lowther JA, Lees DN, O'Brien SJ

Publication type: Article

Publication status: Published

Journal: Epidemiology and Infection

Year: 2018

Volume: 147

Pages: 1-7

Online publication date: 04/12/2018

Acceptance date: 22/10/2018

Date deposited: 22/08/2019

ISSN (print): 0950-2688

ISSN (electronic): 1469-4409

Publisher: Cambridge University Press

URL: https://doi.org/10.1017/S0950268818003217

DOI: 10.1017/S0950268818003217

PubMed id: 30511608


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