Initial test of emergency procedure performance in temporary negative pressure isolation by using simulation technologies

Towards optimal design of patient isolation units in emergency rooms to prevent airborne virus transmission: From computational fluid dynamics to data-driven modeling

BACKGROUND

Patient isolation units (PIUs) can be an effective method for effective infection control. Computational fluid dynamics (CFD) is commonly used for PIU design; however, optimizing this design requires extensive computational resources. Our study aims to provide data-driven models to determine the PIU settings, thereby promoting a more rapid design process.

METHOD

Using CFD simulations, we evaluated various PIU parameters and room conditions to assess the impact of PIU installation on ventilation and isolation. We investigated particle dispersion from coughing subjects and airflow patterns. Machine-learning models were trained using CFD simulation data to estimate the performance and identify significant parameters.

RESULTS

Physical isolation alone was insufficient to prevent the dispersion of smaller particles. However, a properly installed fan filter unit (FFU) generally enhanced the effectiveness of physical isolation. Ventilation and isolation performance under various conditions were predicted with a mean absolute percentage error of within 13%. The position of the FFU was found to be the most important factor affecting the PIU performance.

CONCLUSION

Data-driven modeling based on CFD simulations can expedite the PIU design process by offering predictive capabilities and clarifying important performance factors. Reducing the time required to design a PIU is critical when a rapid response is required.

Simulation and Modeling Applications in Global Health Security

Global health security (GHS) is dependent upon having an adequate and prepared health security workforce. There are currently numerous challenges in establishing and maintaining a health security workforce. The frequency and magnitude of disasters have increased significantly over the past 30 years. Current and future GHS threats, both manmade and natural, require a prepared and flexible healthcare provider workforce ready to respond to current or emerging GHS threats. Developing and maintaining GHS -specific skills in the healthcare workforce is a tremendous logistical challenge. Innovative education technologies, including simulation and digital learning, can be leveraged to achieve preparedness for GHS threats.

This chapter focuses on the application of modeling and simulation to support Global Health Security planning, preparedness and operations.

Simulation in emergency medicine training

Simulation provides a range of educational tools that have increasingly been incorporated into emergency medicine (EM) curricula. Standardized patients and some partial task trainers, such as intubation heads, have been used for decades. More recently, a growing number of computer-screen simulations, high-fidelity mannequins, and virtual-reality simulators have expanded the number of procedures and conditions, which can be effectively simulated.The Accreditation Council for Graduate Medical Education transitioned to a competency-based assessment of residency programs in 2001 and included simulation as a method for incorporating the 6 core competencies into graduate medical education curricula. Over the past decade, numerous peer-reviewed publications have promoted simulation as an effective educational tool for each of the core competencies.The advanced technology used to operate many current simulators can erroneously become the focus of efforts to create a simulation-based curriculum. Simulation can most effectively be incorporated into EM curricula through the use of time-proven concepts, which start with defining the targeted learners, assessing their general and specific educational needs, defining learning objectives, and selecting the best educational strategy for achieving each objective. In many, but not all, instances, simulation can be the best tool for achieving EM learning objectives.