RISK ASSESSMENT FOR COVID-19 TRANSMISSION IN A HEALTH CARE CENTRE BASED ON FAULT TREE AND EVENT TREE

Abstract

Healthcare systems face significant challenges in containing the spread of infectious diseases. This work applies risk assessment and risk management, to evaluate COVID-19 transmission in the healthcare system. The starting point of this research is a Bow-Tie analysis that identified virus threats and consequences of the COVID-19 pandemic for various receptor groups. The study was motivated by the need to assess barriers to transmission in a quantitative manner. This work proposed a quantitative framework for stakeholders to analyze transmission risk and barrier criticality based on Fault Trees and Event Trees. Using the framework, this study collected data on failure probabilities relevant to COVID-19 from journals and expert opinions for a case study. This work also conducted a qualitative assessment and sensitivity analysis of the data. The outputs of calculations based on the Fault Tree and the Event Tree provided numeric results for the probability of each threat and consequence, indicating that the highest risk of infection came from asymptomatic patients. Finally, the work evaluated the overall risk of pandemic transmission at the partner hospital using the As Low As Reasonable Practical approach. The framework is shown to be effective at quantitatively assessing the risk of COVID-19 transmission in the healthcare system.