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Measure  –  Antibiotic resistance

Antibiotic resistance in animals

Here you find guidance, methods and tools to generate data on antibiotic resistance in animal settings.

Data on antibiotic resistance in animal settings can be generated on a small or large scale. Conducting point prevalence surveys is a good way to get started and can be a useful tool to quickly assess the current situation. Over time efforts can be scaled up and eventually act as inputs to national surveillance.

Surveillance in the animal sector

In the animal sector, three categories of bacteria usually are included in surveillance programs: zoonotic bacteria, indicator bacteria, and animal pathogens. Zoonotic bacteria are included because they can develop resistance in the animal reservoir and may also transfer to and cause infections in man. Indicator bacteria are isolated from healthy individuals and give a more accurate value of the occurrence of resistance in the entire animal population. Pathogenic isolates from clinical sampling are usually not representative for the true occurrence of resistance, but are important for detecting emerging resistance.

In the EU and USA, surveillance covers zoonotic bacteria (Salmonella spp, Campylobacter jejuni and Campylobacter coli) and indicator bacteria (commensal E. coli, Enterococcus faecalis and Enterococcus faecium) isolated from healthy animals and food.

Pathogenic bacteria from clinical cases are at present included in some national surveillance programs, for example in Sweden. For many of these samples it is likely that they are from animals treated with antibiotics, which has to be taken into account when analyzing such data. However, there is a need for harmonized monitoring of data for certain types of resistance in certain animal pathogens to be able to detect emerging resistance that might lead to severe therapy failure. An example is pleuromutilin resistance in Brachyspira hyodysenteriae , the bacterium that causes swine dysentery (see grey box).

The burden of antibiotic resistance – swine dysentery

Swine dysentery is an enteric disease of pigs caused by Brachyspira hyodysenteriae. Clinical manifestation can range from mild colitis to severe hemorrhagic colitis with a mortality rate reaching 50-90%. Even though the disease is distributed worldwide, only a few epidemiological studies have been done, showing a prevalence ranging from 0 to near 40%.

At present only few treatment options remain for clinical outbreaks of swine dysentery. Resistance to macrolides and lincosamides is common, and the number of effective antibiotics is limited. In the EU, pleuromutilins are the only potentially effective choice. In the USA carbadox is used, but FDA has recently started a process towards rescinding its approval to treat swine as there may be a potential carcinogenic risk when ingesting pork derived from carbadox-treated pigs.

During the last decade, the occurrence of pleuromutilin resistance among B. hyodysenteriae has increased. In a recent study from Italy, more than 50% of the isolates were resistant. As swine dysentery causes impaired growth, mortality and secondary costs, lack of effective treatment options would have high costs for the production economy.

Eradication programs have successfully been applied in some EU countries, and the European Medicines Agency (EMA) has stressed that such programs are crucial to reduce the need for pleuromutilins. Also, harmonized monitoring for pleuromutilin resistance in B. hyodysenteriae has been proposed.

A protocol for elimination of swine dysentery from single-site, farrow-to-finish herd has been described, and prolonged follow up indicates that B. hyodysenteriae has been successfully eradicated. Eradication from farms has resulted both in higher productivity and decreased use of antibiotics. In addition, eradication programs on national level have decreased both total use of tiamulin and prevalence of pleuromutilin-resistant strains of B. hyodysenteriae.

Data on antibiotic resistance in animal settings: Sampling sites and types

As the main part of samples in animal surveillance systems is derived from healthy animals, veterinary clinics are not a dominating sampling site. Instead, fecal samples at farm level or samples from caecal content taken at the slaughterhouse dominate. Also, as samples are taken from animal-derived food, sampling sites includes retail foods. When starting up a surveillance program in the animal sector, it is recommended to start sampling retail food, and progressively expand the sampling to food producing animals.

Slaughterhouses are usually the most cost-efficient sampling sites for animal samples, even though the caecal microbiota of the animal may change during transportation and in holding pens at the slaughterhouse. Examples of what to consider when taking samples throughout the food chain is presented in figure 1.

The selection of which food and which animal species to sample from should reflect consumption patterns in the studied region. The database of the Food and Agriculture Organization of the United Nations (FAO) summarizes consumption data for different countries and is a useful source of information for this purpose.

