ISSN 1003-8280 CN 10-1522/R 中国疾病预防控制中心 主办
Objective To explore the spatial-temporal characteristics of hemorrhagic fever with renal syndrome (HFRS) in mainland China. Methods Demographic information and the annual number of incident HFRS cases in mainland China from 2004 to 2013 were collected. Retrospective time-space analysis (based on discrete poisson model) was conducted to detect the spatial and spatio-temporal clusters of HFRS cases in SaTScan (Version 9.1.1) after geographical information system database constructed via ArcGIS software (Version 9.3). Gravity centers of HFRS cases were calculated and depicted with bubble charts in Excel 2010. Results The number of HFRS cases decreased from 2004 to 2009 and increased with a gravity center northeast to that of population. The gravity center of HFRS cases in 2013 moved to southwest for 307.87 km compared to that of 2004 with the directional angle as 241.69 degree. The distance in longitude was 119.52 km and 282.61 km in latitude. The most likely cluster was in Heilongjiang, Jilin and Liaoning during 2004 to 2008 with the relative risk 9.22. The secondary cluster included four geographical areas, Shaanxi area (2008-2012), Shandong, Tianjin and Hebei area (2004-2005), Zhejiang province (2004-2007) and Jiangxi (2011-2013), the relative risks varied from 1.32 to 6.33. Conclusion There are significant spatio-temporal cluster pattern for the distribution of HFRS cases in mainland China, the epidemic status showed a weakening trend and the gravity center moved from northeastern part to northern China.
Objective To describe the procedure of building Elman neural network model, and explore the value of potential application of the above model. Methods Monthly incidence of hemorrhagic fever with renal syndrome(HFRS) in China from 2004 to 2013 was used to build Elman neural network model and SARIMA model and forecasted the monthly incidence of HFRS in China from January 2014 to September 2014. The fitting and prediction effects of the two models were compared. Results For training sample, MAE, MAPE and RMSE of Elman neural network were 0.0088, 0.1191 and 0.0127 respectively; MAE, MAPE and RMSE of SARIMA model were 0.0111, 0.1268 and 0.0206 respectively. For predicting sample, MAE, RMSE and MAPE of Elman neural network were 0.0079, 0.1180 and 0.0096 respectively; MAE, RMSE and MAPE of SARIMA model were 0.0178, 0.2778 and 0.1861 respectively. Conclusion Elman neural network fits and forecasts the HFRS incidence trend in China well, and the fitting and prediction effect is superior to the SARIMA model, which is of great application value for the prevention and control of hemorrhagic fever with renal syndrome.
Objective To analyze the epidemiological features of hemorrhagic fever with renal syndrome (HFRS) and associated environmental risk factors for HFRS and associated environmental risk factors for HFRS in Liaoning province, China during 2005-2007, and to provide a scientific basis for HFRS control measures. Methods The epidemic data of HFRS in Liaoning province were collected. Analysis was performed to determine the correlation between the epidemic features of HFRS and environmental factors such as mean temperature, relative humidity, rainfall, sunshine, urban rodent density, rural rodent density, and virus?carrying rate. Results There were 7298 cases of HFRS in Liaoning province from 2005 to 2007, and 78 of them died. The mean annual incidence of HFRS was 5.78/100 000, and the mortality was 0.06/100 000; the incidence and mortality were higher in males than in females; 59.55% of the cases and 69.23% of fatal cases were aged 35-60 years; 61.98% of the cases and 56.41% of fatal cases were farmers. The peak of incidence appeared mainly in November to January and March to May, while the trough period was in July to October, showing the seasonal characteristics in mixed epidemic area; the mean annual incidence of HFRS was relatively high in the cities of Benxi (13.70/100 000), Huludao (12.92/100 000), Jinzhou (11.30/100 000), Dandong (10.21/100 000), and Fushun (9.84/100 000). The incidence of HFRS was negatively correlated with temperature but positively correlated with rainfall, rural rodent density, and virus-carrying rate; the Spearman rank correlation coefficients were -0.351, 0.400, 0.449, and 0.377, respectively, and the P values were 0.023, 0.009, 0.003, and 0.016, respectively. Conclusion In Liaoning province, HFRS is prevalent mainly in winter and spring and among young male farmers. The prevalence of HFRS is closely related to temperature, rainfall, rural rodent density, and virus-carrying rate in the same year.
