Combining demographic shifts with age-based resistance prevalence to estimate future antimicrobial resistance burden in Europe and implications for targets: A modelling study
Bibliographic record
Abstract
BACKGROUND: Antimicrobial Resistance (AMR) is a global public health crisis. Evaluating intervention impact requires accurate estimates of how the AMR burden will change over time, given likely demographic shifts. This study aimed to provide an estimate of future AMR burden in Europe, investigating resistance variation by age and sex and the impact of interventions to achieve the proposed United Nations (UN) political declaration targets. METHODS AND FINDINGS: Using data from 12,807,473 bloodstream infection (BSI) susceptibility tests from routine surveillance in Europe, we estimate age- and sex-specific rates of change in BSI incidence for the 8 bacteria included in European Antimicrobial Resistance Surveillance Network (EARS-Net) surveillance over 2015-2019. This was used to project incidence rates by age and sex for 2022-2050 and, with demographic projections, to generate estimates of BSI burden (2022-2050). Two Bayesian hierarchical models were fitted across 38 bacteria-antibiotic combinations to the 2015-2019 resistance proportion of BSI by year and at the country-level with and without age and sex disaggregation. Inputting the incidence estimates into the "agesex" and "base" model, respectively, we sampled 1,000 model estimates of resistant BSI burden by age, sex, and country to determine the importance of age and sex disaggregation. We explored Intervention scenarios consisting of a 1, 5, or 20 per 100,000 per year reduction in infection incidence rate of change or 5 per 100,000 per year reduction in those older than 64 years. Overall, in Europe, BSI incidence rates are predicted to increase more in men than women across 6 of the 8 bacteria (Pseudomonas aeruginosa and Enterococcus faecium were the exception) and are projected to increase more dramatically in older age groups (74+ years) but stabilise or decline in younger age groups. We project huge country-level variation in resistance burden to 2050, with opposing trends in different countries for the same bacteria-antibiotic combinations (e.g., aminoglycoside-resistant Acinetobacter spp. ranged from a relative difference of 0.34 to 15.38 by 2030). Not accounting for age and sex results in differing resistance burden projections, with 47% of bacteria-antibiotic combinations estimated to have fewer resistant BSIs by 2030 compared to a model with age and sex. Not including age or sex resistance patterns results in fewer male cases for 76% (29/38) of the combinations compared to 11% (4/38) for women. We also saw age-based associations in projections with bigger differences at older ages. Achieving a 10% reduction in resistant BSI incidence by 2030 (equivalent to the UN 10% mortality target) was possible only for 68.4% (26/38) of bacteria-antibiotic combinations even with large reductions in BSI incidence rate of change of -20 per 100,000 per year. In some cases, a 10% reduction was followed by a rebound, with the resistant BSI burden exceeding previous levels by 2050. Limitations include reliance on European data and current trends, and the exclusion of factors such as comorbidities or ethnicity. CONCLUSIONS: Including country-specific, age- and sex-specific resistance levels alongside projected demographic shifts has a large impact on resistant BSI burden projections in Europe to 2030. Reducing this AMR infection burden by 10% will require substantial reductions in infection incidence rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".