Influenza Surveillance System, Beijing, China | CDC EID

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Volume 15, Number 10–October 2009
Research
Review of an Influenza Surveillance System, Beijing, People's Republic of China
Peng Yang, Wei Duan, Min Lv, Weixian Shi, Xiaoming Peng, Xiaomei Wang, Yanning Lu, Huijie Liang, Holly Seale, Xinghuo Pang, and Quanyi Wang
Author affiliations: Beijing Center for Disease Prevention and Control, Beijing, People's Republic of China (P. Yang, W. Duan, M. Lv, W. Shi, X. Peng, X. Wang, Y. Lu, H. Liang, X. Pang, Q. Wang); and University of New South Wales, Sydney, New South Wales, Australia (H. Seale)

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Abstract
In 2007, a surveillance system for influenza-like illness (ILI) and virologic data was established in Beijing, China. The system tracked ILI and laboratory-confirmed influenza in 153 general hospitals from September 1, 2007, through April 30, 2008. To analyze the ILI surveillance data (weekly ILI rates and counts) and the effectiveness of the system, we used the US Centers for Disease Control and Prevention Early Aberration Reporting System. The data indicated that the highest rate of influenza isolation and the highest ILI count occurred in the first week of 2008. The system enabled us to detect the onset and peak of an epidemic.

Surveillance systems in Beijing, People's Republic of China, play a pivotal role in the detection of seasonal influenza. They enable the onset and the peak of an influenza epidemic to be reported in a timely and accurate manner. These systems may be critical to monitoring future emerging aberrant situations, such as an influenza pandemic.

Since 1997, >400 human cases of infection with avian influenza virus A (H5N1) have been documented worldwide, with death rates of ≈60% (1). Of concern is that these influenza A viruses might undergo the genetic changes of antigenic drift into novel pathogenic forms (2), triggering human influenza pandemics (3). Recently, the World Health Organization (WHO) raised the influenza pandemic alert to level 6 because of the emergence of the influenza A pandemic (H1N1) 2009 virus (4). Experts at WHO believe that "the world is now closer to another influenza pandemic than at any time since 1968" (5).

An influenza surveillance program, consisting of disease and virologic data collection, aims to assist in the early detection of influenza, help define the distribution of influenza in the community, and provide timely information about circulating strains. These data, in turn, can be used to analyze geographic, temporal, and biologic differences in circulating influenza strains and assist in monitoring for emerging unusual or critical situations, such as a pandemic (6–8). This information can guide the crucial process of strain selection for vaccine development and other prevention and control strategies (7), as well as aid influenza diagnosis and enhance patient care (9–12).

To use data from a surveillance system efficiently, however, public health professionals need suitable and robust aberration detection methods. The Early Aberration Reporting System (EARS) pioneered by the US Centers for Disease Control and Prevention (CDC; Atlanta, GA, USA) was initially a method for monitoring bioterrorism events, but it has evolved into a tool that also can be used to monitor naturally occurring outbreaks and seasonal diseases. Nonhistorical methods based on a positive 1-sided cumulative sum (CUSUM) calculation in EARS can analyze the data without long-term background data (13,14).

In 2007, a surveillance system for influenza-like illness (ILI) and virologic data was established in Beijing. This system tracks ILI and laboratory-confirmed influenza in 153 general hospitals throughout Beijing. We describe the surveillance system, the surveillance data accumulated during the 2007–08 influenza season, and the performance of the early warning system.

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