Etiological and epidemiological features of acute meningitis or encephalitis in China: a nationwide active surveillance study.

BACKGROUND: Acute meningitis or encephalitis (AME) results from a neurological infection causing high case fatality and severe sequelae. AME lacked comprehensive surveillance in China. METHODS: Nation-wide surveillance of all-age patients with AME syndromes was conducted in 144 sentinel hospitals of 29 provinces in China. Eleven AME-causative viral and bacterial pathogens were tested with multiple diagnostic methods. FINDINGS: Between 2009 and 2018, 20,454 AME patients were recruited for tests. Based on 9,079 patients with all-four-virus tested, 28.43% (95% CI: 27.50%‒29.36%) of them had at least one virus-positive detection. Enterovirus was the most frequently determined virus in children <18 years, herpes simplex virus and Japanese encephalitis virus were the most frequently determined in 18-59 and ≥60 years age groups, respectively. Based on 6,802 patients with all-seven-bacteria tested, 4.43% (95% CI: 3.94%‒4.91%) had at least one bacteria-positive detection, Streptococcus pneumoniae and Neisseria meningitidis were the leading bacterium in children aged <5 years and 5-17 years, respectively. Staphylococcus aureus was the most frequently detected in adults aged 18-59 and ≥60 years. The pathogen spectrum also differed statistically significantly between northern and southern China. Joinpoint analysis revealed age-specific positive rates, with enterovirus, herpes simplex virus and mumps virus peaking at 3-6 years old, while Japanese encephalitis virus peaked in the ≥60 years old. As age increased, the positive rate for Streptococcus pneumoniae and Escherichia coli statistically significantly decreased, while for Staphylococcus aureus and Streptococcus suis it increased. INTERPRETATION: The current findings allow enhanced identification of the predominant AME-related pathogen candidates for diagnosis in clinical practice and more targeted application of prevention and control measures in China, and a possible reassessment of vaccination strategy. FUNDING: China Mega-Project on Infectious Disease Prevention and the National Natural Science Funds.

Implementation of Thermal Camera for Non-Contact Physiological Measurement: A Systematic Review.

Non-contact physiological measurements based on image sensors have developed rapidly in recent years. Among them, thermal cameras have the advantage of measuring temperature in the environment without light and have potential to develop physiological measurement applications. Various studies have used thermal camera to measure the physiological signals such as respiratory rate, heart rate, and body temperature. In this paper, we provided a general overview of the existing studies by examining the physiological signals of measurement, the used platforms, the thermal camera models and specifications, the use of camera fusion, the image and signal processing step (including the algorithms and tools used), and the performance evaluation. The advantages and challenges of thermal camera-based physiological measurement were also discussed. Several suggestions and prospects such as healthcare applications, machine learning, multi-parameter, and image fusion, have been proposed to improve the physiological measurement of thermal camera in the future.

Etiological and epidemiological features of acute respiratory infections in China.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.

Coronavirus disease 2019 outbreak in Beijing's Xinfadi Market, China: a modeling study to inform future resurgence response.

BACKGROUND: A local coronavirus disease 2019 (COVID-19) case confirmed on June 11, 2020 triggered an outbreak in Beijing, China after 56 consecutive days without a newly confirmed case. Non-pharmaceutical interventions (NPIs) were used to contain the source in Xinfadi (XFD) market. To rapidly control the outbreak, both traditional and newly introduced NPIs including large-scale management of high-risk populations and expanded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR-based screening in the general population were conducted in Beijing. We aimed to assess the effectiveness of the response to the COVID-19 outbreak in Beijing's XFD market and inform future response efforts of resurgence across regions. METHODS: A modified susceptible-exposed-infectious-recovered (SEIR) model was developed and applied to evaluate a range of different scenarios from the public health perspective. Two outcomes were measured: magnitude of transmission (i.e., number of cases in the outbreak) and endpoint of transmission (i.e., date of containment). The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% Confidence Interval (CI). RESULTS: Our results indicated that a 3 to 14 day delay in the identification of XFD as the infection source and initiation of NPIs would have caused a 3 to 28-fold increase in total case number (31-77 day delay in containment). A failure to implement the quarantine scheme employed in the XFD outbreak for defined key population would have caused a fivefold greater number of cases (73 day delay in containment). Similarly, failure to implement the quarantine plan executed in the XFD outbreak for close contacts would have caused twofold greater transmission (44 day delay in containment). Finally, failure to implement expanded nucleic acid screening in the general population would have yielded 1.6-fold greater transmission and a 32 day delay to containment. CONCLUSIONS: This study informs new evidence that in form the selection of NPI to use as countermeasures in response to a COVID-19 outbreak and optimal timing of their implementation. The evidence provided by this study should inform responses to future outbreaks of COVID-19 and future infectious disease outbreak preparedness efforts in China and elsewhere.

