Attempted early detection of influenza A (H1N1) pandemic with surveillance data of influenza‐like illness and unexplained pneumonia

Qian, Yan‐Hua; Su, Jing; Shi, Ping; He, En‐Qi; Shao, Jie; Sun, Na; Zu, Rong‐Qiang; Yu, Rong‐Bin

Please cite this paper as: Qian et al. (2011) Attempted early detection of influenza A (H1N1) pandemic with surveillance data of influenza‐like illness and unexplained pneumonia. Influenza and Other Respiratory Viruses 5(6), e479–e486. Background To collect disease information and provide data for early detection of epidemics, two surveillance systems were established for influenza‐like illness (ILI) and unexplained pneumonia (UP) in Wuxi, People’s Republic of China. Objectives The current study aims to describe the performance of these surveillance systems during 2004–2009 and to evaluate the value of surveillance data in detection of influenza epidemics. Methods Two national ILI sentinel hospitals and three UP sentinel hospitals provided data to the surveillance systems. The surveillance data from hospital‐based outpatient clinics and emergency rooms were compared by year. The ILI data of 2009 were further modeled based on previous data using both a control chart method and a moving average regression method. Alarms of potential epidemics would be raised when the input surveillance data surpassed a threshold. Results In 2009, the proportions of ILI and respiratory illness with fever (one surveillance syndrome of the UP system) to total patient visits (3·40% and 11·76%, respectively) were higher than the previous years. The surveillance data of both systems also showed developing trends similar to the influenza A (H1N1) pandemic in 2009. When the surveillance data of 2009 were fitted in the two detection models, alarms were produced on the occurrence of the first local case of influenza A (H1N1), outbreaks in schools and in general populations. Conclusions The results indicated the potential for using ILI and UP surveillance data as syndromic indicators to detect and provide an early warning for influenza epidemics.