Emergency egress for the elderly in care home fire situations

Practitioners are continuing to develop egress modelling software for the design of the built environment. These models require data about human behaviour and factors for calibration, validation and verification. This study aims to address the specific data and knowledge gap: emergency egress of the elderly. Such data are difficult to collect given privacy and consent concerns, with strong relationships generally being required between residences and researchers. Through the observation of nine fire drills at six Canadian long‐term care (LTC) and retirement homes, specific evacuation actions and behaviour were observed for 37 staff members and information about the evacuation of 56 residents was collected. These drills demonstrated that emergency egress in LTC and retirement homes is highly staff dependent with 72% of residents recorded requiring full assistance at all stages of movement in evacuation, and that the type of announced/unannounced drill and level of resident care will affect the type of data collected. The development of travel speed and pre‐movement is discussed subject to limitation with qualitative behavioural insights of residents that were observed. This study provides valuable methodological discussion on how to conduct behavioural studies in similar highly restricted research environments. Specific attention is given to understanding the considerations that must be made when using fire drills as data sources, and the impact that these can have on using such data for modelling. This study may inform the initial setup and programming of evacuation models from an actions and behavioural perspectives of staff members and residents.

[1]  Michael K Lindell,et al.  The Protective Action Decision Model: Theoretical Modifications and Additional Evidence , 2012, Risk analysis : an official publication of the Society for Risk Analysis.

[2]  M. Kuttschreuter.  Communicating environmental risk in multiethnic communities , 2005 .

[3]  Edwin R. Galea,et al.  A review of the methodologies used in the computer simulation of evacuation from the built environment , 1999 .

[4]  Erica D. Kuligowski.  Computer Evacuation Models for Buildings , 2016 .

[5]  Erica D. Kuligowski,et al.  Review of Building Evacuation Models , 2005 .

[6]  Rodrigo Machado Tavares,et al.  Evacuation Processes Versus Evacuation Models: “Quo Vadimus”? , 2009 .

[7]  Daniel Nilsson,et al.  Enhancing egress drills: Preparation and assessment of evacuee performance , 2019 .

[8]  C. Goose,et al.  Glossary of Terms , 2004, Machine Learning.

[9]  Lauren H. Folk,et al.  DESIGN FOR ELDERLY EGRESS IN FIRE SITUATIONS , 2016 .

[10]  A. Steen-Hansen,et al.  How can fatal fires involving vulnerable people be avoided , 2016 .

[11]  D. A. Purser,et al.  Assessment of Hazards to Occupants from Smoke, Toxic Gases, and Heat , 2016 .

[12]  Erica D Kuligowski,et al.  Guidance for the Model User on Representing Human Behavior in Egress Models , 2017, Fire technology.

[13]  D. Purser.  Effects of pre‐fire age and health status on vulnerability to incapacitation and death from exposure to carbon monoxide and smoke irritants in Rosepark fire incident victims , 2017 .

[14]  Enrico Ronchi,et al.  The Process of Verification and Validation of Building Fire Evacuation Models , 2013 .

[15]  Francisca Cisneros Farrar,et al.  Aging population. , 2015, The Nursing clinics of North America.

[16]  Tokiyoshi Yamada,et al.  Visibility and Human Behavior in Fire Smoke , 2016 .

[17]  Erica D. Kuligowski,et al.  Predicting Human Behavior During Fires , 2013 .

[18]  Jose L. Torero,et al.  SFPE handbook of fire protection engineering , 2016 .

[19]  J. V. Rhee.  An Aging Population , 2018 .

[20]  J. Dinsmoor.  On Terms , 2003 .