
I study hospital outbreaks using pathogen genomics and machine learning of electronic health record data
Bio
Dr. Alexander Sundermann is an Assistant Professor at the University of Pittsburgh, Division of Infectious Diseases, Center for Genomic Epidemiology. His work focuses on the research and application of whole genome sequencing surveillance for outbreak detection and investigation in healthcare settings. Dr. Sundermann’s research also utilizes the electronic health record data and machine learning to detect routes of transmission faster and more accurately within outbreaks. More recently, he and the Center for Genomic Epidemiology implemented a real-time whole genome sequencing surveillance program at their hospital which sequences potentially healthcare-associated bacterial infections every week to monitor for transmission, outbreaks, and direct interventions.
Dr. Sundermann previously worked as a Senior Infection Preventionist at the University of Pittsburgh Medical Center where he led investigations into multiple outbreaks and directed patient safety and quality improvement initiatives. He is a Fellow of the Association for Professionals in Infection Control and Epidemiology and board certified in infection control by the Certification Board of Infection Control and Epidemiology.
( 01 )
Education
March 2022
Doctor of Public Health
Epidemiology
University of Pittsburgh
Dissertation title: “Novel Approaches for Healthcare Outbreak Detection and Investigation"
December 2014
Master of Public Health
Infectious Diseases and Microbiology
University of Pittsburgh
Thesis title: “Development of Protocol for Reduction in Central Line Associated Blood Stream Infections”
May 2013
Bachelor of Science
Microbiology
University of Rochester
( 02 )
Experience
July 2022 - Present
Assistant Professor of Infectious Diseases, University of Pittsburgh
Further developing the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT) for hospital outbreak detection and investigation
August 2020 - June 2022
Epidemiologist, University of Pittsburgh
Leading research into the development of Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT) which combines whole genome sequencing surveillance and machine learning of the electronic health record for healthcare outbreak detection and investigation
November 2019 - July 2020
Epidemiologist, Cardno ChemRisk
Provided epidemiological support and analysis in literature review, health policy, microbial assessments, data analysis, data management, and litigation
December 2014 - November 2019
Senior Infection Preventionist, UPMC
Provided surveillance and epidemiological insight and implement interventions to reduce healthcare-associated infections
( 03 )
Recent Publications
June 2022
Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary
November 2021
Whole Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection
April 2022
Remediation of Mucorales-contaminated Healthcare Linens at a Laundry Facility Following an Investigation of a Case Cluster of Hospital-acquired Mucormycosis
( 04 )
Recent Media
The Conversation, Jan 2022
From delta to omicron, here’s how scientists know which coronavirus variants are circulating in the US
Pittsburgh Post Gazette, Nov 2021
Artificial intelligence system may help fight spread of infections in hospitals, new Pitt and CMU study reports
Wall Street Journal, Nov 2021
Pittsburgh Hospital Taps AI to Prevent Spread of Infections
The Conversation, Mar 2021