Selected article for: "infection management and long term"

Author: Zhang, Xingyu; Hou, Fengsu; Li, Xiaosong; Zhou, Lijun; Liu, Yuanyuan; Zhang, Tao
Title: Study of surveillance data for class B notifiable disease in China from 2005 to 2014
  • Cord-id: 5ffsfuh8
  • Document date: 2016_4_14
  • ID: 5ffsfuh8
    Snippet: 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 indi
    Document: 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.

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