Objective: To optimize the warning threshold values of common communicable diseases in Gansu province, and improve the early warning effect. Method: An early warning model was set up for influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and hand foot and mouth disease (HFMD) respectively in Gansu by using the moving percentile method and cumulative sum method. By calculating the sensitivity, specificity, predictive value of positive test, predictive value of negative test, Youden' index and receiver-operating characteristic curve, the optimum early warning threshold values for communicable diseases in Gansu were selected. Results: The optimum early warning boundary values of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, and viral hepatitis type E were P(90), P(80), P(95), P(90), P(80) and P(90) respectively. The optimum early warning parameters of HFMD were k=1.2, H=5σ. Under the optimum early warning boundary values/parameters, the early warning sensitivities of influenza, scarlet fever, other infectious diarrheal diseases, dysentery, typhoid and paratyphoid, viral hepatitis type E and HFMD were 86.67%, 100.00%, 91.67%, 100.00%, 100.00%, 100.00% and 100.00%, the specificities were 86.49%, 62.22%, 75.00%, 100.00%, 97.92%, 89.13% and 74.47%. The predictive values of positive test were 72.22%, 29.17%, 52.38%, 100.00%, 80.00%, 54.55% and 29.41%, and the predictive values of negative test were 94.12%, 100.00%, 96.77%, 100.00%, 100.00%, 100.00% and 100.00%, and the Youden' indexes were 0.73, 0.62, 0.67, 1.00, 0.98,0.89 and 0.74. Receiver-operating characteristic curve showed that the values/parameters of this warning boundary were the points closest to the upper left of the coordinate diagram. Conclusion: The early warning thresholds of influenza, other infectious diarrheal diseases, dysentery and hepatitis E in Gansu may be raised appropriately and the early warning parameters of HFMD need to be adjusted to improve the effectiveness of early warning.
China ; Communicable Disease Control/methods* ; Communicable Diseases/epidemiology* ; Disease Notification ; Disease Outbreaks/prevention & control* ; Humans ; Models, Theoretical ; Population Surveillance/methods*

Objective: To analyze the epidemiological characteristics of notifiable infectious diseases among Chinese students from 2011 to 2016 and to provide reference for the effective prevention and control programs on infectious disease among students. Methods: Both morbidity and mortality of notifiable infectious diseases among Chinese students aged 6-22 years from 2011 to 2016 were analyzed, with main characteristics of the disease described. Results: During 2011 to 2016, morbidities of Categories A, B and C infectious diseases among the Chinese students aged 6-22 years showed a decreasing trend, from 248.24/100 000 in 2012 to 158.57/100 000 in 2016. Mortality rates of Category A, B and C infectious diseases had also decreased from 0.12/100 000 in 2011 to 0.07/100 000 in 2016. The average morbidity of the top four diseases from Category A and B infectious diseases appeared as: tuberculosis (16.24/100 000), scarlet fever (9.39/100 000), hepatitis B (7.69/100 000) and bacillary and amebic dysentery (7.15/100 000). The average rates of mortality on the top four diseases appeared as: rabies (0.044 8/100 000), HIV/AIDS (0.027 7/100 000), tuberculosis (0.008 0/100 000) and Japanese encephalitis (0.005 9/100 000). The average rates of morbidity on the top four diseases appeared as: mumps (75.81/100 000), hand-foot-mouth disease (28.55/100 000), other infectious diarrhea (22.41/100 000) and influenza (15.67/100 000) in the Category C. Reported death cases were from hand-foot-mouth disease (11 cases), influenza (9 cases), mumps (1 case) and rubella (1 case). The prevalence rates varied among different student populations, with higher HIV/AIDS, hepatitis B and tuberculosis rates among college and senior high school students, while higher mumps, influenza and hand-foot-mouth disease rates among primary school and junior high school students. Conclusions: Both morbidity and mortality of notifiable infectious diseases among Chinese students aged 6-22 years had decreased significantly in 2011-2016. However, the major infectious diseases had become new challenges among students. HIV/AIDS had become a key infectious disease among college students and the relatively high prevalence of tuberculosis was seen in college and high school students.
Adolescent ; Child ; China/epidemiology* ; Communicable Diseases/epidemiology* ; Disease Notification/statistics & numerical data* ; Humans ; Population Surveillance/methods* ; Prevalence ; Students/statistics & numerical data* ; Young Adult

OBJECTIVETo explore the appropriate early warning method for influenza epidemic in Gansu province.

METHODSBy using simple control chart, moving percentile method, exponential smoothing method and cumulative sum control chart method, the annual incidence data of influenza-like illness in Gansu province during 2014-2015 were analyzed, and the sensitivities, specificities, positive predictive values, Jorden indexes and Kappa values of the 4 methods were evaluated and compared.

RESULTSThe 2014-2015 seasonal influenza epidemic occurred in the fiftieth week of 2014 in Gansu, and the epidemic peak lasted for 6 weeks. Cumulative sum control chart method had the best early warning effect with the sensitivity of 66.67% and specificity of 93.48%.

CONCLUSIONIt is feasible to use cumulative sum control chart method to give early warning of influenza epidemic in Gansu.

