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This review addresses the challenges in diagnosing and managing scrub typhus, an infection caused by Orientia tsutsugamushi, focusing on the potential of precision medicine. It synthesizes advances in host biomarkers (IL-6, TNF-α, CRP), genomic characterization of O. tsutsugamushi, and AI-driven predictive analytics for improved diagnosis and risk stratification. The review also explores novel therapeutic strategies targeting host immune modulation and pathogen persistence to complement antibiotic treatment.
Precision medicine approaches, including biomarkers and AI-driven risk stratification, show promise for improving outcomes in scrub typhus by enabling earlier diagnosis and individualized treatment.
Orientia tsutsugamushi, the causative agent of scrub typhus, is a re-emerging vector-borne pathogen associated with substantial morbidity and mortality across the Asia–Pacific region and is increasingly reported in Africa and South America. Diagnosis remains challenging due to nonspecific febrile presentation, inconsistent appearance of eschar, and marked antigenic heterogeneity, often resulting in delayed or inappropriate treatment. Although doxycycline and azithromycin are effective, current therapeutic strategies do not account for inter-individual variability in immune responses, pathogen burden, pharmacokinetics, or the risk of severe complications such as acute respiratory distress syndrome, myocarditis, and multiorgan failure. Advances in precision medicine offer transformative opportunities to improve scrub typhus management. Host biomarkers, including interleukin-6, tumor necrosis factor-α, C-reactive protein, procalcitonin, and endothelial activation markers, enable stratification of disease severity, early prediction of complications, and personalization of therapy. Genomic characterization of O. tsutsugamushi strains facilitates identification of strain-specific antigenic signatures and virulence factors, supporting the development of tailored diagnostics and next-generation vaccines. Machine learning and artificial intelligence models integrating clinical, laboratory, and imaging data are emerging as powerful tools for early risk stratification, enabling timely therapeutic decisions even in resource-limited settings. Concurrently, novel therapeutic strategies targeting host immune modulation, angiogenesis pathways, and pathogen persistence are being explored to complement antibiotics and address resistance and relapse. This review synthesizes current advances in biomarkers, AI-driven predictive analytics, and emerging therapies to propose a precision medicine framework for earlier diagnosis, individualized treatment, and improved outcomes in scrub typhus.
