Computational Fluid Dynamics (CFD) studies on airborne transmission in hospitals: A review on the research approaches and the challenges

Airborne transmission has always been one of the contributors to healthcare-associated infections (HAIs). Throughout the years, building researchers and medical experts have conducted a lot of studies to identify the effect of hospital ventilation and other associated factors on airborne transmission to provide a better understanding of HAIs and recommend improvement strategies. Despite the efforts, a general agreement on the optimal ventilation scheme and management strategy for hospitals has not been reached. There is an obvious need for interdisciplinary research in the field to address the pressing challenges. In view of that, a systematic review of the current Computational Fluid Dynamics (CFD) research approaches for investigating the airborne transmission in hospitals was conducted. A total of 95 journal articles and conference papers published between the years 2003 and 2021 were reviewed. The objective, location, methodology, validity, and useful findings of each research study were examined. By clustering the studies according to their research focuses, some of the notable studies were highlighted to present the challenges and special considerations of applying CFD on airborne transmission in hospital setting. Recommendations for maintaining and improving hospital ventilation while minimizing airborne transmission were summarized. Future research directions were also proposed and discussed to provide insights into developing more comprehensive and realistic CFD for airborne transmission in hospitals. •Majority of CFD studies reviewed evaluated the ventilation strategies in hospitals.•Hospital dynamic and high computational cost limited the number of simulated cases.•Ventilation strategies improvement based on professional judgement was recommended.•General occupied spaces, public areas, and multi-zone environments shall be studied.•Emerging CFD techniques can help develop more realistic and comprehensive models.