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Objective@#To analyze the epidemiological characteristics and the molecular types of human adenovirus (HAdV) from influenza-like illness (ILI) samples with negative influenza virus in Xi'an from January 2013 to December 2015.@*Methods@#Samples from patients with ILI were collected from two national influenza sentinel surveillance hospitals during 2013—2015 in Xi′an. HAdV was detected by real-time PCR, and then the positive samples were inoculated into Hep-2 cells to isolate the viruses. The amplified products were purified and sequenced of hexon gene, and the sequences were compared with the Genebank data and phylogenetic trees were constructed.@*Results@#In 2367 samples, 88 samples were positive for HAdV, the positive rate was 3.72%. There were 7 subtypes detected, and the rates of each subtype are as follows: HAdV-1 was 9.09%, HAdV-2 was 22.73%, HAdV-3 was 23.86%, HAdV-4 was 5.68%, HAdV-5 was 7.95%, HAdV-6 was 3.41% and HAdV-7 was 1.14%. Males had higher infection rate than females, but there was no significant difference. The patients were divided into 6 groups according to age. There were 3 positive samples among those under 1 year of age, 36 positive samples among those 1 to 3 years old, 26 positive samples among those 4 to 6 years old, 16 positive samples in those 7 to 18 years old, 5 positive samples in 19 to 59 years old and 2 positive samples in those older than sixty years of age. HAdV infection was primarily confined to children under 7 years of age.@*Conclusions@#HAdV-3 and HAdV-2 were the dominant epidemic strains during 2013—2015 in Xi′an. Children younger than 7 years were the main susceptible population. HAdV infections circulate all year-round and there was no considerable seasonal variation.
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Objective To apply the 'auto-regressive integrated moving average product seasonal model' in predicting the number of hand,foot and mouth disease in Shaanxi province.Methods In Shaanxi province,the trend of hand,foot and mouth disease was analyzed and tested,under the use of R software,between January 2009 and June 2015.Multiple seasonal ARIMA model was then fitted under time series to predict the number of hand,foot and mouth disease in 2016 and 2017.Results Seasonal effect was seen in hand,foot and mouth disease in Shaanxi province.A multiple seasonal ARIMA (2,1,0) × (1,1,0)12 was established,with the equation as (1-B)(1-B12)(1-1.000B)Ln(Xt) =(1-0.532B-0.363B2) (1-0.644B12-0.454B212)εt.The mean of absolute error and the relative error were 531.535 and 0.114,respectively when compared to the simulated number of patients from Jun to Dec in 2015.Results under the prediction of multiple seasonal ARIMA model showed that the numbers of patients in both 2016 and 2017 were similar to that of 2015 in Shaanxi province.Conclusion Multiple seasonal ARIMA (2,1,0) × (1,1,0)12 model could be used to successfully predict the incidence of hand,foot and mouth disease in Shaanxi province.
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Objective To apply the 'auto-regressive integrated moving average product seasonal model' in predicting the number of hand,foot and mouth disease in Shaanxi province.Methods In Shaanxi province,the trend of hand,foot and mouth disease was analyzed and tested,under the use of R software,between January 2009 and June 2015.Multiple seasonal ARIMA model was then fitted under time series to predict the number of hand,foot and mouth disease in 2016 and 2017.Results Seasonal effect was seen in hand,foot and mouth disease in Shaanxi province.A multiple seasonal ARIMA (2,1,0) × (1,1,0)12 was established,with the equation as (1-B)(1-B12)(1-1.000B)Ln(Xt) =(1-0.532B-0.363B2) (1-0.644B12-0.454B212)εt.The mean of absolute error and the relative error were 531.535 and 0.114,respectively when compared to the simulated number of patients from Jun to Dec in 2015.Results under the prediction of multiple seasonal ARIMA model showed that the numbers of patients in both 2016 and 2017 were similar to that of 2015 in Shaanxi province.Conclusion Multiple seasonal ARIMA (2,1,0) × (1,1,0)12 model could be used to successfully predict the incidence of hand,foot and mouth disease in Shaanxi province.