ABSTRACT
Objective To study the function of X -1 2 -ARIMA model in analysis on incidence trend of typhoid. Methods Secular trend,seasonal periodicity and random fluctuations of the monthly morbidity data in Zhejiang province from 2005 to 201 3 were analyzed by X -1 2 -ARIMA model.Results The seasonal fluctuation showed a narrowing trend year by year during 2005 to 201 3.After September,2007,the incidence of typhoid showed a downward trend.After 2008,the annual peak of incidence changed from August to July.The irregular factor may well represent the outbreak. Conclusion The X -1 2 -ARIMA model showed clear secular trend and seasonal periodicity,and the random fluctuation was of great value.
ABSTRACT
<p><b>OBJECTIVE</b>To analyze and evaluate the application of China Infectious Diseases Automated-alert and Response System(CIDARS)in Zhejiang province.</p><p><b>METHODS</b>Data through the monitoring program in 2012 was analyzed descriptively and compared with the incidence data in the same period as well information related to public health emergency events.</p><p><b>RESULTS</b>A total of 14 292 signals were generated on 28 kinds of infectious diseases in the system, in Zhejiang province. 100% of the signals had been responded and the median time to response was 0.81 hours. 123 signals (0.86%)were preliminarily verified as suspected outbreaks and 33 outbreaks were finally confirmed by further field investigation, with a positive ratio of 0.23% . Information related to regional distribution showed significant differences which reflecting a positive correlation between the numbers of diseases and the time of early-warning(r = 0. 97, P < 0.01). Distribution of information related to different types of diseases was also significantly different, showing a positive correlation between the prevalent strength of the disease and the amount of information in a specific area(r = 0.80, P < 0.01).</p><p><b>CONCLUSION</b>CIDARS had a good performance which could be used to assist the local public health institutions on early detection of possible outbreaks at the early stage. However, the effectiveness was different for different regions and diseases.</p>