Johns Hopkins University Prevention Epicenter

Key points

  • First funded in 1997.
  • Develops strategies to improve the safety of patients and healthcare workers by preventing transmission of germs and improving antibiotic use.
  • Conducts research to identify novel approaches to prevent healthcare-associated infections and antimicrobial resistance.

Overview

The Johns Hopkins University Prevention Epicenter's studies address knowledge gaps and develop strategies to improve the safety of patients and healthcare workers by preventing transmission of germs and improving antibiotic use in diverse healthcare settings and patient populations.

Epicenter research translates basic, epidemiologic and technologic discoveries into new strategies to prevent healthcare-associated infections (HAIs) and antimicrobial resistance (AR) and to improve how antibiotics and diagnostic tests are used across all healthcare settings. These studies demonstrate the Epicenter's capacity to integrate expertise in healthcare epidemiology and antibiotic stewardship with other disciplines, including human factors engineering, data science, machine learning, microbiology, mathematical modeling, microbiome science and implementation science.

The Epicenter includes a multi-disciplinary collaborative team of researchers and faculty from the Johns Hopkins University School of Medicine, the Johns Hopkins Bloomberg School of Public Health, the Johns Hopkins Hospital Department of Hospital Epidemiology and Infection Control, and the Johns Hopkins Hospital Department of Antimicrobial Stewardship.

The research team has expertise in:

  • Infection prevention surveillance.
  • Implementation science.
  • Antimicrobial stewardship in acute, ambulatory and long-term care settings.
  • Healthcare epidemiology in acute, ambulatory and long-term care settings.
  • Human factors engineering.
  • Emergency preparedness.
  • Biopreparedness.
  • Data science.
  • Behavioral economics.
  • Pediatrics.
  • Microbiology.
  • Environmental microbiology.
  • Mathematical modeling.
  • Machine learning.
  • Microbiome statistics.
  • Biostatistics.

Core research study areas

Multicenter collaborative research projects

Principal investigators

Clare Rock, MD, MS and Sara E. Cosgrove, MD, MS