4.7 Article

Epidemiology of influenza in hospitalized children with respiratory tract infection in Suzhou area from 2016 to 2019

Journal

JOURNAL OF MEDICAL VIROLOGY
Volume 92, Issue 12, Pages 3038-3046

Publisher

WILEY
DOI: 10.1002/jmv.26015

Keywords

ARIMA model; children; epidemiology; influenza virus; respiratory tract infection

Categories

Funding

  1. Suzhou Medical Youth Talent [GSWS2019047]
  2. Science and Technology Program of Suzhou [SS201869]
  3. Suzhou Medical Technology Project of Clinical Key Diseases [LCZX201809]
  4. National Natural Science Foundation of China [81771676, 81870006]
  5. Social Development Projects of Jiangsu Province [BE2019671]
  6. Key Lab of Respiratory Disease of Suzhou [SZS201714]
  7. Jiangsu Provincial Medical Youth Talent [QNRC2016766]

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Influenza is a contagious respiratory disease and risks public health in China, and it has caused wide public concern in recent years. Immunocompromised patients, such as children and elderly people, suffer more severe influenza complication and some extreme cases are even life threatening. To identify the influenza characteristics and its correlation with various climatic and environmental pollution factors, we collected the reported influenza epidemic of hospitalized children in Children's Hospital of Soochow University from 2016 to 2019. Our results show that the main influenza virus subtypes are A/H1N1, A/H3N2, B/BV, and B/BY. We also identified the characteristics of the prevalent influenza virus subtypes in different months, seasons, years, and patients' age. Of all the influenza infected patients, the most susceptible groups are children over 3 to 5 years of age, and more cases are reported in winter than other seasons. We also found that influenza is also highly correlated with climatic and environmental pollution factors, and the autoregressive integrated moving average model is employed for the short-term influenza prediction in Suzhou city, which can provide scientific basis for the prevention and control of influenza and public health decision-making.

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