Trend AnalysisOther Sciences
Antimicrobial Resistance Meets Climate Change: A One Health Crisis
Antimicrobial resistance kills nearly 5 million people annually—and climate change is making it worse. Rising temperatures accelerate bacterial growth, increase antimicrobial use in livestock, and expand the geographic range of resistant pathogens. The One Health approach is the necessary response.
By Sean K.S. Shin
This blog summarizes research trends based on published paper abstracts. Specific numbers or findings may contain inaccuracies. For scholarly rigor, always consult the original papers cited in each post.
Antimicrobial resistance (AMR) currently contributes to nearly 5 million deaths annually worldwide—more than HIV/AIDS or malaria. Projections suggest this could reach 10 million by 2050 if current trends continue. What makes this projection even more concerning is that climate change—an independently catastrophic phenomenon—is accelerating AMR through multiple interacting pathways. Rising temperatures increase bacterial growth rates and mutation frequencies. Warmer climates expand the geographic range of resistant pathogens. Climate-related agricultural intensification drives antimicrobial overuse in livestock. The interaction between AMR and climate change is not merely additive; it is potentially synergistic.
The Research Landscape
AMR as Climate-Sensitive Disease
Alhassan (2026) proposes a paradigm shift: framing veterinary AMR not merely as a drug resistance problem but as a climate-sensitive emerging infectious disease. The argument is that the environmental conditions that drive AMR emergence—temperature, humidity, water quality, animal density—are all affected by climate change. As these conditions shift, AMR patterns will shift with them, in ways that current surveillance systems are not designed to detect.
The specific pathways include:
- Temperature-dependent resistance: Laboratory and field studies show that bacterial resistance gene transfer rates increase at higher temperatures. In a warming world, the baseline rate of resistance emergence accelerates.
- Water contamination: Climate-driven flooding spreads resistant bacteria from agricultural runoff, sewage, and healthcare waste into drinking water and recreational water—creating new exposure pathways.
- Livestock intensification: Climate-related crop failures and changing grazing conditions push farmers toward more intensive livestock production, which requires more antimicrobials for prophylaxis—a cycle of intensification and resistance.
Foodborne Bacteria in Low- and Middle-Income Countries
Alhassan et al. (2025), with 1 citation, focus specifically on foodborne AMR in low- and middle-income countries (LMICs), where the intersection of climate vulnerability, food safety challenges, and limited surveillance capacity creates compounding risks.
Their analysis documents how climate change affects foodborne AMR pathways:
- Food production: Higher temperatures reduce food safety margins, increasing pathogen growth during storage and transport. Farmers in climate-stressed regions may increase antimicrobial use to compensate for deteriorating production conditions.
- Food distribution: Climate-related disruptions to cold chains (power outages during heatwaves, infrastructure damage during floods) extend the time food spends at temperatures that favor bacterial growth and resistance transfer.
- Food consumption: Climate-driven migration and urbanization concentrate populations in settings where food safety regulation is weak and AMR surveillance is minimal.
The paper argues that LMICs are disproportionately affected because they have the least capacity for surveillance, the weakest food safety regulation, and the highest dependence on antimicrobials for food production.
Comprehensive Driver Analysis
Ye, Li, and Alhassan (2026), with 17 citations, provide the most comprehensive analysis of AMR drivers from a One Health perspective. Their review identifies drivers across human, animal, and environmental domains:
Human domain: Overuse of antibiotics in human medicine (particularly in LMICs where antibiotics are available without prescription), incomplete treatment courses, and hospital-acquired resistant infections.
Animal domain: Prophylactic use of antibiotics in livestock (to prevent disease in crowded conditions), growth promotion (banned in many countries but still practiced in others), and aquaculture (where antibiotics enter aquatic ecosystems directly).
Environmental domain: Antibiotic residues in wastewater, agricultural runoff carrying resistant bacteria into water systems, and environmental reservoirs where resistance genes persist and transfer between species.
The key insight: AMR is a systems problem that cannot be solved by addressing any single domain. Reducing antibiotic prescribing in human medicine is insufficient if agricultural use continues unchecked. Improving hospital infection control is insufficient if resistant bacteria circulate in the environment.
