MOLECULAR CHARACTERIZATION OF HEPATITIS C VIRUS AND INTRODUCTION OF BIORISK MANAGEMENT (CWA 15793-2008) AT MIRPUR DISTRICT, AZAD JAMMU AND KASHMIR

Journal Title: Baqai Journal of Health Sciences - Year 2016, Vol 19, Issue 2

Abstract

The object of the study was to determine the ratio of incidence and genotyping of hepatitis C virus (HCV) infection with reference to different typable and untypable strains in various populations of Mirpur, Azad Jammu and Kashmir (AJK). This was done by taking into account different modalities with reference to gender, age and socio-economic perspective. A total of 88 patients were included in the studyand the screening was initially carried out by rapid diagnostic tests (RDT) with further confirmation by polymerase chain reaction (PCR) method. The real time PCR (qPCR) was performed at Genetic and Molecular Center, Lahore. These tests were done at Biosafety Level 2 (BSL 2) laboratory (according to Biorisk Management CWA15793-2008)which was the criteria determined by risk assessment performed by principal investigator and the scientificofficer of the facility. The genotype 3a was found to be the most common type in affected patients which certainly determined the management of these infections in a more targeted manner.The study was able to determine the prevalence rate on gender basis which was important on local basis and can be the basis to initiate the study for finding out the reasons for the same. The age group most affected was found to be in the younger group. In addition, introduction of Biorisk Management was very encouraging and the professionals showed keen interest in this scientific discipline and were eager to learn the key concepts of it.

Authors and Affiliations

Shamsul Arfin Qasmi, Mohammad Sadiq, Sarmad Pirzada

Keywords

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  • EP ID EP200018
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How To Cite

Shamsul Arfin Qasmi, Mohammad Sadiq, Sarmad Pirzada (2016). MOLECULAR CHARACTERIZATION OF HEPATITIS C VIRUS AND INTRODUCTION OF BIORISK MANAGEMENT (CWA 15793-2008) AT MIRPUR DISTRICT, AZAD JAMMU AND KASHMIR. Baqai Journal of Health Sciences, 19(2), 17-21. https://europub.co.uk/articles/-A-200018