Evidence map›Paper›PMID 40989200›Full record

ArticleRwanda journal of medicine and health sciences2025

Risk Modelling and Seroprevalence of Dengue Virus Non-structural protein-1 Antigenemia and Antibodies among Febrile Patients in Ilorin, Nigeria.

Mutiat Busayo Odebisi-Omokanye, Suleiman Muhammed Mustapha, Udeze Augustine Okechukwu, Oladimeji Melody Oluwabunmi, Omotoyinbo Stella Oluwabusayo

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Article in Rwanda journal of medicine and health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Mutiat Busayo Odebisi-OmokanyeMicrobiology, Faculty of Life Sciences, University of Ilorin, Ilorin, Kwara Nigeria.
Suleiman Muhammed MustaphaMicrobiology, Summit University Offa, Offa, Kwara, Nigeria.
Udeze Augustine OkechukwuMicrobiology, Faculty of Life Sciences, University of Ilorin, Ilorin, Kwara Nigeria.
Oladimeji Melody OluwabunmiMicrobiology, Faculty of Life Sciences, University of Ilorin, Ilorin, Kwara Nigeria.
Omotoyinbo Stella OluwabusayoMicrobiology, Faculty of Life Sciences, University of Ilorin, Ilorin, Kwara Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dengue fever is one of the global arboviral diseases posing significant health challenges, particularly in tropical and subtropical regions. However, there is limited data on the seroprevalence and risk factors of dengue virus infection among febrile patients in this region, and no studies have combined risk modelling and serological analysis for its disease surveillance. Objectives: This study determines the seroprevalence and risk analysis of Dengue Virus Non-structural protein 1 antigen and Immunoglobulin G and M antibodies among febrile patients in Ilorin, Nigeria. Methods: A cross-sectional study using a finite population correction (FPC) approach, where 182 blood samples were collected from consenting febrile patients and screened for DNV immunological markers. A structured questionnaire was used for socio-demographic and risk factors collation, while data analysis and Generalized Linear Model (GLM) were used for risk impact assessment on DNV outcome. Results: Prevalence of DNV NS1 antigen, IgG and IgM antibodies was 36% (66), 32% (62) and 16% (29), respectively. At 26 years mean age, the highest prevalence was recorded among female subjects, the employed groups and participants with formal education. The effect of age and gender was statistically significant at P<0.05, while occupation was not. The GLM presented the combined risk factors as strong predictors of DNV infection outcome at p (Slope=0) = 2.9259×10-9. Conclusions: High prevalence of dengue virus and significant association of risk factors was determined. Inclusion of DNV screening for febrile patients to reduce anti-malaria resistance is advocated.

Indexed as

Aedes MosquitoDengueMalariaModellingResistance

Identifiers

PMID40989200
PMCPMC12451773

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