Implementation of a Multiplex rRT-PCR for Zika, Chikungunya, and Dengue Viruses: Improving Arboviral Detection in an Endemic Region
Autor: | Ana Centurión, Belén Infanzón, Jesse J. Waggoner, Yvalena Guillén, Vicenta Rojas, Anibal Espínola, Teresa Cuevas, Fátima Cardozo, César Cantero, Benjamin A. Pinsky, Laura Aria, Clotilde Segovia, Alejandra Rojas, María Eugenia Acosta |
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Rok vydání: | 2020 |
Předmět: |
Adult
Male Adolescent Endemic Diseases viruses 030231 tropical medicine Biology Dengue virus medicine.disease_cause Virus Dengue fever Zika virus Dengue 03 medical and health sciences Young Adult 0302 clinical medicine Virology medicine Humans Multiplex Chikungunya Child Reference standards Reverse Transcriptase Polymerase Chain Reaction Zika Virus Infection virus diseases Articles biochemical phenomena metabolism and nutrition Middle Aged medicine.disease biology.organism_classification Infectious Diseases Paraguay Chikungunya Fever Parasitology Female Endemic diseases Multiplex Polymerase Chain Reaction |
Zdroj: | Am J Trop Med Hyg |
ISSN: | 1476-1645 |
Popis: | Arboviral diagnosis has been complicated throughout the tropical and subtropical Americas by the recent co-circulation of Zika virus (ZIKV), chikungunya virus (CHIKV), and dengue virus (DENV). The aim of this study was to implement a multiplex real-time RT-PCR (rRT-PCR) for ZIKV, CHIKV, and DENV in Paraguay to test patients who were clinically suspected of having dengue. We tested 110 sera from patients who presented to the Hospital de Clinicas in 2016 and had testing for DENV nonstructural protein 1 (NS1; 40 positive and 70 negative). Using a composite reference standard, we confirmed 51 dengue cases (46.4%): 38/40 NS1 positive and 13/70 NS1 negative. Chikungunya virus and ZIKV were detected in one sample each, both were DENV NS1 negative. The NS1 test demonstrated good agreement with rRT-PCR for DENV. However, multiplex rRT-PCR identified a subset of dengue cases and additional arboviral infections that would not be detected if NS1 assays are relied upon for diagnosis. |
Databáze: | OpenAIRE |
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