Sample sites should be connected to a laboratory facility, either on site or if samples can be stored and transported properly, to a central laboratory. The laboratory should at least have the capacity to isolate and identify target bacteria and perform antibacterial susceptibility testing using validated methods according to established standards.

Flow chart of considerations for sampling through the food chain. Adapted from WHO/AGISAR, 2013 as explained in the text
Figure 1. Considerations for sampling through the food chain. Adapted from WHO/AGISAR, 2013.

Data on antibiotic resistance in animal settings: Data management

To be able to contribute to national and international surveillance, retrieved data should be entered into a data management software. WHONET fulfils the demands for surveillance and is available free of charge. It is already used in hospital, public health, veterinary and food laboratories in over 110 countries and is available in over 20 languages. WHONET includes a feature for exporting resistance statistics into the format required for producing local and national reports and for uploading to the WHO Global Antimicrobial Resistance Surveillance System (GLASS) web interface. At present (2018) GLASS only includes human surveillance, but it will be extended to the food chain in the coming years.

Resources below have been divided into the following tables:

  • Tools and guidelines
  • Data and reports

Selected Resources

Tools and guidelines

Resource Description
Manual of Diagnostic Tests and Vaccines for Terrestrial Animals This OIE manual provides standards, guidelines and recommendations for diagnosis and identification of important diseases and causative organisms in terrestrial animals. Guideline 3.1: Laboratory methodologies for bacterial antimicrobial susceptibility testing (PDF) explains how antimicrobial susceptibility tests should be performed.
WHONET Software A database software for the management and analysis of antibiotic resistance data. The system is free to download and use, developed by WHO.
OIE Terrestrial Animal Health Code Chapter 6.8: Harmonisation of National Antimicrobial Resistance Surveillance and Monitoring Programmes, provides criteria for development and harmonization of national resistance surveillance and monitoring programs in food-producing animals and in products of animal origin intended for human consumption.
OIE Aquatic Animal Health Code OIE guide to development and harmonisation of national antimicrobial resistance surveillance and monitoring programmes for aquatic animals. Chapter 6.3: Monitoring of the quantities and usage patterns of antimicrobial agents used in aquatic animals. Chapter 6.4: Development and Harmonisation of National Antimicrobial Resistance Surveillance and Monitoring Programmes for Aquatic Animals.
CODEX ALIMENTARIUS: Codex Texts on Foodborne Antimicrobial Resistance (PDF 3,2MB) Document part of the CODEX ALIMENTARIUS international food standards, guidelines and codes of practice for international food trade. Compiles the 2 Codex guidelines “Code of Practice to Minimize and Contain Antimicrobial Resistance” (ref no: CAC/RCP 61-2005) and “Guidelines for risk analysis of foodborne antimicrobial resistance”. It provides guidance for the responsible and prudent use of antimicrobials in food-producing animals and for assessing risk to human health from foodborne antibiotic resistant bacteria as well as determining appropriate management strategies to control those risks. English, French and Spanish versions included.

Data and reports

Resource Description
Review of Evidence on Antimicrobial Resistance and Animal Agriculture in Developing Countries This review provides available evidence on resistance in agri- and aquaculture in LMICs, highlighting the scarcity of most data and providing an overview of the gaps in knowledge.
ECDC/EFSA/EMA joint reports on the integrated analysis of the consumption of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from humans and food-producing animals (JIACRA reports) Using existing data from five EU-wide monitoring networks, ECDC/EFSA/EMA analyze the relationship between antimicrobial consumption and resistance to the same antimicrobials in bacteria from humans and food-producing animals, and highlights knowledge gaps. One Health approach.
The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2015 This summary report gives an overview of antimicrobial resistance data in zoonotic Salmonella and Campylobacter species from humans, animals and food, and resistance in indicator Escherichia coli as well as methicillin-resistant Staphylococcus aureus in animals and food from 28 European Union Member States.
Country-specific reports: CanadaDenmark; the Netherlands; Sweden; UK Examples of country-specific reports based on surveillance data on antibiotic resistance in zoonotic and indicator bacteria from animals and food. In some cases integrated with data from humans. Click on the country to access the reports.

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