摘要
目的 进一步论证疾病流行中“Z- D 现象”的存在,并探讨其与病种和时间序列的关系。方法 利用1975~1996 年全国疫情资料,建立了麻疹、猩红热两种疾病1975 ~1995 年、1980~1995 年、1985 ~1995 年和1990~1995 年4 个不同长度的时间序列,进行最佳截取点的月累计百分位数与前兆升降比的相关分析,并通过构建外推模型进行了预测研究。结果 相关分析显示:在上述两种疾病4 个时间序列共236 份资料中,98 .3 % 的资料R< 0(232/236) ,这进一步论证了疾病流行中“Z- D现象”的存在。从时间序列来看,R< 0,P< 0 .05 的资料在上述4 个时间序列中所占比例分别为:63.8% 、54.2% 、44.1% 、35 .0 % ,四者之间差异有显著性(χ2 = 10.86 ,P< 0.05)。从病种来看,麻疹R< 0,P< 0 .05 的资料,在上述4 个时间序列中所占比例分别为:73.3% 、56.7% 、36.7% 、36 .7 % ,四者之间差异有显著性(χ2 = 11 .16,P< 0 .05) ;猩红热为:53 .6 % 、51.8% 、51.7% 、33.3% 。说明“Z- D现象”与时间序列。
Objective To demonstrate further the existence of Zeng-Ding phenomenon in disease epidemic and to explore the relationship between it and the time series in different kinds of diseases. Methods Incidence data of notifiable communicable diseases during 1975 to 1996 were collected. Time series of measles and scarlet fever incidence during 1975 to 1995,1980 to 1995, 1985 to 1995 and 1990 to 1995 were established. Correlation analysis was conducted between monthly cumulative percentage and predictive ratio of increase to decrease in incidence rate at the best cut-off point. Prediction was studied based on the constructed extrapolation model. Results Correlation analysis showed that 98.3 % (232/236) of the coefficients of correlation were negative (R<0),indicating further the existence of Zeng-Ding phenomenon in disease epidemic. There was significant difference in coefficients of correlation between the four time series, which accounted for 63.8%, 54.2 %,44.1% and 35.0%, respectively;and for 73.3%,56.7%,36.7% and 36.7%, respectively, in measles, and for 53.6%,51.8%,51.7% and 33.3%, respectively, in scarlet fever. It showed that Zeng-Ding phenomenon correlated with the time series and the kinds of diseases. Prediction from extrapolation model showed that there was significant difference in predictive agreement between two time series of 1975 to 1995 (65.5%) and 1985 to 1995 (37.0%) with χ 2 of 4.54 and P <0.05,indicating a trend that predictive agreement increased with prolonging of time series, and a trend that predictive agreement for scarlet fever increased with decreasing of coefficients of correlation. Conclusion Predictive value of the incidence data can be evaluated by their source and length of time series.
出处
《中华流行病学杂志》
CAS
CSCD
北大核心
1999年第4期200-203,共4页
Chinese Journal of Epidemiology