Surveillance of antimicrobial resistance in veterinary medicine in the United States: current efforts, challenges, and opportunities

Ruzante JM, Harris B, Plummer P, et al

Published online 20 Dec 2022

Access via Frontiers in Veterinary Science

 

 

 

Publication Summary

Increasing numbers of infections in animals associated with resistant bacteria pose a challenge for veterinarians in the United States (US) and around the world. Efforts to effectively address antimicrobial resistance (AMR) using a One Health approach require AMR surveillance and antimicrobial stewardship (AMS). In the US, platforms exist to collect, analyze, and disseminate AMR data in human health care settings that enable the development of effective infection control and AMS methods. However, equivalent tools do not yet exist in veterinary medicine. This review article presents existing efforts in the US, as well as challenges and opportunities, related to surveillance of AMR in veterinary medicine.

Who this is for

  • Veterinarians
  • Veterinary diagnostic laboratories
  • Individuals, organizations, and agencies working to improve veterinary AMR surveillance

Key findings

Current Efforts: While acknowledging that additional efforts exist, this paper provides details regarding the following programs that collect AMR data from animals in the US:   

  • The National Antimicrobial Resistance Monitoring System (NARMS) monitors AMR among select commensal bacteria (Escherichia coli and Enterococcus) and select pathogens (Campylobacter, Salmonella, E. coli O157) isolated from human patients, retail meats, cecal contents, and meat/poultry products collected at inspected slaughter and processing facilities.
  • The National Center for Biotechnology Information (NCBI) database holds information about isolates sequenced by NARMS, including whole genome sequences (WGS) and selected metadata.
  • The Resistome Tracker is a global tool developed by NARMS that allows users to explore current data about a wide range of bacteria submitted to the NCBI.
  • The National Database of Antibiotic Resistant Organisms (NDARO) is a cross-agency centralized database curated by the NCBI that allows real-time surveillance of pathogenic organisms. Data submissions come from across the US and around the world with the majority of the data coming from human isolates.
  • The Veterinary Laboratory Investigation and Response Network (Vet-LIRN) is a collaboration between the US Food and Drug Administration (FDA) and veterinary diagnostic laboratories (VDLs) that was tasked to develop, expand, and maintain antimicrobial susceptibility testing and WGS testing of selected veterinary pathogens (E. coli and Staphylococcus pseudintermedius from dogs, and Salmonella enterica from any animal species) isolated at VDLs.
  • The National Animal Health Laboratory Network (NAHLN) was created by the US Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS). The project collects and aggregates AMR profiles for select pathogens from livestock and companion animals that are clinically ill. Data from companion animals are combined with Vet-LIRN data and reported jointly through the FDA's NARMS website.
  • The National Animal Health Monitoring System (NAHMS) is administered by USDA APHIS and performs national studies on health and management practices of domestic livestock populations on a rotating schedule. Participation by producers is voluntary and biological samples vary depending on specific studies. Recent reports have included some information about AMS and antimicrobial susceptibility testing.

Challenges: The authors note several challenges that remain for existing programs to provide effective AMR surveillance in veterinary medicine, including:

  • Currently available programs remain heavily focused on zoonotic pathogens and are limited to few organisms of animal health relevance.
  • Current programs may not include phenotype data or may only use human breakpoints to interpret minimum inhibitory concentrations (MICs) to determine resistance making clinical interpretation difficult since human clinical breakpoints often differ substantially from those in animal species
  • Available data are often aggregated at the national or state level and data availability is often delayed by several years.
  • Veterinary medicine has few mechanisms to incentivize generating or sharing data.

Opportunities and Recommendations: The authors highlight the specific opportunity that exists to use VDL data to build a centralized surveillance system in the US. While many challenges remain for building such a system, which are detailed in the full paper, the authors argue that VDLs provide a rich source of data for AMR surveillance in diseased animals and that a centralized system could allow for (i) developing cumulative susceptibility information to guide prescribing practices, (ii) monitoring resistance trends, (iii) detecting emerging diseases, and (iv) potentially improving clinical decision making [i.e., generation of new breakpoints and epidemiological cut-off values (ECVs or ECOFFs) for veterinary medicine]. Some specific recommendations toward this goal include:

  • Nomenclature and ontology must be more widely standardized across laboratories.
  • VDLs need to provide raw antimicrobial susceptibility testing data such as MICs or zone diameters to surveillance programs rather than interpretations (such as susceptible, intermediate, or resistant).
  • A robust information technology (IT) infrastructure needs to be developed that can handle high volumes of data in a continuous manner and remove the burden from VDLs by accepting multiple formats.
  • Models for data security and confidentiality should be explored and adapted to protect sensitive information, such as personal identifiable information, in AMR data from animal sources.
  • Models for improving the collection of antimicrobial use data in VDL submission processes should be explored.

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