Comparative Performance Evaluation of Dengue Rapid Diagnostic Tests Detecting NS1 Antigen, IgM and IgG Antibodies for Diagnosis of Recent Dengue Infection

Every year, dengue outbreaks cause substantial humanitarian and economic hardship worldwide. Simple and cost-effective serological rapid diagnostic tests (RDTs) are currently the preferred methods widely used in laboratories and clinics in dengue-endemic areas. While the sensitivity and specificity of most of the RDTs have been studied, their diagnostic performance can vary across different settings and populations, highlighting the need for ongoing evaluations. This study evaluated the performance of five commercially available dengue RDTs for the detection of infection using the non-structural (NS1) antigen and IgM/IgG antibodies. Well-characterized archived dengue positive and confirmed dengue negative serum samples from the Aga Khan University, Pakistan, were screened. RDTs (SD Bioline Dengue Duo, Artron Dengue virus IgG/IgM and Ag cassette, Standard Q Dengue Duo, Humasis Dengue combo kit, and ALL Test Dengue Combo Rapid Test) were evaluated separately and in combination for the determination of diagnostic parameters (positive for NS1 and IgM). The enzyme-linked immunosorbent assay (ELISA) was considered the reference assay. The sensitivity of the RDTs ranged from 65.1% to 94.1% when compared to NS1 ELISA samples [255 NS1 positive and 175 NS1 negative samples], with the dengue virus IgG/IgM antibody and NS1 antigen cassette demonstrating the highest overall sensitivity. All RDTs showed a specificity of >99%. The dengue virus IgG/IgM antibody and NS1 antigen cassette (Artron Laboratories Inc.) achieved the highest overall diagnostic accuracy (96.3%). The dengue virus IgG/IgM antibody and NS1 antigen cassette (Artron Laboratories Inc.) achieved the highest overall diagnostic accuracy (96.28%). Dengue virus IgG/IgM antibody and NS1 antigen cassette showed the highest sensitivity and diagnostic accuracy, while all RDTs showed similar specificity. These findings highlight the importance of selecting appropriate diagnostic tests based on sensitivity and specificity.