He Z, Tao H. Epidemiology and ARIMA Model of Positive-Rate of Influenza Viruses among Children in Wuhan, China: A Nine-Year Retrospective Study. Int J Infect Dis. 2018 Jul 7. pii: S1201-9712(18)3
OBJECTIVE:
Influenza is a common childhood disease and protecting children by predicting the positive rate of influenza virus is important as vaccines are not routinely administered in China. Our study aims to describe the epidemiology of influenza viruses among children in Wuhan, China during the past nine influenza seasons (2007-2015) and to predict the positive rate of different types of influenza virus in the future.
METHODS:
During the last nine influenza seasons (2007-2015), a total of 10,232 nasopharyngeal swabs collected from pediatric outpatients (age<15years) with influenza-like illness (ILI) infections in two sentinel children´s hospitals, were examined for influenza A and B by real-time one step RT-PCR. An autoregressive integrated moving average (ARIMA) model was used to fit the time series and to predict the future (first half of 2016) positive rates of different types of influenza virus.
RESULTS:
A total of 1,341 specimens were positive for influenza A and 490 for influenza B. The majority of infected patients were 1-11 years old (87.7%). The ARIMA model could effectively predict the positive rate of influenza virus in a short time. ARIMA(0,0,11), SARIMA(1,0,0)(0,1,1)12, ARIMA(0,0,1) and SARIMA(0,0,1)(1,0,1)12 were suitable for B(Victoria), B(Yamagata), A(H1N1)pdm09, and A(H3N2), respectively.
CONCLUSION:
Additional policies must be formulated to prevent and control influenza. The wide use of influenza vaccines, especially for influenza B, especially for influenza B(Yamagata) and B(Victoria), can potentially reduce the effects of influenza on children of China.
Influenza is a common childhood disease and protecting children by predicting the positive rate of influenza virus is important as vaccines are not routinely administered in China. Our study aims to describe the epidemiology of influenza viruses among children in Wuhan, China during the past nine influenza seasons (2007-2015) and to predict the positive rate of different types of influenza virus in the future.
METHODS:
During the last nine influenza seasons (2007-2015), a total of 10,232 nasopharyngeal swabs collected from pediatric outpatients (age<15years) with influenza-like illness (ILI) infections in two sentinel children´s hospitals, were examined for influenza A and B by real-time one step RT-PCR. An autoregressive integrated moving average (ARIMA) model was used to fit the time series and to predict the future (first half of 2016) positive rates of different types of influenza virus.
RESULTS:
A total of 1,341 specimens were positive for influenza A and 490 for influenza B. The majority of infected patients were 1-11 years old (87.7%). The ARIMA model could effectively predict the positive rate of influenza virus in a short time. ARIMA(0,0,11), SARIMA(1,0,0)(0,1,1)12, ARIMA(0,0,1) and SARIMA(0,0,1)(1,0,1)12 were suitable for B(Victoria), B(Yamagata), A(H1N1)pdm09, and A(H3N2), respectively.
CONCLUSION:
Additional policies must be formulated to prevent and control influenza. The wide use of influenza vaccines, especially for influenza B, especially for influenza B(Yamagata) and B(Victoria), can potentially reduce the effects of influenza on children of China.
See Also:
Latest articles in those days:
- In turkeys, unlike chickens, the non-structural NS1 protein does not play a significant role in the replication and tissue tropism of the H7N1 avian influenza virus 5 hours ago
- The evolution, complexity, and diversity of swine influenza viruses in China: A hidden public health threat 2 days ago
- MHC class II proteins mediate sialic acid independent entry of human and avian H2N2 influenza A viruses 2 days ago
- Histopathologic Features and Viral Antigen Distribution of H5N1 Highly Pathogenic Avian Influenza Virus Clade 2.3.4.4b from the 2022–2023 Outbreak in Iowa Wild Birds 2 days ago
- Detection and characterization of H5N1 HPAIV in environmental samples from a dairy farm 2 days ago
[Go Top] [Close Window]