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2022-8-19 22:08:50

He J, Hou S, Chen Y, Yu JL, Chen QQ, He L, Liu J,. The Epidemiological Pattern and Co-infection of Influenza A and B by Surveillance Network From 2009 to 2014 in Anhui Province, China. Front Public Health. 2022 Feb 24;10:825645
submited by kickingbird at Mar, 17, 2022 19:44 PM from Front Public Health. 2022 Feb 24;10:825645

Influenza-like illness (ILI) is one of the most important public health problems globally, causing an enormous disease burden. Influenza infections are the most common cause of ILI. Bacterial and virus co-infection is common yet the data of co-infection with influenza A and B viruses are scarce. To identify the epidemiological patterns of and co-infection of influenza A and B in Anhui province, China, we analyzed the surveillance data of 5 years from 2009 to 2014 collected by the Chinese National influenzas network. The results showed that the weekly ratio of ILI was 3.96 ± 1.9% (95% CI 3.73-4.2%) in outpatients and the highest affected population was children under 5 years old. The epidemic of influenza viruses was highest during 2009-2010. For the other 4 surveillance years, school-aged people (5-14 years) were the most highly affected population. Influenza B and H3N2 viruses were more prevalent than H1N1pdm09 virus after 2010. In addition, a significant co-circulation of influenza A (H1N1pdm09 and H3N2) and influenza B virus was detected with 0.057% PCR positive rate during 2009-2014 in Eastern China, yet isolated only in pediatric patients. Our data reveals school-aged population would be the main vulnerable population and a distinct seasonality for influenza. In addition, the co-infection of influenza A and B were found in Anhui Province, China. Ongoing surveillance is critical to understand the seasonality variation and make evidence-based vaccination recommendations. Information on the epidemiological patterns and co-infections of influenza A and B can help us to implement different strategies for selecting vaccine formulations and monitoring new emerging influenza strains. In addition, the identification of the susceptible population can help us to develop more precise protection measures.

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