One Health Integration
Msemakweli, Mzuka, and Osward (2024), with 3 citations, focus on the practical challenge of implementing One Health approaches to AMR. The review documents that while the One Health framework is widely endorsed in policy documents, actual integration of human, animal, and environmental surveillance remains rare. Most countries maintain separate surveillance systems for human AMR, veterinary AMR, and environmental contamination—systems that use different methodologies, different sampling strategies, and different reporting formats.
Critical Analysis: Claims and Evidence
<
| Claim | Evidence | Verdict |
|---|
| Climate change accelerates AMR through temperature, water, and agricultural pathways | Alhassan's pathway analysis | ✅ Supported — multiple mechanisms documented |
| LMICs are disproportionately affected by foodborne AMR-climate interactions | Alhassan et al.'s LMIC-focused analysis | ✅ Supported — structural vulnerabilities documented |
| AMR is a systems problem requiring One Health integration | Ye et al.'s multi-domain driver analysis | ✅ Supported — drivers span human, animal, and environmental domains |
| Actual One Health surveillance integration remains rare | Msemakweli et al.'s implementation review | ✅ Supported — policy endorsement exceeds operational integration |
Open Questions
Predictive modeling: Can AMR-climate models predict geographic shifts in resistance patterns? Such models could guide preemptive surveillance investment.Alternative approaches: Can phage therapy, antimicrobial peptides, or other alternatives reduce reliance on conventional antibiotics in both human and veterinary medicine?Economic incentives: Antimicrobial overuse is economically rational for individual farmers and patients. What incentive structures would align individual behavior with collective AMR reduction?Governance: AMR and climate change are both global problems requiring coordinated action. Can existing governance structures (WHO, OIE, UNEP) provide adequate coordination, or are new institutions needed?What This Means for Your Research
For veterinary and public health researchers, the AMR-climate nexus represents a research frontier where two global crises interact in ways that are just beginning to be understood.
For policymakers, the One Health integration gap—between policy endorsement and operational surveillance—is the most actionable finding. Investment in cross-domain surveillance infrastructure is needed now, not after the next pandemic.
Explore related work through ORAA ResearchBrain.
Antimicrobial resistance (AMR) currently contributes to nearly 5 million deaths annually worldwide—more than HIV/AIDS or malaria. Projections suggest this could reach 10 million by 2050 if current trends continue. What makes this projection even more concerning is that climate change—an independently catastrophic phenomenon—is accelerating AMR through multiple interacting pathways. Rising temperatures increase bacterial growth rates and mutation frequencies. Warmer climates expand the geographic range of resistant pathogens. Climate-related agricultural intensification drives antimicrobial overuse in livestock. The interaction between AMR and climate change is not merely additive; it is potentially synergistic.
The Research Landscape
AMR as Climate-Sensitive Disease
Alhassan (2026) proposes a paradigm shift: framing veterinary AMR not merely as a drug resistance problem but as a climate-sensitive emerging infectious disease. The argument is that the environmental conditions that drive AMR emergence—temperature, humidity, water quality, animal density—are all affected by climate change. As these conditions shift, AMR patterns will shift with them, in ways that current surveillance systems are not designed to detect.
The specific pathways include:
- Temperature-dependent resistance: Laboratory and field studies show that bacterial resistance gene transfer rates increase at higher temperatures. In a warming world, the baseline rate of resistance emergence accelerates.
- Water contamination: Climate-driven flooding spreads resistant bacteria from agricultural runoff, sewage, and healthcare waste into drinking water and recreational water—creating new exposure pathways.
- Livestock intensification: Climate-related crop failures and changing grazing conditions push farmers toward more intensive livestock production, which requires more antimicrobials for prophylaxis—a cycle of intensification and resistance.
Foodborne Bacteria in Low- and Middle-Income Countries
Alhassan et al. (2025), with 1 citation, focus specifically on foodborne AMR in low- and middle-income countries (LMICs), where the intersection of climate vulnerability, food safety challenges, and limited surveillance capacity creates compounding risks.
Their analysis documents how climate change affects foodborne AMR pathways:
- Food production: Higher temperatures reduce food safety margins, increasing pathogen growth during storage and transport. Farmers in climate-stressed regions may increase antimicrobial use to compensate for deteriorating production conditions.
- Food distribution: Climate-related disruptions to cold chains (power outages during heatwaves, infrastructure damage during floods) extend the time food spends at temperatures that favor bacterial growth and resistance transfer.
