AMR Monitoring in Livestock Poultry Aquaculture
Monitoring Antimicrobial Resistance Across the Livestock, Poultry, and Aquaculture Chain
When an antibiotic is used on a livestock farm, poultry operation, or fish farm, its impact does not remain limited to that herd, flock, or treatment period. Part of the drug’s effect appears in animal health, part in food safety, and part remains in the environment through which feed, water, manure, wastewater, and animal-derived products move. In such a chain, antimicrobial resistance means that bacteria gain the ability to survive against drugs that are supposed to control them, placing treatment decisions, consumer health, and market trust under pressure at the same time.
The importance of this issue for the livestock, poultry, and aquaculture chain begins with the fact that food is not the product of a simple linear path. Animals, feed, the production environment, slaughterhouses, processing, cold-chain transport, retail, and consumers are all part of a connected system, and each link can generate data on antimicrobial use or bacterial resistance. If these data are viewed in isolation, decision-makers see only part of the picture. But when the data are brought together within a One Health framework, the relationships among human, animal, food, plant, and environmental health become traceable.
For agricultural economics and food security, AMR monitoring is not merely a laboratory tool; it is a form of governance infrastructure for the value chain. This infrastructure shows which species, production phases, active substances, and routes of administration require tighter control. In the aquaculture chain, the issue is even more significant because medicated feed, production density, and direct contact with the aquatic environment can transfer selective pressure from the farm level to the surrounding environment.
Why Has Antimicrobial Resistance Monitoring Become a Food Security Issue?
FAO describes antimicrobial resistance as a threat to humans, animals, plants, and the environment, and this broad scope shows that the issue goes far beyond treating an animal disease. When drug efficacy declines, treating animal diseases becomes more expensive, slower, and riskier, and this can affect the sustainable production of animal protein. At the consumer level, food safety is not measured only by controlling drug residues, because the pattern of bacterial resistance in the food chain is itself an independent and monitorable risk.
– Dr. Tedros Adhanom Ghebreyesus, Director-General of the World Health Organization: “Antimicrobial resistance threatens to reverse this progress and is one of the most important health challenges of our time.”
The United Nations high-level political declaration in 2024 introduced a meaningful reduction in antimicrobial use in agrifood systems by 2030 as a global commitment. The declaration’s emphasis on prevention, infection control, and responsible use sends a clear message to the livestock, poultry, and aquaculture chain. The main goal is not simply to reduce drug use, but to reduce the need for drug use through disease management, improved biosecurity, vaccination, feed quality, water quality, and evidence-based decision-making.
In its 2025 report, WOAH showed that the amount of antimicrobials used or sold for animals, measured in milligrams per kilogram of animal biomass, fell from 102 in 2020 to 97 in 2022. This global reduction of about 5 percent is important, but it is not sufficient on its own to assess the quality of AMR control. Consumption figures become meaningful when they are accompanied by sampling data, bacterial species, animal species, active substance, and production location.
– Monique Eloit, Director General of the World Organisation for Animal Health: “Antimicrobial resistance threatens animal health, food safety, and food security.”
How Does One Health Connect Data on Livestock, Poultry, Aquaculture, Food, and the Environment?
In the One Health approach, AMR monitoring does not mean collecting a few scattered tables from laboratories. This approach connects data from humans, animals, food, plants, and the environment so that the source of risk, transmission pathway, and intervention point become clearer. In the livestock and poultry chain, this connection extends from farms and slaughterhouses to processing and retail. In aquaculture, data from the aquatic environment and production phase also become directly important.
– Institutional statement by the Food and Agriculture Organization of the United Nations: “Antimicrobial resistance is a major threat to humans, animals, plants, and the environment.”
Codex guideline CAC/GL 94-2021 presents integrated monitoring and surveillance of foodborne AMR as a framework to support risk management. The strength of this framework is that it does not separate the laboratory from food policy; instead, it places sampling, susceptibility testing, trend analysis, and policy feedback along a single pathway. In this model, laboratory data gain policy value when they lead to decisions about responsible use, food safety, and supply-chain control.
Chapter 6.8 of the WOAH Terrestrial Animal Health Code and Chapter 6.4 of the WOAH Aquatic Animal Health Code are two important regulatory foundations for designing national programs. Their importance lies in the fact that they view livestock, poultry, and aquatic animals through a shared logic but with different implementation designs. A program written for poultry or cattle is not sufficient for aquaculture unless it distinguishes species, production phase, and route of administration, and this difference must be reflected in the monitoring architecture.
How Do Antimicrobial Use Indicators Make Reduction Policies Measurable?
