Construction of ARIMA time series model for healthcareassociated infection in hospitalized children
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R181.3+2

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    Abstract:

    ObjectiveTo investigate the applicability of autoregressive integrated moving average (ARIMA) model in predicting healthcareassociated infection(HAI) in children. MethodsThe ARIMA model was constructed according to the incidence of HAI in a hospital from January 2011 to December 2014. With the use of information criterion, optimal model was determined; HAI data in 2015 was as test samples, the feasibility of the model was evaluated. ResultsARIMA (0,1,1) was the optimal prediction model for HAI rate, the Akaike Information Criterion(AIC)and Bayesian Information Criterion(BIC)of the ARIMA(0,1,1) were 66.61 and 70.76, respectively. The LjungBox statistics value Q= 14.14 was not significantly different (P= 0.658), suggesting a white noise sequence of residuals with a good model fitting. The mean absolute percent error(MAPE) between actual and fitting value of HAI was 22.4, the actual values were within the 95% confidence interval. ConclusionARIMA model fits the time series data, and can achieve satisfactory effect on predicting the incidence of HAI in hospitalized children.

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刘海鹏,金玉莲,刘光辉,等.住院患儿医院感染发生率ARIMA时间序列模型[J].中国感染控制杂志英文版,2017,16(3):243-246. DOI:10.3969/j. issn.1671-9638.2017.03.014.
LIU Haipeng, JIN Yulian, LIU Guanghui, et al. Construction of ARIMA time series model for healthcareassociated infection in hospitalized children[J]. Chin J Infect Control, 2017,16(3):243-246. DOI:10.3969/j. issn.1671-9638.2017.03.014.

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History
  • Received:May 30,2016
  • Revised:June 25,2016
  • Adopted:
  • Online: March 31,2017
  • Published: