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Co-circulation of dengue virus 1 and 2 several years after single serotype detection in Cross River State, Nigeria
Author(s) -
A.B. Onoja,
Uwem George,
I.S. Gadzama
Publication year - 2020
Publication title -
sokoto journal of veterinary sciences
Language(s) - English
Resource type - Journals
eISSN - 2315-6201
pISSN - 1595-093X
DOI - 10.4314/sokjvs.v18i3.7
Subject(s) - dengue virus , dengue fever , abia , serotype , local government area , virology , serology , veterinary medicine , environmental health , medicine , geography , immunology , local government , archaeology , antibody
Dengue is a mosquito-borne viral disease which affects over 390 million people annually around the world. High rates of unrecognized dengue infections have been observed in Nigeria through serological assays. This informed molecular investigation in some areas where previous reports were made. We screened individuals in a rural community in Nigeria for circulating dengue virus serotypes. Using a community based participatory approach, convenient sampling was employed to collect plasma from 17 febrile adults in Abia and Bendeghe wards within Etung Local Government Area of Cross River State, Nigeria. The area is forested with heavy mosquito presence. RNA extraction was carried out with viral RNA mini kit (QIAamp, QIAGEN GmbH, Hilden, Germany). Molecular detection of DENV serotypes was by Polymerase Chain Reaction using characterized DENV isolates as standard controls. Out of 17 participants, 3 (17.6%) tested positive to DENV. Two were infected with DENV-2 and one with DENV-1. All three were men in Abia ward while no person tested positive to the virus in Bendeghe. This present study highlights co-circulation of DENV-1 which demonstrates a change in the epidemiology of dengue in the area. It reinforces the need for public health professionals in the area to be vigilant, and signals the possibility of an increase in Dengue Hemorrhagic Fever. Sustained entomological surveillance is recommended. Keywords: Dengue, Cross River State, Molecular detection, Nigeria, Rain forest

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