论文部分内容阅读
目的探讨改良的serfling回归模型在北京市房山区感染性腹泻监测预警中的应用。方法建立房山区其他感染性腹泻serfling回归模型,应用迭代回归方法对其他感染性腹泻serfling回归模型进行改良,并与传统serfling回归预警方法进行比较。结果改良的serfling回归模型为Y=24.588+7.167 10-8t3-10.596 sin(2πt/52)-20.579 cos(2πt/52)+2.2sin(4πt/52)+8.777cos(4πt/52)(F=430.185,P<0.05),拟合优度检验R2=0.944。预警的信号优于传统方法。结论改良的serfling回归模型能够很好地拟合房山区其他感染性腹泻周发病数据,可用于房山区其他感染性腹泻的监测预警,为下一步采取针对性防控措施提供科学依据。
Objective To investigate the application of the improved serfling regression model in monitoring and early warning of infectious diarrhea in Fangshan District of Beijing. Methods The serfling regression model of other infectious diarrhea in Fangshan District was established. The serfling regression model of other infectious diarrhea was improved by iterative regression method, and compared with the traditional serfling regression prediction method. Results The improved serfling regression model was Y = 24.588 + 7.167 10-8t3-10.596 sin (2πt / 52) -20.579 cos (2πt / 52) + 2.2sin (4πt / 52) + 8.777 cos (4πt / 52) 430.185, P <0.05), goodness of fit test R2 = 0.944. Early warning signals outperform traditional methods. Conclusion The improved serfling regression model can well fit the data of other infectious diarrhea weeks in Fangshan District, which can be used for monitoring and early warning of other infectious diarrhea in Fangshan District and provide a scientific basis for targeted prevention and control measures in the next step.