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Chinese Journal of Schistosomiasis Control ; (6): 26-31, 2018.
Article in Chinese | WPRIM | ID: wpr-704219

ABSTRACT

Objective To evaluate the pathogenic detection capacity of county-level organizations in Jiangsu Province,and to improve the field schistosomiasis detection capacity of professional personnel,thus to provide the technical support for the con-struction of quality control system of schistosomiasis field detection.Method The eggs of Schistosoma japonicum were obtained from rabbit schistosomiasis models and were produced into suspensions at four different concentrations.The county-level workers were invited to hatch the eggs,and the accuracy,detection error rate and omission rate were compared between the detection re-sults and the standard results.The single-blind method was used in the capacity examination. Result A total of 560 suspen-sions were detected by 28 counties(districts,cities),and 283 positive samples and 203 negative samples were detected.The total accuracy was 86.79%,total error rate was 9.38%,and total omission rate was 15.77%.The difference between the detection re-sult and standard result was statistically significant(χ2=12.99,P<0.01).Twenty out of 28 counties(districts,cities)had omis-sion detections,accounting for 71.43%;and 13 had fault detections,accounting for 46.43%.The error rates of workers from the river marshland,hilly areas,water networks,and lake marshland ranged from 4.55% to 43.75%,and the difference was statistical-ly significant(χ2=30.34,P<0.01).The omission rate ranged from 4.17% to 20.45%,and the difference was not statistically sig-nificant(χ2=5.09,P=0.17).The error rates and omission rates of workers from the transmission control areas and transmission interruption areas were 7.50%,13.33% and 10.42%,17.13%,respectively,and the differences were not statistically significant (χ2=0.229,0.575,both P>0.05).The error rates and omission rates of workers from the areas with or without at least ten years history of transmission control were 11.81%,5.00% and 16.67%,14.17%,respectively,and the differences were not statistically significant(χ2=2.804,2.848,both P>0.05).The error rates of workers from the areas with or without at least ten years history of transmission interruption were 11.54% and 10.00%, respectively, and the difference was not statistically significant(χ2=0.069,P=0.792),while the correspondent omission rates were 10.90% and 35.00% respectively,and the difference was statisti-cally significant(χ2=17.364,P<0.01).Conclusion The detection error and omission exist in the schistosomiasis examina-tions in the county-level organizations in Jiangsu Province,and therefore,the field pathogen detection capacity of the professional personnel needs to be further improved.

2.
Article in English | IMSEAR | ID: sea-176289

ABSTRACT

The present study was untaken in order to identify and map soil biophysical constraints by GIS techniques in Singhanhalli-Bogur microwatershed in northern transition zone of Karnataka. Ten biophysical soil parameter including depth, coarse fragment/stoniness, texture, structure, tillage pan, rooting condition, surface crust, organic matter, biological activity and sodicity were assessed and interpreted for soil health. The depth of the soils varied from shallow to deep and structure varied from weak to strong with some mapping units showing slightly developed tillage pans. The texture of soils varied from sandy loam to sandy clay, sandy clay loam and clay while the content of coarse fragments ranged from common to many and abundant. Soils having sandy loam texture showed high content of coarse fragments. No signs of unrestricted root developments were observed as the rooting condition was good. The organic matter content of soils ranged from low to high with presence of few to many termite holes indicating biological activity. Physical soil crusts ranging from slight to severe were observed in some mapping units. The soils were free of high sodium concentrations and hence, classified as non-sodic soils. Overall, soil health status varied from poor to medium with the level of constraints ranging from moderate to severe. Soils with severe constraints showed poor health status while soils with moderate constraints showed medium health status.

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