Optimizing Antibiotic Use: Addressing Resistance Through Effective Strategies and Health Policies
Abstract
:1. Introduction
2. Mechanisms of Antibiotic Resistance
3. Causes of Antibiotic Resistance
4. Epidemiological and Economic Impact
5. European and Italian Healthcare Policies: Frameworks and Implementation
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study Author(s), Ref | Key Results | Implications |
---|---|---|
Alessandro Cassini at al. [39] | The estimated burden of antibiotic-resistant infections in the EU and EEA for 2015 was 671,689 infections, with 63.5% associated with healthcare. These infections led to approximately 33,110 attributable deaths and 874,541 DALYs. The burden was highest in infants (<1 year) and individuals aged 65 and older, with the greatest impact observed in Italy and Greece. | The increased burden of antibiotic-resistant infections highlights the need for prioritizing public health interventions, particularly for vulnerable populations such as infants and the elderly. Regional differences, like the higher burden in Italy and Greece, highlight the need for country-specific interventions. |
World Bank Projection, 2017 [42] | Two scenarios were proposed: a “low-AMR” scenario with moderate economic impacts, projecting a 0.2% global GDP decline by 2030 and $900 billion annual losses by 2030. In the “high-AMR” scenario, global GDP could fall by 3% by 2030, with losses reaching $2.8 trillion annually. Healthcare spending could rise by 7% globally by 2050, with low-income countries facing the highest increases. | AMR could cause economic damage similar to the 2008 financial crisis, with long-term global effects. Delays in treatment development, especially in low-income countries, will worsen global inequalities. Efficient resource allocation and public health interventions are crucial to mitigate AMR and ensure equitable healthcare. |
Andrea Maugeri et al. [58] | AMR was lower in countries with better indexes (p < 0.001), though not always linked to lower antibiotic consumption. Increased governance significantly reduced both antibiotic use (p < 0.001) and AMR (p = 0.006), with governance influencing AMR mainly through antibiotic consumption (31.5% effect). | The findings suggest that poor governance may contribute to high AMR levels, and reducing antibiotic use alone is insufficient to address AMR. Interventions to improve governance efficiency are essential for combating AMR at a global level. |
Khin Hnin Pwint et al. [59] | Antibiotic consumption in public hospitals decreased by 19% from 2014 to 2017. First-line antibiotics increased (42% to 54%), while broad-spectrum antibiotics decreased (46% to 38%). Quinolone use decreased, and only linezolid, a last-resort antibiotic, was procured. | Antibiotic consumption decreased in Myanmar’s public hospitals, providing a baseline for developing an antibiotic consumption surveillance system. |
Robin Vanstokstraeten et al. [61] | Between 2005 and 2017, E. coli blood isolates’ susceptibility to amoxicillin/clavulanic acid decreased from 90% to 50%. In 237 isolates, EUCAST and CLSI methods disagreed in 45% of cases, with EUCAST identifying more resistant strains in 94% of the discrepant results. EUCAST testing correlated better with the presence of beta-lactamase genes. | The study highlights low agreement between EUCAST and CLSI methods, with EUCAST identifying more resistant strains. This underscores the need for standardized testing and alignment with resistance mechanisms, like beta-lactamase genes. |
Antonia Sánchez-Bautista et al. [62] | Applying EUCAST breakpoints, aminoglycoside susceptibility in Gram-negative bacilli, especially Pseudomonas aeruginosa (23.2%), decreased, while aztreonam susceptibility also declined. Resistance to clindamycin (51.5%) and gentamicin (43.1%) increased in Staphylococcus aureus. | Switching from CLSI to EUCAST criteria changes resistance percentages and alters local resistance epidemiology. A multidisciplinary approach is needed to assess the impact on empirical treatment protocols. |
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Capuozzo, M.; Zovi, A.; Langella, R.; Ottaiano, A.; Cascella, M.; Scognamiglio, M.; Ferrara, F. Optimizing Antibiotic Use: Addressing Resistance Through Effective Strategies and Health Policies. Antibiotics 2024, 13, 1112. https://doi.org/10.3390/antibiotics13121112
Capuozzo M, Zovi A, Langella R, Ottaiano A, Cascella M, Scognamiglio M, Ferrara F. Optimizing Antibiotic Use: Addressing Resistance Through Effective Strategies and Health Policies. Antibiotics. 2024; 13(12):1112. https://doi.org/10.3390/antibiotics13121112
Chicago/Turabian StyleCapuozzo, Maurizio, Andrea Zovi, Roberto Langella, Alessandro Ottaiano, Marco Cascella, Manlio Scognamiglio, and Francesco Ferrara. 2024. "Optimizing Antibiotic Use: Addressing Resistance Through Effective Strategies and Health Policies" Antibiotics 13, no. 12: 1112. https://doi.org/10.3390/antibiotics13121112
APA StyleCapuozzo, M., Zovi, A., Langella, R., Ottaiano, A., Cascella, M., Scognamiglio, M., & Ferrara, F. (2024). Optimizing Antibiotic Use: Addressing Resistance Through Effective Strategies and Health Policies. Antibiotics, 13(12), 1112. https://doi.org/10.3390/antibiotics13121112