Shenzhen Exit Entry Inspection and Quarantine Bureau

Shenzhen, China

Shenzhen Exit Entry Inspection and Quarantine Bureau

Shenzhen, China
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Zhang M.,Chinese Academy of Inspection and Quarantine | Yang J.X.,Biotechnology Institute of Fujian Academy of Agriculture science | Lin X.M.,Chinese Academy of Inspection and Quarantine | Zhu C.H.,Biotechnology Institute of Fujian Academy of Agriculture science | And 3 more authors.
Journal of Virological Methods | Year: 2010

A double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) for detection of the soft-shelled turtle iridovirus (STIV) was developed using a specific monoclonal antibody (mAb) against STIV and anti-STIV rabbit serum. Using DAS-ELISA, the detection limit of STIV was found to be 103PFU/ml. The positive rate of 15 STIV samples was 100%, while the positive rate of 100 other aquatic virus samples was 0%. These data show that DAS-ELISA is highly specific and sensitive for the detection of STIV. In clinical tests, 128 samples isolated from pond-reared turtles were subjected to DAS-ELISA and PCR. The overall agreement between the results obtained by DAS-ELISA and PCR was 98.4%. The results indicate that the DAS-ELISA method could be used for diagnosing diseases caused by STIV. © 2010 Elsevier B.V.


Liu C.,Southern Medical University | Liu Q.,Chinese National Institute for Communicable Disease Control and Prevention | Liu Q.,Zhejiang University | Lin H.,Guangdong Institute of Public Health | And 3 more authors.
Asia-Pacific Journal of Public Health | Year: 2014

Guangdong Province is the area most seriously affected by dengue fever in China. In this study, we describe the spatial distribution of dengue fever in Guangdong Province from 2001 to 2006 with the objective of informing priority areas for public health planning and resource allocation. Annualized incidence at a county level was calculated and mapped to show crude incidence, excess hazard, and spatial smoothed incidence. Geographic information system-based spatial scan statistics was conducted to detect the spatial distribution pattern of dengue fever incidence at the county level. Spatial scan cluster analyses suggested that counties around Guangzhou City and Chaoshan Region were at increased risk for dengue fever (P <.01). Some spatial clusters of dengue fever were found in Guangdong Province, which allowed intervention measures to be targeted for maximum effect. © 2013 APJPH.

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