Antimicrobial Resistance: Clinical, Epidemiological, and Public Health Perspectives on the Emerging Global Threat
Dr. Sanjeev Dimri¹ | Dr. R. Manohari Shivakumar² | Dr. Nidhi Tyagi³
¹Professor & HOD, Department of Microbiology, Saraswathi Institute of Medical Sciences, Hapur
²Prof Cum Principal, Obstetric and Gynecological Nursing (OBG), Saraswathi College of Nursing, Hapur
³Professor, Department of Pharmacology, Saraswathi College of Pharmacy, Hapur
Abstract
Antimicrobial resistance (AMR) has emerged as one of the most significant global health crises of the twenty-first century, threatening the clinical effectiveness of antimicrobial therapies and complicating the management of infectious diseases across all healthcare settings. The rapid evolution of resistant microorganisms is driven by inappropriate antibiotic use, healthcare-associated infections, environmental contamination, and international transmission of resistant pathogens. This cross-sectional analytical study examines the clinical and epidemiological patterns of AMR across 238 microbiological isolates collected from hospital laboratories and public health surveillance databases, using culture-based susceptibility testing, molecular resistance detection, and genomic surveillance. Descriptive statistics, ANOVA, and regression modelling examined associations between antimicrobial use patterns, healthcare exposure, and resistance prevalence. A significant increase in multidrug-resistant bacterial isolates was observed, particularly in intensive care units, with prior antibiotic exposure (F=7.18, p=0.001) and hospital department (F=6.42, p=0.003) emerging as the strongest predictors of resistance. Integrated AMR surveillance, digital health systems, and AI-powered diagnostic platforms are essential for addressing the AMR crisis. Digital transformation in healthcare delivery and precision medicine offer promising strategies for combating resistance through early detection and targeted therapy.
Keywords: Antimicrobial resistance, multidrug resistance, clinical microbiology, epidemiology, public health, AI diagnostics, genomic surveillance.