Objective To explore the frontier quarantine strategies for prevention and control of exotic vectors. Methods Exotic vectors first intercepted at Ningbo port from 2004 to 2009 were analyzed along with the case study of hazards brought by exotic vectors. Results With many years of strict frontier quarantine on international sailing ships, containers and cargos, 39 exotic vectors of 3 species, Supella supellectilium, Cochliomyia macellaria and Panchlora nivea were captured for the first time from 10 batches, as well as 9 species from 12 batches, which were sparsely distributed in a handful of provinces other than Zhejiang province. Hence, hazardous exotic vectors were effectively prevented from invading or spreading in China. Conclusion Frontier quarantine is irreplaceably essential to preventing the import of exotic hazardous vectors.
Objective A network system with electronic warning functions was developed for monitoring and control of regional termite infestation, providing a new technique and approach for termite control in China. Methods The electronic monitoring and control devices were planted in the areas of active termites to assess the reliability of infestation alarms made by the devices. Results The infestation warning network system based on type B monitoring and control devices provided accurate warnings in terms of the infestations of common termites such as Coptotermes formosanus, Reticulitermes speratus and Odontotermes formosanus. Conclusion The electronic warning network system for termite monitoring and control may be used for the termite prevention and control in housing construction, reservoirs, dams and landscaping and greening.
【Abstract】 Objective To study the relationships of meteorological factors, animal host and hemorrhagic fever with renal syndrome (HFRS) incidence, and construct mathematical model for the forecast of HFRS. Methods Firstly, air pressure, air temperature, relative humidity, precipitation, sunshine duration and sunshine percentage were selected from all meteorological factors of Huludao city. Secondly, Pearson, Kendall and Spearman correlation analyses were used to describe the relationships among meteorological factors, animal host situation including rodent density and viral carriage of rodents and HFRS incidence. Thirdly, Bayesian discrimination analysis (BDA) was adopted to forecast HFRS incidence on the premise of meteorological factors and animal host formation as explanatory variables. Results There was the close relation between rodent density and annual HRFS incidence(r=0.738, P=0.000), and the rodent density was also influenced by sunshine duration, sunshine percentage and precipitation. A positive correlation was found between rodent density and sunshine time(r=0.494, P=0.016), and the correlation between rodent density and precipitation was negative(r=-0.350, P=0.101). The step wise BDA and all variables discrimination analysis had all good effect on the forecasting of HFRS based on meteorological factors and animal host data. The accuracy rate of fitting and leave?one?out (LOO) cross-validation of stepwise BDA all reached 82.6%(19/23) , however, that of fitting of all variables BDA was 90.9%(20/22) and 81.8%(18/22) for LOO cross-validation. For next year incidence prediction, the accuracy rates of fitting and LOO cross-validation step-wise were all 86.4%(19/22) for step-wise BDA, while for all variables BDA, its accuracy rate of fitting was 100%(21/21) and that of LOO cross-validation was 57.1%(12/21). Conclusion HFRS incidence was related to animal epidemic situation which was influenced by meteorological factors. Stepwise BDA offered useful information in the discrimination and forecasting of HFRS incidence, which had a good application in the future.
【Abstract】 Objective To grasp the dynamic change of the population distribution and seasonal fluctuation of cockroach in Dalian. Methods The baits and traps method was used in the surveillance. Results There were 3 species of cockroaches, and Blattella germanica was the dominant species, accounting for 96.89%. Periplaneta japonica and P.fuliginosa accounted for 3.02% and 0.09% respectively. The activity peak of the cockroach was from July to October. The order of cockroach distributed in different trade was farm produce trade market, residential area, restaurant, hotel and hospital. Conclusion B.germanica was the dominant species in Dalian, suggesting that it should put the emphasis on the control of it in the future.