Dengue diagnosis in an endemic area of Peru: Clinical characteristics and positive frequencies by RT-PCR and serology for NS1, IgM, and IgG
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Authors
Palomares-Reyes, CarlosSilva-Caso, Wilmer
del Valle, Luis J.
Aguilar-Luis, Miguel Angel
Weilg, Claudia
Martins-Luna, Johanna
Viñas-Ospino, Adriana
Stimmler, Luciana
Mallqui Espinoza, Naysha
Aquino Ortega, Ronald
Espinoza Espíritu, Walter
Misaico, Erika
del Valle-Mendoza, Juana
Issue Date
2019-04xmlui.metadata.dc.contributor.email
[email protected]
Metadata
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Elsevier B.V.Journal
International Journal of Infectious DiseasesDOI
10.1016/j.ijid.2019.01.022Additional Links
https://linkinghub.elsevier.com/retrieve/pii/S1201971219300335Abstract
Background: Huánuco is a central eastern region of Peru whose geography includes high forest and low jungle, as well as a mountain range that constitutes the inter-Andean valleys. It is considered a region endemic for dengue due to the many favorable conditions that facilitate transmission of the virus. Methods: A total of 268 serum samples from patients in Huánuco, Peru with an acute febrile illness were assessed for the presence of dengue virus (DENV) via RT-PCR and NS1, IgM, and IgG ELISA during December 2015 and March 2016. Results: DENV was detected in 25% of samples via RT-PCR, 19% of samples by NS1 antigen ELISA, and 10.5% of samples by IgM ELISA. DENV IgG was detected in 15.7% of samples by ELISA. The most frequent symptoms associated with fever across all groups were headache, myalgia, and arthralgia, with no significant difference between the four test methods Conclusions: In this study, DENV was identified in up to 25% of the samples using the standard laboratory method. In addition, a correlation was established between the frequency of positive results and the serological tests that determine NS1, IgM, and IgG. There is an increasing need for point-of-care tests to strengthen epidemiological surveillance in Peru.Type
info:eu-repo/semantics/articleRights
info:eu-repo/semantics/openAccessAttribution-NonCommercial-ShareAlike 3.0 United States
Language
engDescription
This work was supported by Cienciativa of CONCYTEC Peru, under contract number 164-2016-FONDECYT, and the Programa Nacional de Innovación para la Competitividad y Productividad (Innóvate Perú), under contract number 116-PNICP-PIAP-2015.ISSN
12019712ae974a485f413a2113503eed53cd6c53
10.1016/j.ijid.2019.01.022
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