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<p><b>OBJECTIVE</b>To investigate molecular characterization of streptococcus pyogenes isolates involved in an outbreak of scarlet fever in China in 2011.</p><p><b>METHODS</b>Seventy-four Streptococcal pyogenes involved in an outbreak of scarlet fever were isolated from pediatric patients in the areas with high incidence in China from May to August of 2011. Emm genotyping, pulsed-field gel electrophoresis (PFGE), superantigen (SAg) genes and antimicrobial susceptibility profiling were analyzed for these isolates.</p><p><b>RESULTS</b>A total of 4 different emm types were identified. Emm12 was the most prevalent type which contained four predominating PFGE patterns corresponding to four different virulence and superantigen profiles. Emm12 (79.7%) and emm1 (14.9%) accounted for approximately 94% of all the isolates. The speA gene was all negative in emm12 isolates and positive in emm1 isolates. All strains were resistant to erythromycin, and 89.4% of them were resistant to erythromycin, tracycline, and clindamycin simultaneously.</p><p><b>CONCLUSION</b>Several highly diversified clones with a high macrolide resistance rate comprise a predominant proportion of circulating strains, though no new emm type was found in this outbreak. The data provide a baseline for further surveillance of scarlet fever, which may contribute to the explanation of the outbreak and development of a GAS vaccine in China.</p>
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Child , Humans , Anti-Bacterial Agents , Therapeutic Uses , China , Epidemiology , Disease Outbreaks , Drug Resistance, Bacterial , Electrophoresis, Gel, Pulsed-Field , Incidence , Molecular Epidemiology , Scarlet Fever , Drug Therapy , Epidemiology , Microbiology , Streptococcus pyogenes , Genetics , Virulence , VirulenceABSTRACT
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.
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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.
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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.
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<p><b>OBJECTIVE</b>To describe the occupational distribution of staff who worked on detection and reporting on public health emergency events, and to explore the effective strategies for identification and reporting on emergency events.</p><p><b>METHODS</b>We conducted a retrospective survey on 3275 emergent events reported through Public Health Emergency Events Surveillance System from 2005 to the first half of 2006. Data were collected by uniform self-administrated questionnaires by county Centers for Disease Control and Prevention, including information on events detection and reporting, etc.</p><p><b>RESULTS</b>Among event discoverers, 56.40% (1847/3275) were healthcare staff, 20.58% (674/3275) were teachers, and 15.15% (496/3275) were staff from the disease control systems. Among those event reporters, 56.82% (1861/3275) were healthcare staff, 21.77% (713/3275) from disease control system and 10.75% (352/ 3275) were teachers.</p><p><b>CONCLUSION</b>Healthcare staff and teachers played the most important role in detection and reporting on events. It would be favorable to improve the ability of events detection and reporting if we could enhance the training program to the relative staff in medical facilities and school settings especially at the grass root level.</p>
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Humans , China , Disease Notification , Internet , Population Surveillance , Public HealthABSTRACT
<p><b>OBJECTIVE</b>To understand the changing trend on the way of delivery since 1970s and its related factors that influencing the attitude of choice on Cesarean section (C-section) in women at child-bearing age.</p><p><b>METHODS</b>A face-to-face interview was conducted anonymously in pregnant and lying-in women visited at the out-patient department of Gynecology and Obstetrics, Tiantan Hospital of Beijing. Totally, 415 women at child-bearing age, with a history of previous birth were interviewed on date, place and way of delivery of last birth, as well as on information that could have had impact on the choice of C-section.</p><p><b>RESULTS</b>The average rate of C-section in Tiantan Hospital had been 29% since the year of 2000, much higher than that during 1970s, 1980s and 1990s (chi(2) = 22.81, P = 0.001) which showed an increasing trend. Rate of C-section among lying-in women with native Beijing origin was 25.0%, significantly higher than 9.6% (chi(2) = 21.96, P = 0.000 002) that in the migrants. Lying-in women with education level of high school or above had higher chance to choose C-section than those with lower level of education (chi(2) = 43.64, P < 0.000 01). Workers, managerial staff or clerks had more chance to choose C-section than those with other occupations (chi(2) = 20.07, P = 0.01). As reported by the interviewees, 93% (70/75) of C-section in the hospital were performed and recommended by obstetricians.</p><p><b>CONCLUSION</b>Rate of C-section in the hospital showed an increasing trend which suggested that intervention with health education be carried out for both pregnant women and obstetricians.</p>