Gustav Torisson

Gustav Torisson serves as Associate Professor and Postdoctoral Fellow at Lund University's Faculty of Medicine within the Clinical Infection Medicine department. He maintains additional research appointments at Cognitive Disorders and MultiPark (Multidisciplinary research focused on Parkinson's disease), along with project coordination and affiliated researcher roles at Infect@LU. His ORCID profile (0000-0001-9012-2068) documents extensive contributions to infectious disease research.

His research focuses on critical infectious disease challenges including bloodstream infections, antimicrobial resistance mechanisms, sepsis management, and community-acquired pneumonia epidemiology. Specialized work examines antibiotic dosing optimization for Gram-negative pathogens, time-to-positivity diagnostics in bacteremia, and neurological infection comorbidities in Parkinson's disease through the MultiPark consortium. His fingerprint analysis reveals significant contributions to patient outcomes research, atrophy studies, and primary healthcare infection management.

Current research trends demonstrate strong emphasis on population-based cohort studies and antimicrobial stewardship, with recent publications exploring norepinephrine administration techniques in shock management and radiological verification standards for pneumonia hospitalization. His work directly contributes to UN Sustainable Development Goals related to health and wellbeing.

Torisson actively supervises research students with 4 supervised works documented. He leads two major projects: 'Improved treatment of serious infections in an aging population' (funded by Maggie Stephens stiftelse, 2024-2026) and 'Antimicrobial resistance and sepsis' (ongoing dissertation project since 2022) involving collaborators including Riesbeck, Sunnerhagen, and Sjövall.

His research operates within Lund University's Infect@LU network and MultiPark consortium, leveraging clinical data from southern Sweden's healthcare systems. Current work focuses on optimizing antibiotic therapy through pharmacokinetic modeling and validating diagnostic criteria for severe infections in aging populations.