- Food consumption: Climate-driven migration and urbanization concentrate populations in settings where food safety regulation is weak and AMR surveillance is minimal.
The paper argues that LMICs are disproportionately affected because they have the least capacity for surveillance, the weakest food safety regulation, and the highest dependence on antimicrobials for food production.
Comprehensive Driver Analysis
Ye, Li, and Alhassan (2026), with 17 citations, provide the most comprehensive analysis of AMR drivers from a One Health perspective. Their review identifies drivers across human, animal, and environmental domains:
Human domain: Overuse of antibiotics in human medicine (particularly in LMICs where antibiotics are available without prescription), incomplete treatment courses, and hospital-acquired resistant infections.
Animal domain: Prophylactic use of antibiotics in livestock (to prevent disease in crowded conditions), growth promotion (banned in many countries but still practiced in others), and aquaculture (where antibiotics enter aquatic ecosystems directly).
Environmental domain: Antibiotic residues in wastewater, agricultural runoff carrying resistant bacteria into water systems, and environmental reservoirs where resistance genes persist and transfer between species.
The key insight: AMR is a systems problem that cannot be solved by addressing any single domain. Reducing antibiotic prescribing in human medicine is insufficient if agricultural use continues unchecked. Improving hospital infection control is insufficient if resistant bacteria circulate in the environment.
One Health Integration
Msemakweli, Mzuka, and Osward (2024), with 3 citations, focus on the practical challenge of implementing One Health approaches to AMR. The review documents that while the One Health framework is widely endorsed in policy documents, actual integration of human, animal, and environmental surveillance remains rare. Most countries maintain separate surveillance systems for human AMR, veterinary AMR, and environmental contamination—systems that use different methodologies, different sampling strategies, and different reporting formats.
Critical Analysis: Claims and Evidence
<
| Claim | Evidence | Verdict |
|---|
| Climate change accelerates AMR through temperature, water, and agricultural pathways | Alhassan's pathway analysis | ✅ Supported — multiple mechanisms documented |
| LMICs are disproportionately affected by foodborne AMR-climate interactions | Alhassan et al.'s LMIC-focused analysis | ✅ Supported — structural vulnerabilities documented |
| AMR is a systems problem requiring One Health integration | Ye et al.'s multi-domain driver analysis | ✅ Supported — drivers span human, animal, and environmental domains |
| Actual One Health surveillance integration remains rare | Msemakweli et al.'s implementation review | ✅ Supported — policy endorsement exceeds operational integration |
Open Questions
Predictive modeling: Can AMR-climate models predict geographic shifts in resistance patterns? Such models could guide preemptive surveillance investment.Alternative approaches: Can phage therapy, antimicrobial peptides, or other alternatives reduce reliance on conventional antibiotics in both human and veterinary medicine?Economic incentives: Antimicrobial overuse is economically rational for individual farmers and patients. What incentive structures would align individual behavior with collective AMR reduction?Governance: AMR and climate change are both global problems requiring coordinated action. Can existing governance structures (WHO, OIE, UNEP) provide adequate coordination, or are new institutions needed?What This Means for Your Research
For veterinary and public health researchers, the AMR-climate nexus represents a research frontier where two global crises interact in ways that are just beginning to be understood.
For policymakers, the One Health integration gap—between policy endorsement and operational surveillance—is the most actionable finding. Investment in cross-domain surveillance infrastructure is needed now, not after the next pandemic.
Explore related work through ORAA ResearchBrain.
References (4)
[1] Alhassan, M.Y. (2026). Veterinary antimicrobial resistance as a climate-sensitive emerging infectious disease: a paradigm shift in one health surveillance. Veterinary Research Communications.
[2] Alhassan, M.Y., Muhammad, N., & Ahmad, A.A. (2025). Climate change and antimicrobial resistance in foodborne bacteria: a one health perspective for LMICs. Animal Diseases.
[3] Ye, Z., Li, M., & Jing, Y. (2025). What Are the Drivers Triggering Antimicrobial Resistance Emergence and Spread? Antibiotics, 14(6), 543.
[4] Msemakweli, J.G., Mzuka, K., & Osward, A. (2024). One Health Approach to Antimicrobial Resistance: Integrating Human, Animal, and Environmental Perspectives. Journal of Primary Health Care and General Practice.