The Challenge of Diagnosing Asymptomatic Malaria During the Elimination Phase: An Implications for the Sensitivity of Laboratory Methods and Surveillance Strategies in Indonesia - Nurul Amalia (International Journal Labs, 2026)
Malaria remains a significant global health challenge, particularly during the elimination phase, where asymptomatic and sub microscopic infections become major obstacles to interrupting transmission. Individuals with asymptomatic malaria often do not seek treatment but may serve as hidden reservoirs that sustain parasite circulation in endemic communities. Conventional diagnostic methods, including microscopy and rapid diagnostic tests (RDTs), have limited sensitivity in detecting infections with low parasite density, creating challenges for accurate surveillance and case management. This study aims to analyze the challenges of diagnosing asymptomatic malaria, compare the sensitivity of available laboratory methods, and evaluate their implications for malaria elimination strategies in Indonesia. This study employed a literature review with an analytical-critical approach by reviewing scientific articles published between 2015 and 2025 from PubMed, Scopus, and Google Scholar. The reviewed studies focused on diagnostic performance comparisons among microscopy, RDT, polymerase chain reaction (PCR), quantitative PCR (qPCR), and loop-mediated isothermal amplification (LAMP). The findings indicate that microscopy and RDT have limited sensitivity in detecting sub microscopic infections, whereas molecular methods demonstrate superior diagnostic accuracy, with PCR and qPCR capable of identifying parasite densities below the detection limits of conventional approaches. However, the implementation of molecular diagnostics remains constrained by infrastructure, cost, and human resource limitations. In conclusion, malaria elimination in Indonesia requires an integrated diagnostic strategy combining conventional methods with selective molecular testing, strengthened laboratory capacity, and improved surveillance systems to detect hidden infections and prevent residual transmission.