The European Union uses the mg/PCU indicator to adjust antimicrobial sales according to animal biomass. For the 2023 data year, sales of veterinary antimicrobials within the EU’s mandatory scope were reported at 4,380.8 tons of active substance, with an aggregated sales indicator of 88.5 mg/PCU. The EU’s 2030 target is to reach 59.2 mg/PCU compared with the 2018 baseline of 118.3 mg/PCU, showing that monitoring consumption without a comparable indicator remains a weak policy tool.
The United States presents another version of the same logic. The FDA’s report for the 2023 data year announced that sales and distribution of medically important antimicrobials for food-producing animals totaled 6,127,991 kilograms of active substance. This amount was about 2 percent lower than in 2022 and about 37 percent lower than the 2015 peak. However, national sales data alone cannot show on which farm, for which disease, and under what prescribing pattern the drug was used.
The United Kingdom publishes sales, use, and resistance data within a single framework through UK-VARSS, and this combination has significant value for policymaking. In the 2023 data year, sales of veterinary antibiotics for food-producing animals were reported at 25.7 mg/kg, unchanged from 2022 and 59 percent lower than in 2014. Sales of critically important antimicrobials for human medicine were also reported at 0.11 mg/kg, accounting for less than 0.5 percent of total sales.
The Netherlands shows that long-term reductions in use do not always mean a linear decline every year. The SDa report for the 2023 data year recorded an increase of about 4.5 percent in total sales of antibiotics for livestock compared with 2022, but sales remained 76.4 percent lower than the 2009 reference year. This experience is important for policymaking because a monitoring program must be able to detect annual fluctuations while also distinguishing long-term trends from short-term ups and downs.
What Are the Components of Laboratory AMR Monitoring Standards in Livestock, Poultry, and Aquaculture?
– Sampling from Farm to Retail
A credible monitoring program must begin with clearly defined sampling points. Codex highlights points such as farms, slaughterhouses, processing facilities, and retail for foodborne AMR, and when a program is designed, feed and the environment can also be added to the monitoring scope. Choosing a sampling point is not merely a technical decision, because it determines whether the final data can be used for production control, food safety, market management, or drug-use policy.
In mature programs, target bacteria usually include Salmonella, Campylobacter, indicator E. coli, and Enterococcus. Canada’s CIPARS experience shows that monitoring humans, healthy animals on sentinel farms, sick animals, healthy animals at slaughterhouses, and retail meat together makes One Health analysis operational. This type of design helps policymakers more accurately distinguish among food contamination, resistance in indicator bacteria, and drug-use pressure at the farm level.
– Susceptibility Testing and Differentiation of Target Bacteria
Antimicrobial susceptibility testing, or AST, is reliable for decision-making only when it is performed using standardized methods, quality control, and laboratory interpretability. WOAH’s reference to Chapter 2.1.1 of the Manual shows that laboratory methodology is part of the backbone of AMR monitoring, not a secondary step after sampling. If laboratories use inconsistent methods, data cannot be aggregated and compared at the national level, and policy feedback becomes weak.
Monitoring antibiotic residues and monitoring AMR are two different issues, although both are important for market trust and food safety. Residue monitoring is mainly concerned with residues and the maximum permitted level of drug residue in a product, while AMR monitoring focuses on bacterial resistance patterns and selective pressure in the production chain. Iran’s National Action Plan also presents these two pathways separately, and this distinction is essential for designing laboratory and digital systems.
What Warning Does Chile’s Aquaculture Experience Hold for the Blue Economy?
Aquaculture requires a separate monitoring design because of its direct contact with the aquatic environment. In Chile, the salmon industry used 338.9 tons of antimicrobials in the 2023 data year, while harvested salmonid production reached 1,107,109 tons. The ICA indicator in the same report was stated as 0.031 percent, based on the ratio of tons of active substance used to tons of harvested production, multiplied by 100.
Details from the same report show that aquaculture analysis can be misleading without separation by production phase. In 2023, 98.22 percent of antimicrobial use was reported in the seawater phase and only 1.78 percent in freshwater. In the marine phase, 95.46 percent of the active substance used was florfenicol and 3.80 percent was oxytetracycline. Therefore, the name of the active substance and the site of use are directly important for analyzing selective pressure.
The reason for treatment is also a key variable in aquaculture. In Chile’s marine phase, 93.21 percent of use in 2023 was reported for piscirickettsiosis, and 99.34 percent of marine-phase treatments were administered orally. The oral route is especially important because uneaten feed and excretion can transfer part of the drug pressure to the aquatic environment, linking AMR monitoring to disease management, vaccination, and feed quality.
