Detection of Dengue, Chikungunya, and Zika Viruses Among Patients in Sarawak, Malaysia by a Novel Multiplexing Platform
Detection of Dengue, Chikungunya, and Zika Viruses Among Patients in Sarawak, Malaysia by a Novel Multiplexing Platform By Juliana N. Zemke Duke Global Health Institute Duke University Date:_______________________ Approved: ___________________________ Gregory C. Gray, Supervisor ___________________________ Lawrence Park ___________________________ Myaing Myaing Nyunt Thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in the Duke Global Health Institute in the Graduate School of Duke University 2019 ABSTRACT Detection of Dengue, Chikungunya, and Zika Viruses Among Patients in Sarawak, Malaysia by a Novel Multiplexing Platform by Juliana N. Zemke Duke Global Health Institute Duke University Date:_______________________ Approved: ___________________________ Gregory C. Gray, Supervisor ___________________________ Lawrence Park ___________________________ Myaing Myaing Nyunt An abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Duke Global Health Institute in the Graduate School of Duke University 2018 Copyright by Juliana N Zemke 2019 Abstract Introduction: According to the World Health Organization (WHO), 500 million arbovirus cases are diagnosed around the world annually, with 2.7 million associated deaths [1]. The burden of disease caused by dengue, chikungunya, and Zika viruses is likely to be underestimated due to a lack of accurate diagnostic tools and knowledge gaps regarding their epidemiology [2, 3]. This thesis uses a subset of data from an on-going 24-month study to evaluate the potential etiology of dengue-like symptoms of patients recruited from medical facilities in Sarawak, Malaysia. A secondary aim is to assess the diagnostic clinical effectiveness of a new detection method, the novel T-Cor 8 Multiplexing Platform (Tetracore, Inc., USA), using qRT-PCR assays as the gold standard method for comparison.
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