Etiological, epidemiological, and clinical features of acute diarrhea in China.

National-based prospective surveillance of all-age patients with acute diarrhea was conducted in China between 2009‒2018. Here we report the etiological, epidemiological, and clinical features of the 152,792 eligible patients enrolled in this analysis. Rotavirus A and norovirus are the two leading viral pathogens detected in the patients, followed by adenovirus and astrovirus. Diarrheagenic Escherichia coli and nontyphoidal Salmonella are the two leading bacterial pathogens, followed by Shigella and Vibrio parahaemolyticus. Patients aged <5 years had higher overall positive rate of viral pathogens, while bacterial pathogens were more common in patients aged 18‒45 years. A joinpoint analysis revealed the age-specific positivity rate and how this varied for individual pathogens. Our findings fill crucial gaps of how the distributions of enteropathogens change across China in patients with diarrhea. This allows enhanced identification of the predominant diarrheal pathogen candidates for diagnosis in clinical practice and more targeted application of prevention and control measures.

Mapping the distribution of tick-borne encephalitis in mainland China.

Tick-borne encephalitis (TBE) has become an increasing public health threat in recent years, ranging from Europe, through far-eastern Russia to Japan and northern China. However, the neglect of its expansion and scarce analyses of the dynamics have made the overall disease burden and the risk distribution of the disease being unclear in mainland China. In this study, we described epidemiological characteristics of 2117 reported human TBE cases from 2006 to 2013 in mainland China. About 99% of the cases were reported in forest areas of northeastern China, and 93% of reported infections occurred during May-July. Cases were primarily male (67%), mostly in 30-59 years among all age-gender groups. Farmers (31.6%), domestic workers (20.1%) and forest workers (17.9%) accounted for the majority of the patients, and the proportions of patients from farmers and domestic workers were increasing in recent years. The epidemiological features of TBE differed slightly across the affected regions. The distribution and features of the disease in three main endemic areas of mainland China were also summarized. Using the Boosted Regression Trees (BRT) model, we found that the presence of TBE was significantly associated with a composite meteorological index, altitude, the coverage of broad-leaved forest, the coverage of mixed broadleaf-conifer forest, and the distribution of Ixodes persulcatus (I. persulcatus) ticks. The model-predicted probability of presence of human TBE cases in mainland China was mapped at the county level. The spatial distribution of human TBE in China was largely driven by the distributions of forests and I. persulcatus ticks, altitude, and climate. Enhanced surveillance and intervention for human TBE in the high-risk regions, particularly on the forest areas in north-eastern China, is necessary to prevent human infections.

Comparative evaluation of the diagnosis, reporting and investigation of malaria cases in China, 2005-2014: transition from control to elimination for the national malaria programme.

