Antibiotic Resistance Tracking Dataset

The Antibiotic Resistance Tracking Dataset is a comprehensive and structured collection of microbiological and clinical data aimed at monitoring the emergence and spread of antimicrobial resistance (AMR). It compiles laboratory-confirmed bacterial isolates from diverse sample sources—such as blood, urine, sputum, and wound swabs—alongside patient demographics and treatment details. Each entry records the pathogen identified, the antibiotics tested, and the corresponding susceptibility outcomes (sensitive, intermediate, or resistant), using standardized testing methods like MIC and disk diffusion. Additionally, the dataset incorporates temporal and geographical metadata, allowing researchers to analyze resistance trends over time and across regions. Special attention is given to multidrug-resistant organisms (MDROs), including MRSA, CRE, and ESBL-producing bacteria. The dataset also captures contextual variables such as hospital ward, infection type, and prior antibiotic exposure, offering insights into drivers of resistance. By linking clinical outcomes with resistance patterns, the dataset supports predictive modeling and risk assessment. It serves as a vital tool for health authorities, researchers, and policymakers working to curb the global AMR threat through evidence-based interventions and antimicrobial stewardship.

Clinical and Hematological Parameters Included:
Patient_ID: Unique identifier assigned to each patient.
Age: Patient’s age in years.
Gender: Sex of the patient (Male/Female).
Specimen_Type: Type of biological sample tested (e.g., blood, urine, sputum).
Amoxicillin: Resistance result of the bacterial isolate to Amoxicillin (Sensitive/Resistant).
Ciprofloxacin: Resistance result to Ciprofloxacin.
Meropenem: Resistance status to Meropenem, a carbapenem antibiotic.
Vancomycin: Susceptibility result for Vancomycin.
Colistin: Resistance profile to Colistin, often used as a last-resort antibiotic.
Test_Method: Laboratory method used for antibiotic susceptibility testing (e.g., disk diffusion, MIC).
Resistance_Genes: Presence of specific antibiotic resistance genes identified (e.g., blaNDM, mecA).
Outcome: Clinical outcome of the patient (e.g., Recovered, Died, Under Treatment).

Structure of the Dataset:
Format: CSV
Rows: 2,200 (individual patient records)
Columns: 13 (clinical and hematological parameters, including diagnostic result)