Parasitic infections remain a major global public health challenge, disproportionately affecting populations in low- and middle-income countries and contributing to significant morbidity, mortality, and socioeconomic burden. Accurate and timely diagnosis is essential for effective disease control; however, conventional diagnostic methods, including microscopy, serology, and molecular assays, exhibit important limitations in sensitivity, specificity, and field applicability, particularly in early-stage and low-intensity infections. In recent years, advances in omics technologies have enabled the identification of emerging biomarkers that provide dynamic and highly sensitive indicators of host–parasite interactions. This review provides a comprehensive overview of emerging biomarkers for human parasitic infections, including parasite-derived markers such as circulating cell-free DNA, extracellular vesicles, microRNAs, and novel antigens, as well as host-derived signatures such as microRNAs, cytokine profiles, proteomic, and metabolomic biomarkers. These biomarkers offer significant advantages, including early detection, improved sensitivity in low-parasite-burden infections, and the ability to reflect real-time infection status and treatment response. However, their clinical translation remains constrained by challenges such as biological variability, lack of standardization, and the need for advanced analytical platforms. The integration of multi-omics approaches, coupled with machine learning and the development of point-of-care technologies, represents a promising strategy to overcome these limitations. Emerging biomarkers are poised to transform the diagnostic landscape of parasitic diseases by enabling more precise, non-invasive, and scalable diagnostic solutions, ultimately supporting improved disease management and global control efforts.
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Grari et al. (2026) studied this question.
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