ABSTRACT
<p><b>OBJECTIVE</b>To analyze and further improvement the application of the China Infectious Diseases Automated-alert and Response System (CIDARS) in Guangxi Zhuang Autonomous Region.</p><p><b>METHODS</b>Results related to the amount of signal, proportion of signal responded, time to signal response, manner of signal verification and on each signal of Guangxi in CIDARS from 2009 to 2011 were described. Performance was compared between the periods of pre/ post the adjustment of parameters in CIDARS on December 10, 2010.</p><p><b>RESULTS</b>A total of 29 788 signals were generated on 16 infectious diseases in the system in Guangxi. 100% signals had been responded with the median time to response as 1.5 hours. The average amount of signal per county per week was 1.7;with 624 signals(2.09%)verified as suspected outbreaks preliminarily and 191 outbreaks of 9 diseases were finally confirmed by further field investigation. The sensitivity of CIDARS was 89.25% , and the timeliness of detection was 2.8 d. After adjusting the parameter of CIDARS, the number of signals reduced, and the sensitivity and timeliness of detection improved for most of the diseases.</p><p><b>CONCLUSION</b>The signals of CIDARS were responded timely, and the performance of CIDARS might be improved by adjusting the parameters of early-warning model, which helped enhance the ability of outbreaks-detection for local public health departments. However the current proportion of false positive signals still seemed to be high, suggesting that both the methods and parameters should be improved, according to the characteristics of different diseases.</p>
Subject(s)
Humans , China , Epidemiology , Communicable Disease Control , Methods , Communicable Diseases , Epidemiology , Disease Notification , Methods , Disease Outbreaks , Models, Theoretical , Population Surveillance , MethodsABSTRACT
<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>
Subject(s)
Humans , China , Epidemiology , Communicable Disease Control , Methods , Communicable Diseases , Epidemiology , Disease Outbreaks , Incidence , Population Surveillance , Methods , Public HealthABSTRACT
Objective To analyze the results of application on China Infectious Diseases Automated-alert and Response System(CIDARS)and for further improving the system. Methods Amount of signal, proportion of signal responded, time to signal response, manner of signal verification and the outcome of each signal in CIDARS were descriptively analyzed from July 1,2008to June 30, 2010. Results A total of 533 829 signals were generated nationwide on 28 kinds of infectious diseases in the system. 97.13% of the signals had been responded and the median time to response was 1.1 hours. Among them, 2472 signals were generated by the fixed-value detection method which involved 9 kinds of diseases after the preliminary verification, field investigation and laboratory tests. 2202 signals were excluded, and finally 246 cholera cases, 15 plague cases and 9H5N1 cases as well as 39 outbreaks of cholera were confirmed. 531 357 signals were generated by the other method - the 'moving percentile method' which involved 19 kinds of diseases. The average amount of signal per county per week was 1.65, with 6603 signals(1.24%)preliminarily verified as suspected outbreaks and 1594 outbreaks were finally confirmed by further field investigation. For diseases in CIDARS, the proportion of signals related to suspected outbreaks to all triggered signals showed a positive correlation with the proportion of cases related to outbreaks of all the reported cases (r=0.963, P＜0.01). Conclusion The signals of CIDARS were responded timely, and the signal could act as a clue for potential outbreaks, which helped enhancing the ability on outbreaks detection for local public health departments.
ABSTRACT
Objective To analyze the pilot results of both temporal and temporal-spatial models in outbreaks detection in China Infectious Diseases Automated-alert and Response System (CIDARS)to further improve the system. Methods The amount of signal, sensitivity, false alarm rate and time to detection regarding these two models of CIDARS, were analyzed from December 6,2009 to December 5,2010 in 221 pilot counties of 20 provinces. Results The sensitivity of these two models was equal(both 98.15%). However, when comparing to the temporal model, the temporal-spatial model had a 59.86% reduction on the signals(15 702)while the false alarm rate of the temporal-spatial model(0.73%)was lower than the temporal model(1.79%), and the time to detection of the temporal-spatial model(0 day)was also 1 day shorter than the temporal model.Conclusion Comparing to the temporal model, the temporal-spatial model of CIDARS seemed to be better performed on outbreak detection.
ABSTRACT
Objective To evaluate the performance of China Infectious Disease Automatedalert and Response System(CIDARS). Methods A retrospective analysis was conducted on data related to the warning signals, the outcome of signal verification, the field investigation of CIDARS,and the emergent events reported through Public Health Emergency Events Surveillance System from July 1,2008 to June 30, 2010 in Zhejiang province. The performance of CIDARS was qualitatively evaluated by indicators on its sensitivity and rote of false alarm. Results In total, 26 446 signals were generated by the system which involving 17 diseases, with an average of 2.83 signals per country per week. Among all the signals, 99.95% of them were responded. 0.90% of the signals were judged as suspected events via the preliminary verification, and 30 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 69.77% with the false alarm rate as 1.39%. Conclusion The system seemed to have worked on the outbreak early warning of infectious diseases and could directly reflect the anomaly event emerged from the infectious disease reporting system.However, more efforts should be paid to the following areas as how to decrease the false positive signals, select suitable thresholds and increase the quality of data in order to enhance the accuracy of the system.
