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Understanding norovirus reporting patterns in England: a mixed model approach
BACKGROUND: Norovirus has a higher level of under-reporting in England compared to other intestinal infectious agents such as Campylobacter or Salmonella, despite being recognised as the most common cause of gastroenteritis globally. In England, this under-reporting is a consequence of the frequentl...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240379/ https://www.ncbi.nlm.nih.gov/pubmed/34182979 http://dx.doi.org/10.1186/s12889-021-11317-3 |
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author | Ondrikova, N. Clough, H. E. Cunliffe, N. A. Iturriza-Gomara, M. Vivancos, R. Harris, J. P. |
author_facet | Ondrikova, N. Clough, H. E. Cunliffe, N. A. Iturriza-Gomara, M. Vivancos, R. Harris, J. P. |
author_sort | Ondrikova, N. |
collection | PubMed |
description | BACKGROUND: Norovirus has a higher level of under-reporting in England compared to other intestinal infectious agents such as Campylobacter or Salmonella, despite being recognised as the most common cause of gastroenteritis globally. In England, this under-reporting is a consequence of the frequently mild/self-limiting nature of the disease, combined with the passive surveillance system for infectious diseases reporting. We investigated heterogeneity in passive surveillance system in order to improve understanding of differences in reporting and laboratory testing practices of norovirus in England. METHODS: The reporting patterns of norovirus relating to age and geographical region of England were investigated using a multivariate negative binomial model. Multiple model formulations were compared, and the best performing model was determined by proper scoring rules based on one-week-ahead predictions. The reporting patterns are represented by epidemic and endemic random intercepts; values close to one and less than one imply a lower number of reports than expected in the given region and age-group. RESULTS: The best performing model highlighted atypically large and small amounts of reporting by comparison with the average in England. Endemic random intercept varied from the lowest in East Midlands in those in the under 5 year age-group (0.36, CI 0.18–0.72) to the highest in the same age group in South West (3.00, CI 1.68–5.35) and Yorkshire & the Humber (2.93, CI 1.74–4.94). Reporting by age groups showed the highest variability in young children. CONCLUSION: We identified substantial variability in reporting patterns of norovirus by age and by region of England. Our findings highlight the importance of considering uncertainty in the design of forecasting tools for norovirus, and to inform the development of more targeted risk management approaches for norovirus disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11317-3. |
format | Online Article Text |
id | pubmed-8240379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82403792021-06-30 Understanding norovirus reporting patterns in England: a mixed model approach Ondrikova, N. Clough, H. E. Cunliffe, N. A. Iturriza-Gomara, M. Vivancos, R. Harris, J. P. BMC Public Health Research BACKGROUND: Norovirus has a higher level of under-reporting in England compared to other intestinal infectious agents such as Campylobacter or Salmonella, despite being recognised as the most common cause of gastroenteritis globally. In England, this under-reporting is a consequence of the frequently mild/self-limiting nature of the disease, combined with the passive surveillance system for infectious diseases reporting. We investigated heterogeneity in passive surveillance system in order to improve understanding of differences in reporting and laboratory testing practices of norovirus in England. METHODS: The reporting patterns of norovirus relating to age and geographical region of England were investigated using a multivariate negative binomial model. Multiple model formulations were compared, and the best performing model was determined by proper scoring rules based on one-week-ahead predictions. The reporting patterns are represented by epidemic and endemic random intercepts; values close to one and less than one imply a lower number of reports than expected in the given region and age-group. RESULTS: The best performing model highlighted atypically large and small amounts of reporting by comparison with the average in England. Endemic random intercept varied from the lowest in East Midlands in those in the under 5 year age-group (0.36, CI 0.18–0.72) to the highest in the same age group in South West (3.00, CI 1.68–5.35) and Yorkshire & the Humber (2.93, CI 1.74–4.94). Reporting by age groups showed the highest variability in young children. CONCLUSION: We identified substantial variability in reporting patterns of norovirus by age and by region of England. Our findings highlight the importance of considering uncertainty in the design of forecasting tools for norovirus, and to inform the development of more targeted risk management approaches for norovirus disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11317-3. BioMed Central 2021-06-28 /pmc/articles/PMC8240379/ /pubmed/34182979 http://dx.doi.org/10.1186/s12889-021-11317-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Ondrikova, N. Clough, H. E. Cunliffe, N. A. Iturriza-Gomara, M. Vivancos, R. Harris, J. P. Understanding norovirus reporting patterns in England: a mixed model approach |
title | Understanding norovirus reporting patterns in England: a mixed model approach |
title_full | Understanding norovirus reporting patterns in England: a mixed model approach |
title_fullStr | Understanding norovirus reporting patterns in England: a mixed model approach |
title_full_unstemmed | Understanding norovirus reporting patterns in England: a mixed model approach |
title_short | Understanding norovirus reporting patterns in England: a mixed model approach |
title_sort | understanding norovirus reporting patterns in england: a mixed model approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240379/ https://www.ncbi.nlm.nih.gov/pubmed/34182979 http://dx.doi.org/10.1186/s12889-021-11317-3 |
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