# An integrated framework for antimicrobial resistance: links with climate change and vulnerability

**Authors:** Estibaliz Baroja, Inmaculada Batalla, Maria Jose Sanz, Aline Chiabai

PMC · DOI: 10.3389/fpubh.2025.1679189 · 2026-02-03

## TL;DR

This paper introduces a new framework linking climate change and antimicrobial resistance, highlighting how vulnerabilities increase health risks.

## Contribution

The novel contribution is an integrated framework combining climate change and AMR risks using the mDPSEEA model and IPCC vulnerability concepts.

## Key findings

- The framework identifies vulnerable groups at higher risk from AMR, such as children and those in contaminated environments.
- Addressing AMR requires coordinated policies on infectious diseases, chronic diseases, and environmental hazards.
- Climate change, pollution, and social inequalities are interconnected and must be tackled together to combat AMR.

## Abstract

Antimicrobial resistance (AMR) has been extensively studied in clinical settings; however, research on the environmental aspects of AMR is relatively new. Recently, there has been growing interest in the relationship between climate change and AMR, yet evidence linking AMR to climate change and potential environmental transmission is very limited. Even less is understood about how vulnerabilities may exacerbate exposure and associated health risks. This study aims to compile literature on recent research on how climate change exacerbates risks associated with AMR. The study builds a framework based on this review that connects the amplifying effects of climate change to AMR risk using the modified DPSEEA (mDPSEEA) model. Additionally, the framework complements the mDPSEEA context by incorporating the vulnerability concept of the Intergovernmental Panel on Climate Change (IPCC) risk framework, which encompasses susceptibility and limited coping capacity to face exposure and potential health impacts of AMR. The integrated framework facilitates systemic analysis of the combined risk of climate change and AMR in its early stages, particularly within the driver-pressure-state interface. It also helps to identify vulnerable groups most likely to experience severe effects from AMR, such as the older adult(s), children, individuals with pre-existing chronic conditions, those at higher occupational risk of being colonised by antibiotic-resistant bacteria (ARB), and populations living in highly contaminated environments. The framework analysis emphasises that addressing AMR requires more than just isolated interventions; it demands a fundamental rethinking of public health planning and agendas. There is a need to develop strategies that coordinate various policy frameworks, including those about infectious diseases, chronic diseases and environmental hazards. Tackling climate change, pollution, and social inequalities is essential for combating AMR, as their interconnectedness cannot be overlooked.

## Full-text entities

- **Genes:** SERPINA2 (serpin family A member 2 (gene/pseudogene)) [NCBI Gene 390502] {aka ARGS, ATR, PIL, SERPINA2P, psiATR}
- **Diseases:** cognitive impairment (MESH:D003072), frailty (MESH:D000073496), bacterial infectious diseases (MESH:D003141), chronic diseases (MESH:D002908), bloodstream infections (MESH:D018805), cardiovascular, neoplasm, (MESH:D018376), salmonellosis (MESH:D012480), malaria (MESH:D008288), respiratory, diabetes and kidney, (MESH:D003928), Zika (MESH:D000071243), gram-negative bacteraemia (MESH:D016905), mDPSEEA (MESH:C564098), tuberculosis (MESH:D014376), NCDs (MESH:D000073296), bacterial infections (MESH:D001424), dengue fever (MESH:D003715), wound infections (MESH:D014946), asthma (MESH:D001249), Lyme disease (MESH:D008193), infection (MESH:D007239), IPCC (MESH:D009402), cancer (MESH:D009369), AMR (MESH:D060467), waterborne diseases (MESH:D000069578), diabetes (MESH:D003920), malnutrition (MESH:D044342), death (MESH:D003643), ARB (MESH:C000719206), sarcopenia (MESH:D055948), infectious respiratory diseases (MESH:D012141)
- **Chemicals:** Mn (MESH:D008345), heavy metals (MESH:D019216), Pb (MESH:D007854), beta-lactam (MESH:D047090), As (MESH:D001151), Cd (MESH:D002104), Cu (MESH:D003300), Fe (MESH:D007501), carbapenem (MESH:D015780), water (MESH:D014867), CO2 (MESH:D002245), ciprofloxacin (MESH:D002939), rifampicin (MESH:D012293), cephalosporins (MESH:D002511), Ni (MESH:D009532), Cr (MESH:D002857), nitrogen (MESH:D009584), methane (MESH:D008697), phosphorus (MESH:D010758), Hg (MESH:D008628), Zn (MESH:D015032), gatifloxacin (MESH:D000077734), ARB (-), metals (MESH:D008670)
- **Species:** Enterobacterales (order) [taxon 91347], Gallus gallus (bantam, species) [taxon 9031], Bos taurus (bovine, species) [taxon 9913], Vibrio vulnificus (species) [taxon 672], human metagenome (species) [taxon 646099], Klebsiella pneumoniae (species) [taxon 573], Homo sapiens (human, species) [taxon 9606], Staphylococcus aureus (species) [taxon 1280], Pseudomonas aeruginosa (species) [taxon 287], Salmonella (genus) [taxon 590], Vibrio (genus) [taxon 662], Escherichia coli (E. coli, species) [taxon 562], Ostreidae (oysters, family) [taxon 6563]

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12909482/full.md

---
Source: https://tomesphere.com/paper/PMC12909482