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Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The objectives of the study are to present a comprehensive technique for: (i) keyword selection, (ii) keyword filtering, (iii) index composition and (iv) modeling and detection of influenza activity in China. Sequential time-series for the selected composite keyword index is significantly correlated with Chinese influenza case data. In addition, one-month ahead prediction of influenza cases for the first eight months of 2012 has a mean absolute percent error less than 11%. To our knowledge, this is the first study on the use of search query data from Baidu in conjunction with this approach for estimation of influenza activity in China. [ABSTRACT FROM AUTHOR]

Background: Acute respiratory infections (ARIs) are the leading cause of children and their leading killer. ARIs are responsible for at least six percent of the world's disability and death. Viruses are one of the most common agents causing ARIs. Few studies on the viral etiology and clinical characteristics of ARIs have been performed in the northwest region of China, including Gansu Province. Methods: Clinical and demographic information and throat swabs were collected from 279 patients from January 1st to December 30st, 2011. Multiplex RT-PCR was performed to detect 16 respiratory viral pathogens. Results: 279 patients were admitted for ARIs. The patients aged from 1 month to 12 years, with the median age of 2 years. Of which, 105 (37.6%) were positive for at least one pathogen. A total of 136 respiratory viral pathogens were identified from the 105 patients. Respiratory syncytial virus (RSV) was the most frequently detected pathogen (26.5%, 36/136), followed by parainfluenza virus (PIV) 1–3 (22.1%, 30/136), human rhinovirus (HRV) (21.3%, 29/136), human coronavirus (CoV) (10.3%, 14/136) and human adenovirus (HAdV) (9.6%, 13/136). Influenza A (Flu A), human metapneumovirus (hMPV) and human bocavirus (BoCA) were found 4.4%, 3.7% and 2.2%, respectively. Influenza B (Flu B) and seasonal influenza A H1N1(sH1N1) were not detected. Single-infections were detected in 30.5% (85/279) of cases. RSV was the most common pathogens in patients under 1 year and showed seasonal variation with peaks during winter and spring. Conclusions: This paper presents data on the epidemiology of viral pathogens associated with ARIs among children in Gansu Province, China. RSV is most frequently detected in our study. The findings could serve as a reference for local CDC in drawing up further plans to prevent and control ARIs. [ABSTRACT FROM AUTHOR]