<![CDATA[Background: Dengue and malaria co-infection pose significant diagnostic challenges due to overlapping symptoms, leading to potential misdiagnosis and severe health outcomes. This systematic review explores diagnostic challenges, recent advancements in diagnostic technologies, and the impact of rapid diagnostic tests (RDTs) on clinical outcomes.
Subjects and Method: This systematic review accesses the diagnostic challenges and innovations in detecting dengue and malaria co-infection in four African countries (Cameroon, Kenya, Nigeria, and Sudan). A systematic search was conducted usings several of electronic databases, such as PubMed, Google Scholar, Medline, Web of Science, and Scopus. The literature search across five databases (2014–2024) yielded 135 studies; 10 met inclusion criteria. These studies, mostly quantitative, used diagnostic methods like microscopy, RDTs, ELISA, PCR, and machine learning, focusing on febrile patients. Inclusion criteria required peer-reviewed English articles involving both diseases. Three studies used mixed methods and were appraised using CASP tools.
Results: From the 10 articles used in this review several key themes were identified such as diagnostic accuracy, technological advancements, clinical impact of RDTs, and practice recommendations. The review found significant variations in diagnostic methods, including microscopy, serological tests, PCR, and RDTs. Traditional methods like microscopy, while commonly used, often suffer from variable accuracy due to dependency on operator skill and equipment quality. Innovations such as PCR and advanced serological tests offer higher accuracy but face barriers related to cost and accessibility in resource-limited settings. RDTs showed potential in improving diagnostic timeliness and accuracy, enhancing clinical outcomes. However, their sensitivity and specificity varied, highlighting the need for further validation and standardization.
Conclusion: The study advocates for continuous innovation in diagnostic technologies and the implementation of cost-effective, accurate, and accessible diagnostic methods.]]>
