Effective Surveillance
Antimicrobial resistance (AMR)
AMR develops when bacteria, fungi or viruses are exposed to antibiotics, antifungals or antivirals. As a result, the antimicrobials become ineffective and infections may persist. In addition, medical interventions including surgery, chemotherapy and stem cell therapy may become impossible.
AMR is considered the biggest global threat of Health and Food Safety.
AMR Insights
For Officers at authorities, ministries, international organisations and NGO’s who wish to prevent the further global spreading of Antimicrobial resistance, AMR Insights offers selected, global information and data, specific education and extensive networking and partnering opportunities.
AMR Insights is for:
- Senior officials and (top) civil servants at national authorities
- Policy Officers at Ministries
- Civil servants at regional authorities
- Senior officials at international organizations
- Senior officials at NGO’s
Latest Topics
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05 January 2026Which European countries use the most antibiotics?
Antibiotic use across Europe varies widely, with several countries continuing to prescribe far more antibiotics than others, raising concerns for antimicrobial resistance. On average, EU antibiotic consumption reached about 20 defined daily doses per 1,000 inhabitants in 2024, slightly higher than before the COVID-19 pandemic and well above the EU’s 2030 reduction target of 15.9. […]
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05 January 2026From the lens of early-career researchers: bridging science, technology, arts, and humanities to tackle antimicrobial resistance
Antimicrobial resistance (AMR) constitutes a silent pandemic and a mounting global threat, demanding innovative and genuinely transdisciplinary responses. This initiative seeks to catalyse collaboration across the natural sciences, engineering, economics, social sciences, and the arts in order to address the multifaceted nature of AMR. It underscores the distinctive contribution of early-career researchers (ECRs) in driving […]
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22 December 2025Global Prediction of Antimicrobial Resistance Trends Using Statistical and Machine Learning Models: Evaluating National Action Plan Policy Impacts Through Interrupted Time Series Analysis
The study presents a data-driven global analysis of antimicrobial resistance (AMR), using statistical and machine learning models to forecast AMR trends and evaluate the effects of national action plans on resistance patterns. Clinical isolate data from 65 countries were analysed, revealing that AMR burdens are highest in low- and middle-income regions, particularly in Southeast Asia […]
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