China ; epidemiology ; Disease Notification ; methods ; Epidemics ; Feasibility Studies ; Humans ; Influenza, Human ; epidemiology ; Seasons

OBJECTIVEProviding evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) via analyzing the outbreak detection performance of Moving Percentile Method (MPM) by optimizing thresholds in different provinces.

METHODSWe collected the amount of MPM signals, response results of signals in CIDARS, cases data in nationwide Notifiable Infectious Diseases Reporting Information System, and outbreaks data in Public Health Emergency Reporting System of 16 infectious diseases in 31 provinces in Chinese mainland from January 2011 to October 2013. The threshold with the optimal sensitivity, the shortest time to detect outbreak and the least number of signals was considered as the best threshold of each disease in Chinese mainland and in each province.

RESULTSAmong all the 16 diseases, the optimal thresholds of 10 diseases, including dysentery, dengue, hepatitis A, typhoid and paratyphoid, meningococcal meningitis, Japanese encephalitis, scarlet fever, leptospirosis, hepatitis, typhus in country level were the 90(th) percentile (P90), which was the same as provincial level for those diseases.For the other 6 diseases, including other infectious diarrhea, influenza, acute hemorrhagic conjunctivitis, mumps, rubella and epidemic hemorrhagic fever, the nationwide optimal thresholds were the 80th percentile (P80), which was different from that by provinces for each disease. For these 6 diseases, the number of signals generated by MPM with the optimal threshold for each province was decreased by 23.71% (45 557), 15.59% (6 124), 14.07% (1 870), 9.44% (13 881), 8.65% (1 294) and 6.03% (313) respectively, comparing to the national optimal threshold, while the sensitivity and time to detection of CIDARS were still the same.

CONCLUSIONOptimizing the threshold by different diseases and provinces for MPM in CIDARS could reduce the number of signals while maintaining the same sensitivity and time to detection.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Population Surveillance ; methods

OBJECTIVEFor providing evidences for further modification of China Infectious Diseases Automated-alert and Response System (CIDARS) by comparing the early-warning performance of the temporal model and temporal-spatial model in CIDARS.

METHODSThe application performance for outbreak detection of temporal model and temporal-spatial model simultaneously running among 208 pilot counties in 20 provinces from 2011 to 2013 was compared; the 16 infectious diseases were divided into two classes according to the disease incidence level; cases data in nationwide Notifiable Infectious Diseases Reporting Information System was combined with outbreaks reported to Public Health Emergency Reporting System, by adopting the index of the number of signals, sensitivity, false alarm rate and time for detection.

RESULTSThe overall sensitivity of temporal model and temporal-spatial model for 16 diseases was 96.23% (153/159) and 90.57% (144/159) respectively, without significant difference (Z = -1.604, P = 0.109), and the false alarm rate of temporal model (1.57%, 57 068/3 643 279) was significantly higher than that of temporal-spatial model (0.64%, 23 341/3 643 279) (Z = -3.408, P = 0.001), while the median time for detection of these two models was not significantly different, which was 3.0 days and 1.0 day respectively (Z = -1.334, P = 0.182).For 6 diseases of type I which represent the lower incidence, including epidemic hemorrhagic fever,Japanese encephalitis, dengue, meningococcal meningitis, typhus, leptospirosis, the sensitivity was 100% for both models (8/8, 8/8), and the false alarm rate of both temporal model and temporal-spatial model was 0.07% (954/1 367 437, 900/1 367 437), with the median time for detection being 2.5 days and 3.0 days respectively. The number of signals generated by temporal-spatial model was reduced by 2.29% compared with that of temporal model.For 10 diseases of type II which represent the higher incidence, including mumps, dysentery, scarlet fever, influenza, rubella, hepatitis E, acute hemorrhagic conjunctivitis, hepatitis A, typhoid and paratyphoid, and other infectious diarrhea, the sensitivity of temporal model was 96.03% (145/151), and the sensitivity of temporal-spatial model was 90.07% (136/151), the number of signals generated by temporal-spatial model was reduced by 59.36% compared with that of temporal model. Compared to temporal model, temporal-spatial model reduced both the number of signals and the false alarm rate of all the type II diseases;and the median of outbreak detection time of temporal model and temporal-spatial model was 3.0 days and 1.0 day, respectively.

CONCLUSIONOverall, the temporal-spatial model had better outbreak detection performance, but the performance of two different models varies for infectious diseases with different incidence levels, and the adjustment and optimization of the temporal model and temporal-spatial model should be conducted according to specific infectious disease in CIDARS.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Models, Theoretical ; Population Surveillance ; methods ; Spatio-Temporal Analysis

OBJECTIVETo analyze the implement performance of China Infectious Diseases Automated-alert and Response System (CIDARS) of 31 provinces in mainland China, and to provide the evidences for further promoting the application and improvement of this system.

METHODSThe amount of signals, response situation and verification outcome of signals related to 32 infectious diseases of 31 provinces in mainland China in CIDARS were investigated from 2011 to 2013, the changes by year on the proportion of responded signals and timeliness of signal response were descriptively analyzed.

