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Study of surveillance data for class B notifiable disease in China from 2005 to 2014

BACKGROUND: The surveillance of infection is very important for public health management and disease control. It has been 10 years since China implemented its new web-based infection surveillance system, which covers the largest population in the world. METHODS: In this study, time series data were...

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Detalles Bibliográficos
Autores principales: Zhang, Xingyu, Hou, Fengsu, Li, Xiaosong, Zhou, Lijun, Liu, Yuanyuan, Zhang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110548/
https://www.ncbi.nlm.nih.gov/pubmed/27094249
http://dx.doi.org/10.1016/j.ijid.2016.04.010
Descripción
Sumario:BACKGROUND: The surveillance of infection is very important for public health management and disease control. It has been 10 years since China implemented its new web-based infection surveillance system, which covers the largest population in the world. METHODS: In this study, time series data were collected for 28 infectious diseases reported from 2005 to 2014 . Seasonality and long-term trends were explored using decomposition methods. Seasonality was expressed by calculating the seasonal indices. Long-term trends in the diseases were assessed using a linear regression model on the deseasonalized series. RESULTS: During the 10-year period, 38 982 567 cases and 126 372 deaths were reported in the system. The proportion of deaths caused by AIDS increased from 12% in 2005 to 78% in 2014. There were six diseases for which the seasonal index range was greater than 2: dengue fever, Japanese encephalitis, leptospirosis, anthrax, cerebrospinal meningitis, and measles . Among the 28 diseases, the incidence of syphilis increased fastest, with an average increase of 0.018626/100 000 every month after adjustment for seasonality. CONCLUSIONS: Effective surveillance is helpful in gaining a better understanding of the infection behaviour of infectious diseases; this will greatly facilitate disease control and management.