Digital misinformation and antimicrobial stewardship: cross-platform epidemiologic signals from a decade of online discourse (2015–2025)

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.