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This paper presents a position statement on combining computational fluid dynamics (CFD) and ergonomics to guide the design of personal protective equipment (PPE). We used CFD to simulate 36 exposure scenarios of an infected patient sneezing at different distances and different angles while facing either the front or the side of a healthcare worker with or without goggles. The results show that medical goggles indeed block most droplets from the outer surface, but many droplets still deposit on the bottom edge (especially at the nose), inside the air holes and on the side edge. However, the edges of medical goggles have fitment problems with people in different regions, and the air holes do not function as filters and cannot prevent fine droplets from entering the interior and contacting the eyes. Our research demonstrates the feasibility of studying the design of PPE for airtightness and protection by means of CFD. Practitioner summary:  Computational fluid dynamics can quickly and efficiently reflect the airtightness design problems of PPE. A model was developed using CFD to examine the protective effect of medical goggles in preventing the airborne transmission of viruses. The model demonstrates the feasibility of using CFD to solve ergonomic problems. Abbreviations:  CFD: computational fluid dynamics; PPE: personal protective equipment; WHO: the World Health Organisation; COVID-19: coronavirus disease 2019; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; OSHA: the Occupational Safety and Health Administration; CDC: the Centres for Disease Control; FEM: finite element method; 3M: Minnesota Mining and Manufacturing Corporation; SPH: smoothed particle hydrodynamics; AROM: active range of motion; DPM: discrete phase model; PISO: pressure implicit with splitting of operators; VR: virtual reality; AR: augmented reality

“Simulation of medical goggles to stop airborne transmission of viruses: computational fluid dynamics in ergonomics”