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Coherence of Influenza Surveillance Data across Different Sources and Age Groups, Beijing, China, 2008-2015

Influenza is active during the winter and spring in the city of Beijing, which has a typical temperate climate with four clear distinct seasons. The clinical and laboratory surveillance data for influenza have been used to construct critical indicators for influenza activities in the community, and...

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Detalles Bibliográficos
Autores principales: Wu, Zhenyu, Sun, Xiaoyu, Chu, Yanhui, Sun, Jingyi, Qin, Guoyou, Yang, Lin, Qin, Jingning, Xiao, Zheng, Ren, Jian, Qin, Di, Wang, Xiling, Zheng, Xueying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5201231/
https://www.ncbi.nlm.nih.gov/pubmed/28036373
http://dx.doi.org/10.1371/journal.pone.0169199
Descripción
Sumario:Influenza is active during the winter and spring in the city of Beijing, which has a typical temperate climate with four clear distinct seasons. The clinical and laboratory surveillance data for influenza have been used to construct critical indicators for influenza activities in the community, and previous studies have reported varying degrees of association between laboratory-confirmed influenza specimens and outpatient consultation rates of influenza-like illness in subtropical cities. However, few studies have reported on this issue for cities in temperate regions, especially in developing countries. Furthermore, the mechanism behind age-specific seasonal epidemics remains unresolved, although it has been widely discussed. We utilized a wavelet analysis method to monitor the coherence of weekly percentage of laboratory-confirmed influenza specimens with the weekly outpatient consultation rates of influenza-like illness in Beijing, China. We first examined the seasonal pattern of laboratory-confirmed cases of influenza A (subtyped into seasonal A(H1N1) and A(H3N2) and pandemic virus A(H1N1) pdm09) and influenza B separately within the period from 2008–2015; then, we detected the coherence of clinical and laboratory surveillance data in this district, specially examining weekly time series of age-specific epidemics of influenza-like illnesses in the whole study period for three age categories (age 0–5, 5–15 and 25–60). We found that influenza A and B were both active in winter but were not always seasonally synchronous in Beijing. Synchronization between age ranges was found in most epidemic peaks from 2008–2015. Our findings suggested that peaks of influenza-like illness in individuals aged 0–5 and 5–15 years consistently appeared ahead of those of adults, implying the possibility that schoolchildren may lead epidemic fluctuations.