Strengthening Global AMR Surveillance Networks
Systematic collection and statistical analysis of antimicrobial susceptibility test (AST) data enable public health agencies to track emerging resistance clusters, monitor hospital-acquired infections, and formulate regional antibiotic stewardship policies.
Core Analytics Infrastructure
Using standardized data formats (WHO GLASS, WHONET), data analytics pipelines process MIC (Minimum Inhibitory Concentration) values and disc diffusion diameters to identify high-priority multidrug-resistant pathogens (ESKAPE bacteria).
📊 Public Health AMR Data Science
Master epidemiological surveillance models, AST data analytics, and resistance monitoring tools.
Frequently Asked Questions
How does machine learning improve AMR surveillance?
ML algorithms identify subtle multi-drug resistance pattern shifts early, predicting outbreak risks before conventional surveillance thresholds are triggered.