ArticleInfectious diseases and therapy2025
Conceptual Methodological Framework for Incorporating Antimicrobial Resistance Considerations in Economic Models for Pneumococcal Conjugate Vaccines.
Article in Infectious diseases and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
introductionAntimicrobial resistance (AMR) is a substantial global health threat and economic burden. Vaccines reduce antibiotic use and prevent resistant infections, combating AMR. However, their economic and health benefits are often underestimated because economic analyses do not consider vaccines' broader impacts, such as effects on AMR. We conceptualize a framework for estimating the impacts of vaccination on AMR using pneumococcal conjugate vaccines (PCVs) as an example.
methodsThe proposed framework includes three pathways: population and pathogen, care, and health outcomes. Operationalizing this framework requires extensive detailed data, such as serotype distribution, disease incidence, resistance profile, antibiotic use, and treatment failure, derived from multiple sources, such as national surveillance systems, epidemiological studies, and hospital records, which are often unavailable. However, considering vaccines' impact on AMR is crucial because of potential future health and cost issues. Therefore, we adopted a simplified framework leveraging all available data related to antibiotic prescriptions and resistance to estimate the impact on critical outcomes.
resultsRoutine PCV20 vaccination was estimated to prevent up to 23,509,406 antibiotic prescriptions and 14,050,115 antibiotic-resistant infections over 25 years compared to PCV13 and 12,087,128 antibiotic prescriptions and 7,245,908 antibiotic-resistant infections compared to PCV15, demonstrating the potential impact of PCV infant immunization on AMR cases and antibiotic prescriptions.
conclusionsA simplified model can effectively incorporate critical AMR parameters for a more comprehensive evaluation of PCVs. Our framework also identifies key data gaps that should be addressed for future modeling efforts.
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