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Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model
BACKGROUND: In temperate zones, all‐cause mortality exhibits a marked seasonality, and influenza represents a major cause of winter excess mortality. We present a statistical model, FluMOMO, which estimate influenza‐associated mortality from all‐cause mortality data and apply it to Danish data from...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086850/ https://www.ncbi.nlm.nih.gov/pubmed/29660769 http://dx.doi.org/10.1111/irv.12564 |
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author | Nielsen, Jens Krause, Tyra Grove Mølbak, Kåre |
author_facet | Nielsen, Jens Krause, Tyra Grove Mølbak, Kåre |
author_sort | Nielsen, Jens |
collection | PubMed |
description | BACKGROUND: In temperate zones, all‐cause mortality exhibits a marked seasonality, and influenza represents a major cause of winter excess mortality. We present a statistical model, FluMOMO, which estimate influenza‐associated mortality from all‐cause mortality data and apply it to Danish data from 2010/11 to 2016/17. METHODS: We applied a multivariable time series model with all‐cause mortality as outcome, influenza activity and extreme temperatures as explanatory variables while adjusting for time trend and seasonality. Three indicators of weekly influenza activity (IA) were explored: percentage of consultations for influenza‐like illness (ILI) at primary health care, national percentage of influenza‐positive samples, and the product of ILI percentage and percentage of influenza‐positive specimens in a given week, that is, the Goldstein index. RESULTS: Independent of the choice of parameter to represent influenza activity, the estimated influenza‐associated mortality showed similar patterns with the Goldstein index being the most conservative. Over the 7 winter seasons, the median influenza‐associated mortality per 100 000 population was 17.6 (range: 0.0‐36.8), 14.1 (0.3‐31.6) and 8.3 (0.0‐25.0) for the 3 indicators, respectively, for all ages. CONCLUSION: The FluMOMO model fitted the Danish data well and has the potential to estimate all‐cause influenza‐associated mortality in near real time and could be used as a standardised method in other countries. We recommend using the Goldstein index as the influenza activity indicator in the FluMOMO model. Further work is needed to improve the interpretation of the estimated effects. |
format | Online Article Text |
id | pubmed-6086850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60868502018-09-01 Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model Nielsen, Jens Krause, Tyra Grove Mølbak, Kåre Influenza Other Respir Viruses Original Articles BACKGROUND: In temperate zones, all‐cause mortality exhibits a marked seasonality, and influenza represents a major cause of winter excess mortality. We present a statistical model, FluMOMO, which estimate influenza‐associated mortality from all‐cause mortality data and apply it to Danish data from 2010/11 to 2016/17. METHODS: We applied a multivariable time series model with all‐cause mortality as outcome, influenza activity and extreme temperatures as explanatory variables while adjusting for time trend and seasonality. Three indicators of weekly influenza activity (IA) were explored: percentage of consultations for influenza‐like illness (ILI) at primary health care, national percentage of influenza‐positive samples, and the product of ILI percentage and percentage of influenza‐positive specimens in a given week, that is, the Goldstein index. RESULTS: Independent of the choice of parameter to represent influenza activity, the estimated influenza‐associated mortality showed similar patterns with the Goldstein index being the most conservative. Over the 7 winter seasons, the median influenza‐associated mortality per 100 000 population was 17.6 (range: 0.0‐36.8), 14.1 (0.3‐31.6) and 8.3 (0.0‐25.0) for the 3 indicators, respectively, for all ages. CONCLUSION: The FluMOMO model fitted the Danish data well and has the potential to estimate all‐cause influenza‐associated mortality in near real time and could be used as a standardised method in other countries. We recommend using the Goldstein index as the influenza activity indicator in the FluMOMO model. Further work is needed to improve the interpretation of the estimated effects. John Wiley and Sons Inc. 2018-05-06 2018-09 /pmc/articles/PMC6086850/ /pubmed/29660769 http://dx.doi.org/10.1111/irv.12564 Text en © 2018 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Nielsen, Jens Krause, Tyra Grove Mølbak, Kåre Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title | Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title_full | Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title_fullStr | Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title_full_unstemmed | Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title_short | Influenza‐associated mortality determined from all‐cause mortality, Denmark 2010/11‐2016/17: The FluMOMO model |
title_sort | influenza‐associated mortality determined from all‐cause mortality, denmark 2010/11‐2016/17: the flumomo model |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086850/ https://www.ncbi.nlm.nih.gov/pubmed/29660769 http://dx.doi.org/10.1111/irv.12564 |
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