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Kyasanur forest disease (KFD) is a zoonotic viral disease caused by infection by a Flavivirus, a member of the family Flaviviridae. KFD is a public health concern in the Karnataka State in southern India. Available conventional diagnostic tests such as virus isolation and serological tests, such as haemagglutination inhibition and complement fixation tests are time consuming. This study reports the development of a nested RT-PCR [nRT-PCR] and a TaqMan-based real-time RT-PCR and IgM antibodies capture ELISA [MAC-ELISA] for rapid and accurate diagnosis of suspected KFD cases. The nRT-PCR and the TaqMan-based real-time RT-PCR assays were developed using gene sequences of the NS-5/non-coding region. Both the assays detected KFD viral RNA in acute phase human serum samples and can provide early diagnosis of infection. Real-time RT-PCR was found to be more sensitive than nRT-PCR, which could detect 38 copies of KFDV RNA. MAC-ELISA was developed for the detection of recent infections. Although real-time RT-PCR and nRT-PCR require expensive reagents, expensive equipment and trained personnel, the developed MAC-ELISA can be used easily in the affected areas. These tests add to the existing diagnosis arsenal against haemorrhagic viruses that are prevalent in India. These assays will also help to extend our knowledge of the pathology of KFD virus and its associated clinical features, by measuring the viral titre during infection and at the time of seroconversion. Information, which is not available currently because of the lack of appropriate diagnostic methods. In addition, early laboratory diagnosis of KFDV infection will help in the application of appropriate control measures and management of KFD cases. Copyright © 2012 Elsevier B.V. All rights reserved.

Citation

Devendra T Mourya, Pragya D Yadav, Rajeev Mehla, Pradip V Barde, Prasanna N Yergolkar, Sandeep R P Kumar, Jyotsna P Thakare, Akhilesh C Mishra. Diagnosis of Kyasanur forest disease by nested RT-PCR, real-time RT-PCR and IgM capture ELISA. Journal of virological methods. 2012 Dec;186(1-2):49-54

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PMID: 22874757

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