Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

OBJECTIVETo explore the effect of signal strength indictor (SSI) in improving sensitivity of China Infectious Diseases Automated-alert and Response System (CIDARS).

METHODSDiarrhea cases in 2007-2011 and early warning signals in 2010-2011 were selected by using random digital table method. Then, SSI and event-related ratio (ER) were calculated. The relationship between ER and SSI was analyzed, and the effect of SSI on ER was explored by using multiple logistic regression analysis.

RESULTS9 620 early warning signals in 2010-2011 were generated in two years. Of these, 74, or 0.77% were defined as suspected outbreak signal. The median of SSI related with suspected outbreak signal was 4.0, which was much higher than non-suspected outbreak signal (1.7). ER was significantly correlated with SSI (r=0.917). SSI classification has a good correlation between the ER, ER exceeded 20 after SSI reached 20. The multivariate logistic regression analysis showed OR of SSI related with suspected outbreak signal was 2.52 (95% CI 2.04-3.12). Compared with non-epidemic season, the relationship of SSI and ER in epidemic season was much higher.

CONCLUSIONSSI was closely related with ER. The relationship was much closer in large scale outbreak and epidemic season, and compared to non-epidemic,the effect of epidemic season is more obvious.

China ; Communicable Diseases ; diagnosis ; epidemiology ; Diarrhea ; diagnosis ; epidemiology ; Disease Outbreaks ; Humans ; Population Surveillance

Objective: To understand characteristics of demographic, seasonal and spatial distribution of H5N1 cases in major countries of Asia (Indonesia, Cambodia, Vietnam, China) and Africa (Egypt). Methods: Through searching public data resource and published papers, we collected cases information in five countries from May 1st, 1997 to November 6th, 2017, including general characteristics, diagnosis, onset and exposure history, etc. Different characteristics of survived and death cases in different countries were described and χ² test was used to compare the differences among death cases and odds ratio (OR) and 95%CI value was used to compare death risk in different countries. Results: A total of 856 cases were reported in five countries with Egypt had the most cases (44.3%). The highest number of cases were reported in 2015 (18.3%). 53% cases were reported from January to March, and 96.1% of cases had the history of poultry exposure. 64.2% (43 cases) cases in China had live poultry market exposure, but the sick/dead poultry exposure was the major exposure for cases in other four countries. 452 death cases were reported in five countries, and the fatality rate was 52.8%. With Egypt as the reference group, the highest death risk was seen in Indonesia (OR (95%CI): 11.52 (7.46-17.77)), followed by Cambodia (OR (95%CI): 4.27(2.37-7.69)) and China (OR (95%CI): 2.87 (1.73-4.74)). The age distribution of death cases among 5 countries was statistically significant, and the highest fatality rate was in 15-54 years group in Egypt (83.6%, 102 cases), while in Cambodia the highest fatality rate was in 0-14 years group (76.9%, 30 cases). The highest number of deaths were reported in 2006, and 48.3% were reported from January to March. There was difference in exposure routes among 5 countries (χ²=43.85, P=0.001), 63.2% (24 cases) of the death cases in China had live poultry market exposure. 92.9% (79 cases), 83.3% (40 cases) and 100.0% (38 cases) death cases in Indonesia, Vietnam and Camodia had sick/dead poultry exposure, respectively;and 81.6% (31 cases) of the death cases in Egypt had backyard poultry exposure. Conclusion The geographical distribution, seasonal age, gender, exposure matter and outcome of H5N1 cases in five countries were different.

This paper summarizes the basic principles and models of early warning for infectious disease outbreaks, introduces the early warning systems for infectious disease based on different data sources and their applications, and discusses the application potential of big data and their analysing techniques, which have been studied and used in the prevention and control of COVID-19 pandemic, including internet inquiry, social media, mobile positioning, in the early warning of infectious diseases in order to provide reference for the establishment of an intelligent early warning mechanism and platform for infectious diseases based on multi-source big data.

Intelligent syndromic surveillance is an important part of multi-point triggering and multi-channel surveillance system of intelligent early warning of infectious diseases in China, and an inevitable development process of traditional syndromic surveillance as the constant emergence of new technologies. Intelligent syndromic surveillance collects not only the medical data of patients seeking medical care in hospitals but also massive non-medical information. However, along with its rapid development, challenges in intelligent syndromic surveillance have emerged, such as information explosion, cost-effective balance, information sharing, data security and privacy. This paper summarizes the concept and development of intelligent syndromic surveillance to provide references for the method and technique development of intelligent early warning of infectious diseases and new thought for the prevention and control of infectious diseases in China and in the world.