BACKGROUND: The elimination of malaria requires high-quality surveillance data to enable rapid detection and response to individual cases. Evaluation of the performance of a national malaria surveillance system could identify shortcomings which, if addressed, will improve the surveillance program for malaria elimination. METHODS: Case-level data for the period 2005-2014 were extracted from the China National Notifiable Infectious Disease Reporting Information System and Malaria Enhanced Surveillance Information System. The occurrence of cases, accuracy and timeliness of case diagnosis, reporting and investigation, were assessed and compared between the malaria control stage (2005-2010) and elimination stage (2011-2014) in mainland China. RESULTS: A total of 210 730 malaria cases were reported in mainland China in 2005-2014. The average annual incidence declined dramatically from 2.5 per 100 000 people at the control stage to 0.2 per 100 000 at the elimination stage, but the proportion of migrant cases increased from 9.8 % to 41.0 %. Since the initiation of the National Malaria Elimination Programme in 2010, the overall proportion of cases diagnosed by laboratory testing consistently improved, with the highest of 99.0 % in 2014. However, this proportion was significantly lower in non-endemic provinces (79.0 %) than that in endemic provinces (91.4 %) during 2011-2014. The median interval from illness onset to diagnosis was 3 days at the elimination stage, with one day earlier than that at the control stage. Since 2011, more than 99 % cases were reported within 1 day after being diagnosed, while the proportion of cases that were reported within one day after diagnosis was lowest in Tibet (37.5 %). The predominant source of cases reporting shifted from town-level hospitals at the control stage (67.9 % cases) to city-level hospitals and public health institutes at the eliminate stage (69.4 % cases). The proportion of investigation within 3 days after case reporting has improved, from 74.6 % in 2010 to 98.5 % in 2014. CONCLUSIONS: The individual case-based malaria surveillance system in China operated well during the malaria elimination stage. This ensured that malaria cases could be diagnosed, reported and timely investigated at local level. However, domestic migrants and overseas populations, as well as cases in the historically malarial non-endemic areas and hard-to-reach area are new challenges in the surveillance for malaria elimination.

Mapping the Distribution of Anthrax in Mainland China, 2005-2013.

BACKGROUND: Anthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: Using the national surveillance data of human and livestock anthrax from 2005 to 2013, we conducted a retrospective epidemiological study and risk assessment of anthrax in mainland China. The potential determinants for the temporal and spatial distributions of human anthrax were also explored. We found that the majority of human anthrax cases were located in six provinces in western and northeastern China, and five clustering areas with higher incidences were identified. The disease mostly peaked in July or August, and males aged 30-49 years had higher incidence than other subgroups. Monthly incidence of human anthrax was positively correlated with monthly average temperature, relative humidity and monthly accumulative rainfall with lags of 0-2 months. A boosted regression trees (BRT) model at the county level reveals that densities of cattle, sheep and human, coverage of meadow, coverage of typical grassland, elevation, coverage of topsoil with pH > 6.1, concentration of organic carbon in topsoil, and the meteorological factors have contributed substantially to the spatial distribution of the disease. The model-predicted probability of occurrence of human cases in mainland China was mapped at the county level. CONCLUSIONS/SIGNIFICANCE: Anthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections.

Governmental supervision and rapid detection on dengue vectors: An important role for dengue control in China.

BACKGROUND: China experienced an unprecedented outbreak of dengue fever in 2014, the National Health and Family Planning Commission of the People's Republic of China (NHFPC) carried out a series of supervision work on integrated vector management (IVM), and Chinese Center for Disease Control and Prevention (China CDC) conducted a rapid detection on vector density in some areas with high dengue incidence. The goal of this study was to explain the effect of these actions, which play an important role for dengue control, and we wish to give a good example for dengue control in China, even in the world. METHODS: Compare mosquito vector density with Breteau Index (BI) and dengue incidence after or along with control work vs. before. Data was entered and analyzed by Microsoft Excel 2007 and SPSS19.0. RESULTS: Average value of BI from 22.82 in September dropped to 3.93 along with supervision and rapid detection. BI showed a significant decrease (paired sample t-test, t=3.061, P=0.018≺0.05). Dengue incidence decreased gradually along with supervision and rapid detection. CONCLUSIONS: Supervised work on IVM by NHFPC and the rapid detection on dengue vector Aedes by China CDC promoted to cut down the dengue vector density, then reduced dengue incidence; both played an important role for dengue control throughout China in 2014.

Visualized Exploratory Spatiotemporal Analysis of Hand-Foot-Mouth Disease in Southern China.

