National Antimicrobial Resistance Monitoring System Isolate Level Data

**Overview**
This data package contains data that comprises the testing on NARMS animal isolates from diagnostic and food-producing farm animals and human isolates to find out how antibiotic resistance has changed over the past 20 years for four bacteria transmitted commonly through food—Campylobacter, E. coli O157, Salmonella, and Shigella. It also contains data on Antimicrobial Use and Resistance Eligible Antimicrobial Agents.

**Description**
In an effort to prospectively monitor the occurrence of antimicrobial resistance of zoonotic pathogens from human diagnostic specimens, retail meats and food animals, the National Antimicrobial Resistance Monitoring System (NARMS) was established in 1996 by the Food and Drug Administration’s Center for Veterinary Medicine in collaboration with the Center for Disease Control and Prevention (CDC), and the United States Department of Agriculture (USDA). The animal component of NARMS is housed within the Bacterial Epidemiology and Antimicrobial Resistance Research Unit (BEAR) of the Agricultural Research Service (ARS) in Athens, Georgia. The animal component of NARMS comprises the testing of isolates obtained from diagnostic animal specimens, healthy on-farm animals, and food-producing animals at slaughter. NARMS also tracks changes in the antimicrobial susceptibility of certain enteric (intestinal) bacteria found in ill people (CDC), retail meats (FDA), and food animals (USDA) in the United States. The NARMS program at CDC helps protect public health by providing information about emerging bacterial resistance, the ways in which resistance is spread, and how resistant infections differ from susceptible infections. NARMS monitors antibiotic resistance among the following four major foodborne bacteria: Salmonella, Campylobacter, Escherichia coli and Enterococcus.

**Benefits**
- monitor trends in antimicrobial resistance among foodborne bacteria from humans, retail meats, and animals
- disseminate timely information on antimicrobial resistance to promote interventions that reduce resistance among foodborne bacteria
- conduct research to better understand the emergence, persistence, and spread of antimicrobial resistance
- assist the fda in making decisions related to the approval of safe and effective antimicrobial drugs for animals

**License Information**
The use of John Snow Labs datasets is free for personal and research purposes. For commercial use please subscribe to the [Data Library](https://www.johnsnowlabs.com/marketplace/) on John Snow Labs website. The subscription will allow you to use all John Snow Labs datasets and data packages for commercial purposes.

**Included Datasets**
- [Antimicrobial Use and Resistance Eligible Antimicrobial Agents](https://www.johnsnowlabs.com/marketplace/antimicrobial-use-and-resistance-eligible-antimicrobial-agents)
- The National Healthcare Safety Network (NHSN) Antimicrobial Use and Resistance (AUR) provides a mechanism for facilities to report and analyze antimicrobial use and/or resistance as part of local or regional efforts to reduce antimicrobial resistant infections through antimicrobial stewardship efforts or interruption of transmission of resistant pathogens at their facility.
- [NARMS Food Animal Isolate Data](https://www.johnsnowlabs.com/marketplace/narms-food-animal-isolate-data)
- The National Antimicrobial Resistance Monitoring System (NARMS) Animal Isolates provides data that comprises the testing of isolates obtained from diagnostic animal specimens, healthy on-farm animals, and food-producing animals at slaughter. These tests on retail samples were performed by FDA.
- [NARMS Human Isolate Data](https://www.johnsnowlabs.com/marketplace/narms-human-isolate-data)
- The National Antimicrobial Resistance Monitoring System (NARMS) Human Isolate Data makes it easier and quicker to find out how antibiotic resistance has changed over the past 20 years for four bacteria transmitted commonly through food—Campylobacter, E. coli O157, Salmonella, and Shigella.

**Data Engineering Overview**
**We deliver high-quality data**
- Each dataset goes through 3 levels of quality review
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