The Conventional Diagnostic Techniques of Malaria in Endemic Areas: A Review of the Approaches with Focus on Newly Noninvasive Methods

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جامعة الشيخ عبدالله البدري
Abstract Background: Malaria continues to be a major global health problem, with over 228 million cases and 405,000 deaths estimated to occur annually. Rapid and accurate diagnosis of malaria is essential to decrease the burden and impact of this disease, particularly in children. We aimed to review the main available techniques for the diagnosis of clinical malaria in endemic settings and explore possible future options to improve its rapid recognition. Methods: Electronic databases including, Google, Google Scholar, PMC, PubMed, Science Direct, and Scopus were rigorously searched using the terms Malaria diagnosis, Microscopy for malaria, plasmodium detection, Rapid diagnostic tests, PCR for malaria for the completion of this descriptive review. Result: Literature review shows that Light microscopy is still considered the gold standard method for malaria diagnosis and continues to be at the frontline of malaria diagnosis. However, technologies such as rapid diagnostic tests, mainly those that detect histidine-rich protein-2, offer an accurate, fast, and affordable alternative for malaria diagnosis in endemic areas. They are now the technique most extended in endemic areas for parasitological confirmation. In these settings, PCR-based assays are usually restricted to research and they are not currently helpful in the management of clinical malaria. Other technologies, such as isothermal methods could be an exciting and alternative approach to PCR in the future. Conclusion: Available evidence suggests that the role of RDT, despite its increasing false negatives, is still the most feasible diagnostic test because it is easy to use, fast and does not need expensive equipment. Noninvasive tests that do not require a blood sample, but use saliva or urine, are some of the recent tests under development that have the potential to aid malaria control and elimination. Therefore, future innovation will be required to apply more sensitive and affordable methods in resource-limited settings