In order to investigate the effects of HA whisker and carboxymethyl chitosan-gelatin(CMC-Gel) on the mechanical properties of porous calcium phosphate cement, a series of alpha-tricalcium phosphate (alpha-TCP), HA whisker and L-sodium glutamate porogen with different mass fractions were mixed, and setting liquid was added to them to prepare alpha-TCP/HA whisker composite porous bone cement. Then, the cement was immersed in a series of CMC-Gel solutions which had different weight ratios of CMC to Gel to prepare alpha-TCP/HA whisker/CMC-Gel composite porous bone cement. The compressive strengths and microstructure of cement were characterized by mechanical testing machine and SEM. The results showed that when the mass fraction of HA whisker is 4%, the compressive strength of alpha-TCP/HA whisker composite porous bone cement reaches 2.57MPa, which is 1.81 times that of alpha-TCP bone cement. When the weight ratio of CMC to Gel is 50:50, the compressive strength of alpha-TCP/HA whisker/CMC-Gel composite porous bone cement is 3. 34MPa, which is 2.35 times that of alpha-TCP bone cement, and the toughness of the composite cement is greatly improved as well.
Biocompatible Materials ; chemistry ; pharmacology ; Bone Cements ; chemical synthesis ; Calcium Phosphates ; chemistry ; Chitosan ; analogs & derivatives ; chemical synthesis ; chemistry ; Compressive Strength ; Gelatin ; chemistry ; Hydroxyapatites ; chemical synthesis ; chemistry ; Porosity

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

OBJECTIVETo investigate the cause and related risk factors of an outbreak caused by Brucellosis.

METHODSEpidemiological investigation and laboratory test were carried out among occupationally invloved population including sheep slaughters and sellers in the village.

RESULTS18 people were serology positive among the 129 occupationally involved persons under survey. Seven of them were confirmed cases, 11 were latent infection, to make the overall attack rate as 14%. 90% of the sheep were from high-risk areas of Brucella. Among the occupationally involved persons, 89% of them never wore face masks, 84% never wear overalls and 70% never wear gloves. Factors as:work but wearing no gloves (RR = 7.4, 95%CI:1.1-53.0), with hand wound (RR = 3.4, 95%CI:1.1-11.0) could increase the risk of Brucella infection.

CONCLUSIONThe cause of this outbreak was due to the plentiful influx of unchecked sheep from the northern part of China and the employees in the process of sheep slaughtering or trading were lack of effective prevention programs.

Abattoirs ; Animals ; Brucella ; isolation & purification ; Brucellosis ; epidemiology ; China ; epidemiology ; Commerce ; Disease Outbreaks ; Humans ; Incidence ; Occupational Diseases ; epidemiology ; Risk Factors ; Sheep ; microbiology

OBJECTIVETo 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.

METHODSEight 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.

RESULTS4 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.

CONCLUSIONRSV 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.

Child, Hospitalized ; statistics & numerical data ; Child, Preschool ; China ; epidemiology ; Female ; Humans ; Infant ; Male ; Pneumonia, Viral ; epidemiology ; virology