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Healthcare-associated infections (HAIs) represent a major global public health challenge due to their significant morbidity, mortality, and substantial economic burden. This study presents a comprehensive bibliometric analysis of the scientific literature at the intersection of healthcare-associated infections, epidemiological surveillance, and innovative technologies in hospital settings over the past decade. A corpus of 149 peer-reviewed articles published between 2014 and 2025 was systematically identified from Scopus using a targeted search strategy combining HAI terminology, surveillance concepts, and technological innovation terms. Analysis was conducted using R software and Biblioshiny, employing descriptive analysis, keyword co-occurrence network analysis, and factorial analysis to map the intellectual structure and thematic evolution of the field. Results reveal sustained growth in scientific production, peaking in 2023, coinciding with the COVID-19 pandemic. Three principal thematic clusters emerged: (1) traditional infection prevention and control practices centered on hand hygiene and protocol compliance; (2) digital transformation integrating electronic health records, artificial intelligence, and machine learning for surveillance optimization; and (3) microbiological approaches encompassing antimicrobial resistance and advanced genomic techniques including whole genome sequencing. Factorial and hierarchical cluster analyses confirm progressive convergence among conventional prevention practices, microbiological challenges, and computational innovations. The study demonstrates a paradigm shift from traditional prevention-focused approaches toward an integrated, interdisciplinary, and digitally-enabled surveillance framework. These findings provide valuable insights for researchers, funding agencies, and healthcare administrators to make evidence-informed decisions regarding research priorities and technology investments in HAI surveillance.

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Healthcare-Associated Infection Surveillance in the Digital Age: A Decade of Convergence among Prevention Practices, AI Technologies, and Genomic Methods (2014–2025)

  • 会议论文

  • 发表日期：

    2026年

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  • Mohammed Amine Lafraxo,
  • Kawtar Kharti,
  • Ouassima Erefai,
  • Said Ezrari,
  • Ikram Douelfiqar,
  • Samia Essadki,
  • Abdel Bacite Zarouali,
  • Abderrazak Saddari,
  • Abdelmajid Soulaymani,
  • Hinde Hami

摘要

Healthcare-associated infections (HAIs) represent a major global public health challenge due to their significant morbidity, mortality, and substantial economic burden. This study presents a comprehensive bibliometric analysis of the scientific literature at the intersection of healthcare-associated infections, epidemiological surveillance, and innovative technologies in hospital settings over the past decade. A corpus of 149 peer-reviewed articles published between 2014 and 2025 was systematically identified from Scopus using a targeted search strategy combining HAI terminology, surveillance concepts, and technological innovation terms. Analysis was conducted using R software and Biblioshiny, employing descriptive analysis, keyword co-occurrence network analysis, and factorial analysis to map the intellectual structure and thematic evolution of the field. Results reveal sustained growth in scientific production, peaking in 2023, coinciding with the COVID-19 pandemic. Three principal thematic clusters emerged: (1) traditional infection prevention and control practices centered on hand hygiene and protocol compliance; (2) digital transformation integrating electronic health records, artificial intelligence, and machine learning for surveillance optimization; and (3) microbiological approaches encompassing antimicrobial resistance and advanced genomic techniques including whole genome sequencing. Factorial and hierarchical cluster analyses confirm progressive convergence among conventional prevention practices, microbiological challenges, and computational innovations. The study demonstrates a paradigm shift from traditional prevention-focused approaches toward an integrated, interdisciplinary, and digitally-enabled surveillance framework. These findings provide valuable insights for researchers, funding agencies, and healthcare administrators to make evidence-informed decisions regarding research priorities and technology investments in HAI surveillance.