传染病发病率变化趋势的非线性过程分析

Non-linear Regression Analysis on Incidence of Legal Contagious Diseases

目的 利用非线性过程探讨传染病发病规律。 方法 对传染病发病率曲线进行非线性过程的幂函数拟合 ,并与用曲线参数估计法的幂函数拟合结果进行对比。 结果 利用非线性回归分析过程拟合的幂函数模型为 Y=4 2 5 .76 4 6 X- 0 .51 85,R2 =0 .96 95 ,预测精度高于用曲线参数估计法拟合的幂函数模型 (R2 =0 .94 2 9)。 结论 非线性的幂函数拟合结果相对较优 ,故更好地分析与预测深圳市龙岗区传染病发病情况。在卫生部门行之有效的防治措施下 。

Objective To explore the regularity of legal contagious disease with curve fitting model. Methods Adopting non-linear regression power model to fit the curve of incidence of infectious disease, whose result is contrast with the same model by adopting curve estimation method. Result The power non-linear regression model (Y=425 7646X -0 5185 ,R 2=0.9695) is optimum, indicates that it fits the fact better. Conclusion The non-linear regression power model is suitable for analyzing the data of incidence of infectious disease in Long Gang district of Shenzhen. With the hygiene department's effective prevention and control,the incidence tends to fall down.