RESULTSA total of 960 831 signals were generated nationwide on 32 kinds of infectious diseases in the system, with 98.87% signals (949 936) being responded, and the median (the 25(th) percentile to the 75(th) percentile (P25-P75) ) of time to response was 1.0 (0.4-3.3) h. Among all the signals, 242 355 signals were generated by the fixed-value detection method, the proportion of responded signals was 96.37% (62 349/64 703), 98.75% (68 413/69 282) and 99.37% (107 690/108 370), respectively, and the median (P25-P75) of time to response was 1.3 (0.3-9.7), 0.8(0.2-4.9) and 0.7 (0.2-4.2) h, respectively. After the preliminary data verification, field investigation and laboratory test by local public health staffs, 100 232 cases (41.36%) were finally confirmed.In addition, 718 476 signals were generated by the temporal aberration detection methods, and the average amount of signal per county per week throughout the country were 1.53, and 8 155 signals (1.14%) were verified as suspected outbreaks. During these 3 years, the proportion of signal response was 98.89% (231 149/233 746), 98.90% (254 182/257 015) and 99.31% (226 153/227 715), respectively, and the median (P25-P75) of time to response was 1.1 (0.5-3.3), 1.0 (0.5-2.9) and 1.0 (0.5-2.6) h, respectively.

CONCLUSIONFrom 2011 to 2013, the proportion of responded signals and response timeliness of CIDARS maintained a rather high level, and further presented an increasing trend year by year. But the proportion of signals related to suspected outbreaks should be improved.

China ; Communicable Diseases ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Population Surveillance ; methods

Communicable Disease Control ; Communicable Diseases ; Disease Notification ; Humans ; Population Surveillance ; methods

OBJECTIVETo select the premium alert threshold for major communicable disease by using the control graph alert technique based on the local disease information.

METHOD8 major communicable diseases in Songjiang district were ascertained by analysis of the national early warning detection information system which include the other diarrhea, mumps, chickenpox, scarlet fever, rubella, hand foot mouth disease, influenza and dysentery; weekly reported cases from 2008 to 2011 were used to establish the early detection model (PERCENTILE (array, x), array (4×5), x = 0.05, 0.10…0.95) by moving percentile method, next applying the established early detection model and the golden standard (AKX(-)D ± 2s) to predict the expected weekly cases in 2012 respectively, and then ascertain the predict results by comparison with the actual weekly cases in 2012 respectively, finally the premium threshold was selected by comparison of the model predicted results with the golden standard predicted results after comprehensive consideration of the sensitivity, specificity, positive predictive value and negative predictive value and receiver operating characteristic (ROC) curve.

RESULTSThe premium alert threshold for mumps, other diarrhea and rubella was P90, dysentery was P75, scarlet fever and chickenpox was P80, and the premium threshold for hand-foot-mouth disease (HFMD) and influenza was P95, the sensitivity of 8 major communicable diseases were 100%, 100%, 86%, 100%, 100%, 100%, 94%, 100%, respectively; the specificities were 92%, 73%, 72%, 77%, 73%, 92%, 66%, 80%, respectively; the positive predictive values were 43%, 40%, 32%, 8%, 24%, 20%, 59%, 47%, respectively; and the negative predictive values were 100%, 100%, 97%, 100%, 100%, 100%, 96%, 100%, respectively. The national recommended alert thresholds for the 8 major communicable diseases were P80, except for chickenpox (P50) and HFMD (CUSUM).

CONCLUSION6 out of 8 major communicable diseases' early detection thresholds in Songjiang district should be adjusted according to the analysis results. Premium alert threshold selection need to consider the local disease report and the characteristics of infectious diseases to upgrade the early detection capability.

China ; epidemiology ; Communicable Disease Control ; methods ; Communicable Diseases ; epidemiology ; Disease Notification ; Disease Outbreaks ; prevention & control ; Humans ; Models, Theoretical ; Population Surveillance ; methods

Cardiovascular Diseases ; China ; Disease Notification ; methods ; Humans ; United States

OBJECTIVETo describe the experience of the China CDC in rebuilding reporting capacity and response to the Sichuan earthquake through use of mobile phones.

METHODSSoftware engineering and business modeling are used to design and develop a cell phone-based reporting system. The PDA-based system used by the Field Adapted Survey Toolkit (FAST) was deployed

RESULTSApproximately one week after deployment of the mobile phone-based reporting system, the cumulative reporting rate reached the same level (81%) as the same period in 2007. In the Sichuan provincial pilot investigation for infectious disease, 1339 records were collected using PDAs developed and deployed by FAST.

CONCLUSIONThe mobile-based system is recognized as a quick and effective response solution to this public health challenge. Our experience suggests that mobile-based data collection tools provide faster, cleaner, standardized, and shareable data for critical decision making. This system could be adapted as complementary to national infectious disease reporting systems after natural disaster occurrences.

Cell Phone ; China ; Communicable Diseases ; epidemiology ; Disease Notification ; methods ; Earthquakes ; Emergencies ; Humans ; Population Surveillance ; methods