Multi-hazard hospital evacuation planning during disease outbreaks using agent-based modeling

Abstract

As different types of hazards, including natural and man-made, can occur simultaneously, to implement an integrated and holistic risk management, a multi-hazard perspective on disaster risk management, including preparedness and planning, must be taken for a safer and more resilient society. Considering the emerging challenges that the COVID-19 pandemic has been introducing to regular hospital operations, there is a need to adapt emergency plans with the changing conditions, as well. Evacuation of patients with different mobility disabilities is a complicated process that needs planning, training, and efficient decision-making. These protocols need to be revisited for multi-hazard scenarios such as an ongoing disease outbreak during which additional infection control protocols might be in place to prevent transmission. Computational models can provide insights on optimal emergency evacuation strategies, such as the location of isolation units or alternative evacuation prioritization strategies. This study introduces a non-ICU patient classification framework developed based on available patient mobility data. An agent-based model was developed to simulate the evacuation of the emergency department at the Johns Hopkins Hospital during the COVID-19 pandemic due to a fire emergency. The results show a larger nursing team can reduce the median and upper bound of the 95% confidence interval of the evacuation time by 36% and 33%, respectively. A dedicated exit door for COVID-19 patients is relatively less effective in reducing the median time, while it can reduce the upper bound by more than 50%.

The effectiveness of naive optimization of the egress path for an active-shooter scenario

“…Haghpanah et al explored the evacuations of hospital, taking into account the different mobility disabilities of patients and requirements for distancing due to infectious diseases [13] . They introduced a non-ICU patient classification framework that identified the various mobility factors characterized by the patients conditions.…”

Proceedings of the 28th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA) [Volume 1]

“…requires exposing real people to potentially dangerous conditions. Especially in situations where users may have mobility restrictions, such as nursing homes or hospitals (Haghpanah et al, 2021;Yuyang et al, 2018). An intelligent computational tool that accounts for human and social crowd behaviour becomes a viable alternative here (Feng et al, 2020;Pan et al, 2007).…”

Crowd dynamics research in the era of Covid-19 pandemic: Challenges and opportunities

“…Also, while the issue of hospital evacuation has been particularly of the focus of attention of crowd researchers within both numerical and experimental realms in the years prior to pandemic, it may be worth noting that with hospitals around the world working at capacities treating Covid-19 patients, there may be further complications with respect to hospital evacuation that may require specific attention ( Haghpanah et al, 2021 , Yazdani et al, 2021 ). Development of specific strategies for the evacuation of hospital in which a mixture of Covid-19 patients and other patients are treated may require simulation testing and optimisation methods.…”