In the US, the National Antimicrobial Resistance Monitoring System has been using WGS of Salmonella as a tool of routine surveillance since 2013. To date, NARMS has generated MIC and WGS data on over 10,000 Salmonella isolates from food animals, 9,000 from human clinical cases, 6,000 from retail meats, and 1,4OO from imported foods. Analysis of this dataset showed that the presence of known resistance determinants is very highly correlated with clinical resistance, indicating that WGS data can be used to predict resistance in Salmonella strains lacking traditional antimicrobial susceptibility data. To make these data accessible, the NARMS program has launched Resistome Tracker and other online tools that provide visually informative displays of antibiotic resistance genes. Resistome Tracker harvests resistance gene information on a weekly basis from genomic data deposited at NCBI. It presents the resistome data using interactive dashboards that allows users to customize visualizations by antibiotic drug class, compare resistance genes across different sources, identify new resistance genes, and map selected resistance genes to geographic region. The tool also provides alerts about new resistance traits as they emerge in a region or source to provide early warning on emergent trends. 

Learning Objectives: 

1. The technical aspects of integrated antimicrobial resistance monitoring 
2. The utility of whole genome sequence data in resistance surveillance
3. Visualization and reporting tools to foster global data sharing