Abstract

Malaria remains one of the most pressing global health challenges, with hundreds of millions of cases annually and 
a disproportionate impact on sub-Saharan Africa and South Asia. Accurate and timely diagnosis is essential for 
effective case management, disease surveillance, and elimination strategies. Traditional diagnostic methods such as 
microscopy and rapid diagnostic tests (RDTs) continue to play a central role, but their limitations in sensitivity, 
species differentiation, and field applicability highlight the need for innovation. Advances in molecular diagnostics, 
including polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and serological 
methods, have enhanced detection capabilities, though high costs and infrastructure requirements restrict 
widespread deployment. More recent innovations, such as next-generation sequencing (NGS), CRISPR-based 
diagnostics, and portable point-of-care technologies, offer promising opportunities to overcome persistent 
diagnostic gaps. However, challenges remain in integrating these tools into health systems, addressing ethical 
issues around data privacy and informed consent, and ensuring accessibility in resource-limited settings. This 
review synthesizes existing knowledge on traditional and emerging malaria diagnostic technologies, examines 
their strengths and weaknesses, and explores pathways to their sustainable adoption for global malaria control and 
eventual elimination.