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A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan
BACKGROUND: Detecting the onset of influenza epidemic is important for epidemiological surveillance and for investigating the factors driving spatiotemporal transmission patterns. Most approaches define the epidemic onset based on thresholds, which use subjective criteria and are specific to individ...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383251/ https://www.ncbi.nlm.nih.gov/pubmed/30786869 http://dx.doi.org/10.1186/s12879-019-3777-x |
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author | Cai, Jun Zhang, Bing Xu, Bo Chan, Karen Kie Yan Chowell, Gerardo Tian, Huaiyu Xu, Bing |
author_facet | Cai, Jun Zhang, Bing Xu, Bo Chan, Karen Kie Yan Chowell, Gerardo Tian, Huaiyu Xu, Bing |
author_sort | Cai, Jun |
collection | PubMed |
description | BACKGROUND: Detecting the onset of influenza epidemic is important for epidemiological surveillance and for investigating the factors driving spatiotemporal transmission patterns. Most approaches define the epidemic onset based on thresholds, which use subjective criteria and are specific to individual surveillance systems. METHODS: We applied the empirical threshold method (ETM), together with two non-thresholding methods, including the maximum curvature method (MCM) that we proposed and the segmented regression method (SRM), to determine onsets of influenza epidemics in each prefecture of Japan, using sentinel surveillance data of influenza-like illness (ILI) from 2012/2013 through 2017/2018. Performance of the MCM and SRM was evaluated, in terms of epidemic onset, end, and duration, with those derived from the ETM using the nationwide epidemic onset indicator of 1.0 ILI case per sentinel per week. RESULTS: The MCM and SRM yielded complete estimates for each of Japan’s 47 prefectures. In contrast, ETM estimates for Kagoshima during 2012/2013 and for Okinawa during all six influenza seasons, except 2013/2014, were invalid. The MCM showed better agreement in all estimates with the ETM than the SRM (R(2) = 0.82, p < 0.001 vs. R(2) = 0.34, p < 0.001 for epidemic onset; R(2) = 0.18, p < 0.001 vs. R(2) = 0.05, p < 0.001 for epidemic end; R(2) = 0.28, p < 0.001 vs. R(2) < 0.01, p = 0.35 for epidemic duration). Prefecture-specific thresholds for epidemic onset and end were established using the MCM. CONCLUSIONS: The Japanese national epidemic onset threshold is not applicable to all prefectures, particularly Okinawa. The MCM could be used to establish prefecture-specific epidemic thresholds that faithfully characterize influenza activity, serving as useful complements to the influenza surveillance system in Japan. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3777-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6383251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63832512019-03-01 A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan Cai, Jun Zhang, Bing Xu, Bo Chan, Karen Kie Yan Chowell, Gerardo Tian, Huaiyu Xu, Bing BMC Infect Dis Research Article BACKGROUND: Detecting the onset of influenza epidemic is important for epidemiological surveillance and for investigating the factors driving spatiotemporal transmission patterns. Most approaches define the epidemic onset based on thresholds, which use subjective criteria and are specific to individual surveillance systems. METHODS: We applied the empirical threshold method (ETM), together with two non-thresholding methods, including the maximum curvature method (MCM) that we proposed and the segmented regression method (SRM), to determine onsets of influenza epidemics in each prefecture of Japan, using sentinel surveillance data of influenza-like illness (ILI) from 2012/2013 through 2017/2018. Performance of the MCM and SRM was evaluated, in terms of epidemic onset, end, and duration, with those derived from the ETM using the nationwide epidemic onset indicator of 1.0 ILI case per sentinel per week. RESULTS: The MCM and SRM yielded complete estimates for each of Japan’s 47 prefectures. In contrast, ETM estimates for Kagoshima during 2012/2013 and for Okinawa during all six influenza seasons, except 2013/2014, were invalid. The MCM showed better agreement in all estimates with the ETM than the SRM (R(2) = 0.82, p < 0.001 vs. R(2) = 0.34, p < 0.001 for epidemic onset; R(2) = 0.18, p < 0.001 vs. R(2) = 0.05, p < 0.001 for epidemic end; R(2) = 0.28, p < 0.001 vs. R(2) < 0.01, p = 0.35 for epidemic duration). Prefecture-specific thresholds for epidemic onset and end were established using the MCM. CONCLUSIONS: The Japanese national epidemic onset threshold is not applicable to all prefectures, particularly Okinawa. The MCM could be used to establish prefecture-specific epidemic thresholds that faithfully characterize influenza activity, serving as useful complements to the influenza surveillance system in Japan. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3777-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-20 /pmc/articles/PMC6383251/ /pubmed/30786869 http://dx.doi.org/10.1186/s12879-019-3777-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cai, Jun Zhang, Bing Xu, Bo Chan, Karen Kie Yan Chowell, Gerardo Tian, Huaiyu Xu, Bing A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title | A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title_full | A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title_fullStr | A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title_full_unstemmed | A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title_short | A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan |
title_sort | maximum curvature method for estimating epidemic onset of seasonal influenza in japan |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383251/ https://www.ncbi.nlm.nih.gov/pubmed/30786869 http://dx.doi.org/10.1186/s12879-019-3777-x |
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