4.7 Article

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

Journal

INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
Volume 48, Issue -, Pages 7-13

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ijid.2016.04.010

Keywords

Infectious disease; Seasonality; Long-term trend; Time series

Funding

  1. National Science and Technology Major Special Project Data mining and analysis of the surveillance data of five syndrome pathogens [2012ZX10004201-006]
  2. Sichuan University grant the Fundamental Research Funds for the Central Universities [2016SCU11006]
  3. China Scholarship Council (CSC)

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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. (C) 2016 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license.

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