OBJECTIVEIn order to understand the distribution of the host animals in Junggar Basin, this study intended to map the spatial distribution and identifying the risk of Rhombomys opimus in the framework of ecological niche theory based on the "3S" technology.

METHODSData on Rhombomys opimus was obtained through a series of field surveys. Environmental variables were achieved through data from Remote Sensing. Maxent modeling was built to map the potential distribution of Rhombomys opimus, with its risks identified.

RESULTSThe prediction model showed ideal accuracy, with the AUC value as 0.968. Probability of Maximum Youden Index was defined as the threshold being used. The sensitivity and specificity showed as 91.4% and 63.3%, respectively. The accuracy was 73.8%, and the Kappa coefficient was 0.495. The positive predictive value was 59.7%. The negative predictive value was 92.6%. The predicted high risk area was 37 304 km2, with 6.2% in the whole area, distributed in 18 counties, including Changji Hui Autonomous Prefecture, Urumqi, Karamay and so on. The number of people under high risk would come about 120 000, scattering in the areas of 261 square kilometers.

CONCLUSIONIt was feasible to predict the potential distribution of Rhombomys opimus based on the ecological niche theory as well as environmental variables derived from data through remote sensing. More specific high-risk areas could be identified under this technique so as to guide the monitoring programs.

OBJECTIVETo establish a comprehensive evaluation index system for the China Public Health Emergency Events Surveillance System (CPHEESS).

METHODSA draft index system was built through literature review and under the consideration of the characteristics on CPHEESS. Delphi method was adapted to determine the final index system.

RESULTSThe index system was divided into primary, secondary and tertiary levels. There were 4 primary indicators: System structure, Network platform, Surveillance implementation reports with Data analysis and utilization. There were 16 secondary and 70 tertiary indicators being set, with System structure including 14 tertiary indicators (accounted for 20.00%), 21 Network platforms (accounted for 30.00%). Twenty-four Surveillance implementation reports (accounted for 34.29%), 11 Data analysis and utilization (accounted for 15.71%). The average score of importance of each indicators was 4.29 (3.77-4.94), with an average coefficient variation as 0.14 (0.12-0.16). The mean Chronbach's α index was 0.84 (0.81-0.89). The adaptability of each related facilities indicator was specified.

CONCLUSIONThe primary indicators were set in accordance with the characteristics and goals of the surveillance systems. Secondary indicators provided key elements in the management and control of the system while the tertiary indicators were available and operative. The agreement rate of experts was high with good validity and reliability. This index system could be used for CPHEESS in future.

China ; epidemiology ; Delphi Technique ; Emergencies ; Forecasting ; Humans ; Public Health Surveillance ; methods ; Reproducibility of Results

OBJECTIVETo analyze the epidemiological characteristics of Middle East Respiratory Syndrome (MERS) outbreak in the Republic of Korea in 2015 and provide related information for the public health professionals in China.

METHODSThe incidence data of MERS were collected from the websites of the Korean government, WHO and authoritative media in Korea for this epidemiological analysis.

RESULTSBetween May 20 and July 13, 2015, a total of 186 confirmed MERS cases (1 index case, 29 secondary cases, 125 third generation cases, 25 fourth generation cases and 6 cases without clear generation data), including 36 deaths (case fatality rate: 19%), were reported in Korea. All cases were associated with nosocomial transmission except the index case and two possible family infections. Sixteen hospitals in 11 districts in 5 provinces/municipalities in Korea reported confirmed MERS cases, involving 39 medical professionals or staff. For the confirmed cases and death cases, the median ages were 55 years and 70 years respectively, and the cases and deaths in males accounted for 60% and 67% respectively. Up to 78% of the deaths were with underlying medical conditions. Besides the index case, other 12 patients were reported to cause secondary cases, in which 1 caused 84 infections. One imported MERS case from Korea was confirmed in China on May 29, no secondary cases occurred. The viruses strains isolated from the cases in Korea and the imported case in China show no significant variation compared with the strains isolated in the Middle East.

CONCLUSIONThe epidemiological pattern of the MERS outbreak in Korea was similar to MERS outbreaks occurred in the Middle East.

Aged ; Coronavirus Infections ; epidemiology ; Cross Infection ; Disease Outbreaks ; Female ; Hospitals ; Humans ; Male ; Middle Aged ; Middle East Respiratory Syndrome Coronavirus ; Public Health ; Republic of Korea ; epidemiology