2010-2015年耐甲氧西林金黄色葡萄球菌医院流行趋势时间序列分析
发布时间：2018-08-15 15:38
【摘要】：目的探讨应用时间序列求和自回归滑动平均模型(ARIMA)进行耐甲氧西林金黄色葡萄球菌(MRSA)流行趋势预测的可行性,为降低MRSA定植或感染提供理论依据。方法使用2010-2014年浙江医院MRSA检出率拟合ARIMA模型,以2015年1-12月MRSA实际检出率作为预测模型的考核样本,验证模型的预测效果。结果 MRSA检出率ARIMA模型为Xt=0.3807Xt-1+Xt-12-0.3807Xt-13-0.02725;模型预测的平均相对误差为20.19%,预测的动态趋势与实际值基本吻合。结论 ARIMA模型对MRSA检出率拟合较为满意,预测效果良好,可为临床早期采取防控措施提供依据。
[Abstract]:Objective to explore the feasibility of predicting the trend of (MRSA) prevalence of methicillin-resistant Staphylococcus aureus by using time series summation autoregressive moving average model (ARIMA) and to provide a theoretical basis for reducing MRSA colonization or infection. Methods the MRSA positive rate of Zhejiang Hospital from 2010 to 2014 was used to fit the ARIMA model, and the actual detection rate of MRSA from January to December 2015 was used as the test sample to verify the prediction effect of the model. Results the ARIMA model of MRSA detection rate was Xt=0.3807Xt-1 Xt-12-0.3807Xt-13-0.02725, the average relative error of the model was 20.19, and the predicted dynamic trend was basically consistent with the actual value. Conclusion the ARIMA model is satisfactory in fitting the detection rate of MRSA, and can provide evidence for early clinical prevention and control.
【作者单位】： 浙江医院医院感染管理科;浙江医院医学检验科;
【基金】：浙江医院医药卫生科学研究基金项目(2015YJ008)
【分类号】：R446.5
，
本文编号：2184653
[Abstract]:Objective to explore the feasibility of predicting the trend of (MRSA) prevalence of methicillin-resistant Staphylococcus aureus by using time series summation autoregressive moving average model (ARIMA) and to provide a theoretical basis for reducing MRSA colonization or infection. Methods the MRSA positive rate of Zhejiang Hospital from 2010 to 2014 was used to fit the ARIMA model, and the actual detection rate of MRSA from January to December 2015 was used as the test sample to verify the prediction effect of the model. Results the ARIMA model of MRSA detection rate was Xt=0.3807Xt-1 Xt-12-0.3807Xt-13-0.02725, the average relative error of the model was 20.19, and the predicted dynamic trend was basically consistent with the actual value. Conclusion the ARIMA model is satisfactory in fitting the detection rate of MRSA, and can provide evidence for early clinical prevention and control.
【作者单位】： 浙江医院医院感染管理科;浙江医院医学检验科;
【基金】：浙江医院医药卫生科学研究基金项目(2015YJ008)
【分类号】：R446.5
，
本文编号：2184653
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