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Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Digital misinformation and antimicrobial stewardship: cross-platform epidemiologic signals from a decade of online
1Assistance Medical Sciences, University of Tabukhttps://ror.org/04yej8x59, Saudi Arabia.
Objective:
To quantify antibiotic-related misinformation across major social networking platforms and examine its potential relevance to antimicrobial stewardship(AMS) and healthcare epidemiology.
Design:
A retrospective, Cross-platform infodemiology study (2015-2025).
Setting:
Public data from Twitter/X, Reddit, and Facebook were analyzed, and a temporal association with global antimicrobial-resistance measures from the World Health Organization's Global Antimicrobial Resistance(AMR) Surveillance System.
Methods:
We extracted 1.8 million posts containing antibiotic-related key terms. Natural-language processing and transformer-based classification identified misinformation themes, sentiment polarity, and diffusion dynamics. Topic modeling and network analysis (Gephi) characterized echo-chamber structures. Temporal associations between misinformation intensity and antimicrobial-resistance indicators were examined using cross-correlation and Granger lead-lag analysis.
Results:
Misinformation comprised 19.3% of posts, spreading 2.4 times faster than factual content (p <.001). Four dominant themes were identified: self-medication advocacy, natural-remedy promotion, misinformation alleging hidden motives or suppressed evidence, and anti-medical discourse. Misinformation intensity correlated strongly with antibiotic search intent (ρ = .74; p <.001) and preceded resistance trends by 6-9 months for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus.
Conclusions:
Antibiotic misinformation may function as a measurable behavioral exposure with potential relevance to AMS and infection prevention goals. The inclusion of digital-behavioral surveillance in AMS reporting platforms would offer warning signs for potential risks associated with antibiotic resistance.
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