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

Objective:To determine the predictive value of preoperative monocyte-to-lymphocyte ratio(MLR) for prognosis in elderly patients with upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy(RNU).Methods:A retrospective study was performed on 168 elderly patients who underwent RNU in Beijing Hospital between March 2004 to February 2019.Males accounted for 44.6% (75 patients) and females 55.4%(93 patients) of the patients. Median age at the time of surgery was 73(69-78) years, and 110 (65.5%) patients suffered from hydronephrosis. There were 147 cases(87.5%)with single tumor, and 21 cases(12.5%)with multiple tumors, including 75(46.6%) cases in renal pelvis or pelvi-ureteric junction, and 93(53.4%)cases in ureter. Open RNU was performed in 106(63.1%) patients, and laparoscopic method in 62(32.9%) patients. The optimal cutoff value of MLR was set as 0.22 by using the median.χ 2 test, which was used to detect the association between MLR(≤0.22 vs.>0.22) and clinicopathological variables. Survival analyses were performed using the Kaplan-Meier method and were compared using the log-rank test. Additional subgroup analyses(low grade vs. high grade) were performed according to pathological grade. Univariate and multivariate analysis by Cox’s proportional hazards model was used to determine the significance of MLR in respect to OS and PFS. Results:The follow-up period ranged from 19.2 to 86.9 months (median 51.9 months). Next, the cohort was divided into 2 groups , including 77 patients with low MLR(≤0.22) and 91 patients with high MLR(>0.22). High MLR was significantly more frequent in male patients(31.2% vs.56.0%), as well as those undergoing laparoscopic surgery (54.5% vs.70.3%)(All P<0.05). Based on a Cox univariate proportional hazards analysis, male gender( HR=1.793, 95% CI 1.003-3.205, P=0.049), presence of lymph node metastasis( HR=6.809, 95% CI 2.124-17.454, P=0.001) and high MLR( HR=2.287, 95% CI 1.259-4.154, P=0.007)were associated with poor OS. Male gender( HR=1.758, 95% CI 1.066-2.902, P=0.027), presence of lymph node metastasis( HR=6.524, 95% CI 2.542-16.748, P<0.001), lymphovascular invasion(LVI) ( HR=2.348, 95% CI 1.139-4.838, P=0.021), high MLR( HR=2.801, 95% CI 1.657-4.735, P<0.001)and PLR( HR=1.663, 95% CI 1.003-2.757, P=0.049) were significantly associated with subsequent PFS. By multivariate analysis, tumor site( HR=2.050, 95% CI 1.079-3.892, P=0.028), lymph node metastasis ( HR=6.641, 95% CI 1.852-23.811, P=0.004) and MLR( HR=2.089, 95% CI 1.062-4.113, P=0.033) were the independent risk factors for OS in elderly patients with UTUC. Tumor side( HR=2.024, 95% CI 1.033-3.965, P=0.040), multifocality ( HR=2.992, 95% CI 1.161-7.713, P=0.023), lymph node metastasis ( HR=6.454, 95% CI 2.026-20.564, P=0.002) and MLR( HR=2.866, 95% CI 1.554-5.284, P=0.001) were associated with PFS.The multivariate analysis of the significant risk factors established a postoperative risk stratification model for OS and PFS. The results showed significant differences among the 3 subgroups of patients with low(0 risk factor), intermediate(1 risk factor), or high risk(2-3 risk factors)(All P<0.05). Conclusion:MLR was an independent risk factor for OS and PFS in elderly patients with UTUC and patients with elevated MLR have worsen prognosis.

Objective To analyze the viral etiologies of hospitalized pneumonia patients aged less than five years in six provinces during 2009-2012,and to describe the seasonality of the detected viral etiologies. Methods Eight hospitals were selected in six provinces from a national acute respiratory infection surveillance network. Demographic information,clinical history and physical examination,and laboratory testing results of the enrolled hospitalized patients aged less than five years with pneumonia,including respiratory syncytial virus (RSV),human influenza virus, adenoviruses(ADV),human parainfluenza virus(PIV),human metapneumovirus(hMPV),human coronavirus(hCoV)and human bocavirus(hBoV)were analyzed. The viral etiology spectrum of the enrolled patients was analyzed by age-group,year,and seasonality of the detected viral etiologies were described. Results 4 508 hospitalized children less than five years old,with pneumonia from 8 hospitals were included,and 2 688(59.6%)patients were positive for at least one viral etiology. The most frequent detected virus was RSV(21.3%),followed by PIV(7.1%)and influenza(5.2%),hBoV (3.8%),ADV(3.6%)and hMPV(2.6%). The lowest positive rates in hCoV(1.1%). RSV,influenza, PIV,hBoV and hMPV all showed the nature of seasonality. Conclusion RSV was a most common viral etiology in the hospitalized young children less than 5 years of age with pneumonia. Prevention measures should be conducted to decrease its severe impact to the young infants and children in China.