ABSTRACT
Objective To understand the effectiveness of China Infectious Disease Automated-alert and Response System(CIDARS)for outbreak detection at the regional level.Methods Two counties in Hunan province(Yuelu and Shuangfeng county)and two counties in Yunnan province(Xishan and Gejiu county)were chosen as the study areas. Data from CIDARS were analyzed on the following items: reported cases, warning signals, the time interval of signal response feedback, way of signal verification, outcome of signal verification and field investigation, from July 1,2008 to June 30,2010. Results In total, 12 346 cases from 28 kinds of diseases were reported,and 2096 signals of 19 diseases were generated by the system, with an average of 4.94 signals per county per week. The median of time interval on signal verification feedback was 0.70 hours(P25-P75:0.06-1.29 h)and the main way of signal preliminary verification was through the review of surveillance data(account for 63.07%). Among all the signals, 34 of them(1.62%)were considered to be related to suspected events via the preliminary verification at the local level. Big differences were found to have existed on the proportion of signals related to the suspected events of the total signals among the four counties, with Shuangfeng county as 4.71%, Yuelu county as 1.88%, Gejiu county as 0.95% and Xishan county as 0.58%. After an indepth study on the fields of suspected events, 12outbreaks were finally confirmed, including 5 on rubella, 4 on mumps, 2 on influenza and 1 on typhoid fever. Conclusion CIDARS 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 depending on the regions and diseases.
ABSTRACT
Objective To compare the different thresholds of 'moving percentile method' for outbreak detection in the China Infectious Diseases Automated-alert and Response System (CIDARS). Methods The thresholds of P50, P60, P70, P80 and P90 were respectively adopted as the candidates of early warning thresholds on the moving percentile method. Aberration was detected through the reported cases of 19 notifiable infectious diseases nationwide from July 1,2008 to June 30,2010. Number of outbreaks and time to detection were recorded and the amount of signals acted as the indicators for determining the optimal threshold of moving percentile method in CIDARS. Results The optimal threshold for bacillary and amebic dysentery was P50. For non-cholera infectious diarrhea,dysentery, typhoid and paratyphoid, and epidemic mumps, it was P60. As for hepatitis A, influenza and rubella, the threshold was P70, but for epidemic encephalitis B it was P80. For the following diseses as scarlet fever, typhoid and paratyphoid, hepatitis E, acute hemorrhagic conjunctivitis, malaria, epidemic hemorrhagic fever, meningococcal meningitis, leptospirosis, dengue fever, epidemic endemic typhus,hepatitis C and measles, it was P90. When adopting the adjusted optimal threshold for 19 infectious diseases respectively, 64 840(12.20%)signals had a decrease, comparing to the adoption of the former defaulted threshold(P50)during the 2 years. However, it did not reduce the number of outbreaks being detected as well as the time to detection, in the two year period. Conclusion The optimal thresholds of moving percentile method for different kinds of diseases were different.Adoption of the right optimal threshold for a specific disease could further optimize the performance of outbreak detection for CIDARS.
ABSTRACT
Objective To compare the performance of aberration detection algorithm for infectious disease outbreaks, based on two different types of baseline data. Methods Cases and outbreaks of hand-foot-and-mouth disease (HFMD) reported by six provinces of China in 2009 were used as the source of data. Two types of baseline data on algorithms of C1 ,C2 and C3 were tested, by distinguishing the baseline data of weekdays and weekends. Time to detection (TTD) and false alarm rate (FAR) were adopted as two evaluation indices to compare the performance of 3 algorithms based on these two types of baseline data. Results A total of 405 460 cases of HFMD were reported by 6 provinces in 2009. On average,each county reported 1.78 cases per day during the weekdays and 1.29 cases per day during weekends, with significant difference (P<0.01) between them. When using the baseline data without distinguish weekdays and weekends, the optimal thresholds for C1, C2 and C3 was 0.2,0.4 and 0.6 respectively while the TTD of C1,C2 and C3 was all 1 day and the FARs were 5.33% ,4.88% and 4.50% respectively. On the contrast, when using the baseline data to distinguish the weekdays and weekends, the optimal thresholds for C1, C2 and C3 became 0.4,0.6 and 1.0 while the TTD of Cl,C2 and C3 also appeared equally as 1 day.However, the FARs became 4.81%,4.75% and 4.16% respectively, which were lower than the baseline data from the first type. Conclusion The number of HFMD cases reported in weekdays and weekends were significantly different, suggesting that when using the baseline data to distinguish weekdays and weekends, the FAR of C1, C2 and C3 algorithm could effectively reduce so as to improve the accuracy of outbreak detection.
ABSTRACT
In recent years, for improving the ability of early detection on infectious disease outbreak, many researchers study the disease outbreak detection algorithms, based on many disease surveillance data, expecting to detect the abnormal increasing and cluster of disease and symptom at an early stage by adopting appropriate algorithm. This paper introduces a cumulative sum control chart method, one of statistical process control algorithms widely used in foreign countries and describes its basic principle and characteristic, key points of design, typical examples in application of disease outbreak detection of cumulative sum method, with expect to provide reference for its application in studies of disease outbreak early warning in China.