– Soledad Tapia Almonacid, National Director of Chile’s National Fisheries and Aquaculture Service: “This measure sets new standards in aquaculture and strengthens active citizen participation.”
What Lessons Do Global AMR Monitoring Models Offer Iran’s Animal Production Chain?
Canada’s CIPARS shows that AMR monitoring becomes mature when humans, animals, and food are viewed within a single system. This program tracks trends in antimicrobial use and resistance in selected bacteria from humans, animals, and food sources, placing retail meat data alongside farm, slaughterhouse, and human health data. For Iran, the main value of this experience is not the transfer of Canadian figures, but learning the architecture of the sampling network and how multi-sectoral data are connected.
Japan’s JVARM provides an important example of monitoring both healthy and sick livestock. The data show that in E. coli isolated from healthy livestock, tetracycline resistance in 2021 was 40.7 percent, resistance to third-generation cephalosporins was 1.4 percent, and fluoroquinolone resistance was 5.5 percent. This pattern is a reminder that low resistance to drugs that are critically important for human medicine does not necessarily mean low resistance to older drugs.
In the Dutch model, farm veterinarians and livestock owners submit use data to sectoral databases, and SDa receives anonymized annual use data for sectors such as veal calves, cattle, pigs, poultry, goats, and rabbits. The importance of this model lies in its combination of professional responsibility, data confidentiality, and sectoral benchmarking. If consumption data remain only at the level of national sales, the ability to analyze performance by species, farm, or production chain becomes limited.
Global case studies carry one shared message: drug sales, actual use, and bacterial resistance are three different layers. EMA, WOAH, and FDA each cover part of this data chain, but accurate decision-making emerges when sales data are connected to prescriptions, species, diseases, sampling, and laboratory testing. For countries seeking to upgrade their livestock, poultry, and aquaculture chains, this data connection is as important as the laboratory itself.
Iran’s Implementation Path for AMR Monitoring Through Data Governance and Credible Laboratories
For Iran, the defensible starting point is not the rushed announcement of a national figure, but the construction of a phased and trustworthy monitoring architecture. Iran’s National Action Plan against AMR identifies monitoring in livestock, aquaculture, and companion animals, as well as connecting human, animal, and food data, as necessary actions. This framework can serve as the basis for designing a system that begins with several priority chains and then expands as laboratory and digital capacity increase.
In this process, poultry, livestock, and aquaculture must be designed separately. Using a single indicator for all sectors, without distinguishing species, production phase, active substance, disease, and route of administration, is scientifically weak. Chile’s data on the difference between freshwater and seawater, JVARM’s data on differences among drug classes, and CIPARS’ experience in differentiating sample sources all show that monitoring design must align with production biology and supply-chain logic.
A credible laboratory infrastructure must be accompanied by a laboratory information management system, sample coding, quality control, cold-chain management, and a clear definition of data ownership. In such a design, LIMS is not merely software for recording results; it is a tool for connecting the sample, farm, species, bacterium, active substance, test method, and policy report. Without this connection, laboratories produce data, but the national network loses the ability to analyze trends, compare regions, and provide feedback to veterinarians and producers.
The role of the private sector is defensible when it serves data quality and risk reduction across the chain. Accredited private reference laboratories, sampling services, cold-chain transport, farm audits, supply-chain monitoring, and quality assurance services can work alongside regulators, provided that farm confidentiality, data ownership, and reporting standards are clearly defined. For investors, the value of this field is not limited to selling individual tests; it lies in building trust infrastructure for food, exports, modern retail, and production risk management.
A Practical Conclusion for Investment in Food Security and the Animal Production Chain
Monitoring antimicrobial resistance across the livestock, poultry, and aquaculture chain is the point where laboratories, veterinary medicine, food safety, the blue economy, and data governance intersect. The experience of the European Union, the United Kingdom, the United States, the Netherlands, Canada, Japan, and Chile shows that use indicators are valuable when interpreted alongside sampling and resistance data. For Iran, the implementation path should begin with priority chains, coordinated laboratories, aggregable data, and a precise distinction between drug residues and bacterial resistance.
Future decision-making in this field must move away from a purely therapeutic perspective and treat AMR as a structural risk in the food chain. Responsible reduction of use, stronger biosecurity, improved feed and water quality, vaccination, disease monitoring, and AST standardization are parts of a shared pathway. Any investment that can connect these components through reliable data, dependable laboratory services, and actionable feedback to producers will help strengthen food security and market trust.
