Detection of Dengue, Chikungunya, and Zika Viruses Among Patients in Sarawak, Malaysia by a Novel Multiplexing Platform

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2019

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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. The prevalence of arboviral infections as determined by gold-standard qRT-PCR assays and potential risk factors in the study population were also analysed.

Methods: In this cross-sectional study, patients more than seven years of age with dengue-like symptoms were enrolled at medical facilities in the towns of Sibu and Kapit in Sarawak, Malaysia. Blood, urine, and gingival crevicular fluid samples, as well as risk factor data, were collected from participants at the time of enrolment. These samples were studied by qRT-PCR assays and the novel T-Cor 8 Multiplexing Platform.

Results: Seven (14%) of 51 participants’ serum RNA samples tested positive for arbovirus infection by gold-standard qRT-PCR assays. Two participants (4%) were positive for dengue subtype-1, four participants (8%) were positive for dengue subtype-2, and one participant (2%) was positive for dengue subtype-4. No patient samples had molecular evidence of chikungunya or Zika viruses. The T-Cor 8 multiplexing platform demonstrated a 71% sensitivity (95% confidence interval 29-96%), 93% specificity (95% confidence interval 81-99%), and 90% accuracy (95% confidence interval 78-97%) compared to the gold-standard assays on serum RNA samples. From this subset of data, we failed to identify important risk factors for arboviral infection.

Conclusion: From this limited subset of data, we conclude that the T-Cor 8 platform’s simplicity and accuracy in detecting at least dengue virus infections has considerable potential for clinical usefulness in low-resource settings.

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Zemke, Juliana Nash (2019). Detection of Dengue, Chikungunya, and Zika Viruses Among Patients in Sarawak, Malaysia by a Novel Multiplexing Platform. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/18844.

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