OBJECTIVES: In epidemiological research, major studies have focused on theoretical models; however, few methods of visual analysis have been used to display the patterns of disease distribution. DESIGN: For this study, a method combining the space-time cube (STC) with space-time scan statistics (STSS) was used to analyze the pattern of incidence of hand-foot-mouth disease (HFMD) in Guangdong Province from May 2008 to March 2009. In this research, STC was used to display the spatiotemporal pattern of incidence of HFMD, and STSS were used to detect the local aggregations of the disease. SETTING: The hand-foot-mouth disease data were obtained from Guangdong Province from May 2008 to March 2009, with a total of 68,130 cases. RESULTS: The STC analysis revealed a differential pattern of HFMD incidence among different months and cities and also showed that the population density and average precipitation are correlated with the incidence of HFMD. The STSS analysis revealed that the most likely aggregation includes the Shenzhen, Foshan and Dongguan populations, which are the most developed regions in Guangdong Province. CONCLUSION: Both STC and STSS are efficient tools for the exploratory data analysis of disease transmission. STC clearly displays the spatiotemporal patterns of disease. Using the maximum likelihood ratio, the STSS model precisely locates the most likely aggregation.

[Application of the China Infectious Diseases Automated-alert and Response System in Guangxi, 2009-2011].

OBJECTIVE: To analyze and further improvement the application of the China Infectious Diseases Automated-alert and Response System (CIDARS) in Guangxi Zhuang Autonomous Region. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

[The application of China Infectious Diseases Automated-alert and Response System in Zhejiang province, 2012].

OBJECTIVE: To analyze and evaluate the application of China Infectious Diseases Automated-alert and Response System(CIDARS)in Zhejiang province. METHODS: 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. RESULTS: 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). CONCLUSION: 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.

A spatial scan statistic for nonisotropic two-level risk cluster.

Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the hand-foot-mouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster.

Area disease estimation based on sentinel hospital records.

BACKGROUND: Population health attributes (such as disease incidence and prevalence) are often estimated using sentinel hospital records, which are subject to multiple sources of uncertainty. When applied to these health attributes, commonly used biased estimation techniques can lead to false conclusions and ineffective disease intervention and control. Although some estimators can account for measurement error (in the form of white noise, usually after de-trending), most mainstream health statistics techniques cannot generate unbiased and minimum error variance estimates when the available data are biased. METHODS AND FINDINGS: A new technique, called the Biased Sample Hospital-based Area Disease Estimation (B-SHADE), is introduced that generates space-time population disease estimates using biased hospital records. The effectiveness of the technique is empirically evaluated in terms of hospital records of disease incidence (for hand-foot-mouth disease and fever syndrome cases) in Shanghai (China) during a two-year period. The B-SHADE technique uses a weighted summation of sentinel hospital records to derive unbiased and minimum error variance estimates of area incidence. The calculation of these weights is the outcome of a process that combines: the available space-time information; a rigorous assessment of both, the horizontal relationships between hospital records and the vertical links between each hospital's records and the overall disease situation in the region. In this way, the representativeness of the sentinel hospital records was improved, the possible biases of these records were corrected, and the generated area incidence estimates were best linear unbiased estimates (BLUE). Using the same hospital records, the performance of the B-SHADE technique was compared against two mainstream estimators. CONCLUSIONS: The B-SHADE technique involves a hospital network-based model that blends the optimal estimation features of the Block Kriging method and the sample bias correction efficiency of the ratio estimator method. In this way, B-SHADE can overcome the limitations of both methods: Block Kriging's inadequacy concerning the correction of sample bias and spatial clustering; and the ratio estimator's limitation as regards error minimization. The generality of the B-SHADE technique is further demonstrated by the fact that it reduces to Block Kriging in the case of unbiased samples; to ratio estimator if there is no correlation between hospitals; and to simple statistic if the hospital records are neither biased nor space-time correlated. In addition to the theoretical advantages of the B-SHADE technique over the two other methods above, two real world case studies (hand-foot-mouth disease and fever syndrome cases) demonstrated its empirical superiority, as well.

A spatial scan statistic for multiple clusters.

Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect.

[The comparison of two different types of baseline data regarding the performance of aberration detection algorithm for infectious disease outbreaks].

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 C1, 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.

[Comparison on the performance of both temporal and temporal-spatial models for outbreak detection through China Infectious Diseases Automated-alert and Response System (CIDARS)].

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.

[Preliminary application on China Infectious Diseases Automated-alert and Response System (CIDARS), between 2008 and 2010].

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, 2008 to 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 9 H5N1 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.