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# Antimicrobial resistance deaths linked to human antibiotic use across 114 countries
- URL: https://www.coios.me/antimicrobial-resistance-deaths-linked-to-human-antibiotic/
- Published: 2026-10-31T11:18:32.000Z
- Updated: 2026-11-01T07:06:39.000Z
- Description: In a modelled scenario, 10% less antibiotic use meant 38,000 fewer yearly antimicrobial resistance deaths, 0.50% of bacterial disease mortality.
- Author: Daniel Ryan
- Tags: Behavioural science, Infection and pandemics, World, #peer-reviewed, #refines, #item, #source-2026-10, #score-80

Weighted regression models estimated how antimicrobial resistance (AMR) relates to population-level antibiotic consumption across 7 drug classes. Data covered over 30 million isolates of 16 pathogens from 114 countries, 2000 to 2018, with country-level controls. Associations were strongest for Acinetobacter spp., Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli. A modelled 10% cut in antibiotic use was associated with 38,000 (95% CI 36,000–41,000) fewer annual AMR-attributable deaths. This was 0.50% of bacterial disease mortality globally, and 0.34% in sub-Saharan Africa. The main limitation is reliance on ecological relationships, with low-resource settings under-represented in the surveillance data.

*Why it is interesting: It puts a figure on the AMR mortality linked to modifiable antibiotic use. The modelled gain is small against total bacterial disease deaths, including in sub-Saharan Africa, where bacterial disease mortality is highest.*

Source

[PLOS Medicine, 26 October 2026](https://doi.org/10.1371/journal.pmed.1005140?ref=coios.me)

Paper

Burden of bacterial antimicrobial resistance associated with modifiable human antibiotic consumption: An observational study

Authors

Singer BJ, Gleason A, Impalli I, Nagorsen MD, Chae C, Granskog LC et al.

DOI

10.1371/journal.pmed.1005140

Type

Peer-reviewed article

Design

Observational ecological analysis of global AMR surveillance, >30 million isolates, 114 countries, 2000–2018, with weighted regression elasticity models and counterfactual simulation

Verdict

Refines prior evidence

Driver

[Infection and pandemics](https://www.coios.me/d-infectious-disease/)

Free full text

[Free to read at the publisher](https://doi.org/10.1371/journal.pmed.1005140?ref=coios.me)

Abstract — the authors' own words, CC BY

Background

Human antibiotic use is widely believed to contribute to the evolution and maintenance of antimicrobial resistance (AMR) in bacterial pathogens. While antibiotic stewardship should thus discourage use in situations where AMR-related harms outweigh clinical benefit, evidence to inform this assessment of tradeoffs is lacking, most notably in low-resource settings where gaps in antibiotic access persist. Quantitative understanding of use-resistance relationships is thus necessary as countries navigate commitments from the 2024 UN General Assembly resolution to reduce AMR burden by 2030\. Methods and findings

We used global surveillance data on AMR prevalence from 2000 to 2018 representing over 30 million bacterial isolates from 114 countries, along with antibiotic consumption estimates for each country and year, to estimate elasticity relationships between AMR and antibiotic exposure. Our analyses addressed 16 bacterial pathogens and antibiotic consumption across 7 drug classes, controlling for country-level health and development indicators via weighted regression models. Across pathogens, evidence that AMR is associated with population-level antibiotic exposure is strongest for Acinetobacter spp., Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli. In a modeled counterfactual scenario, we estimate that 10% lower levels of antibiotic use, in comparison to current levels, across classes, would be associated with 38,000 (95% confidence interval: 36,000-41,000) fewer annual deaths attributable to AMR globally. Although substantial, this total represents only 0.50% of estimated bacterial disease mortality. In sub-Saharan Africa, where risk of death due to bacterial disease is greatest, the modeled avertible burden of AMR-attributable deaths comprises only 0.34% of bacterial disease mortality. Key limitations of the study include reliance on ecological relationships to infer modifiable burden, and under-representation of low-resource settings in surveillance data on antibiotic consumption and AMR. Conclusions

Our findings suggest near-term achievable reductions in AMR-attributable deaths may be modest relative to the persisting burden of bacterial disease mortality. These estimates should inform assessments of the potential benefits and harms of restrictive versus permissive antibiotic use paradigms in epidemiologically distinct settings.