Background: This study investigated the frequency, characteristics, and geospatial clustering of hotel suicides in Australia to inform suicide prevention efforts. Aims: (1) To determine the proportion of suicide deaths that occurred in hotels, (2) to determine differences in demographic characteristics of hotel deaths compared to other locations, (3) to assess level of planning, and (4) to determine whether these deaths form geographic clusters amenable to targeted suicide prevention activities. Methods: Archival data on suicide mortality were used to examine associations between incident location (hotels, home, away from home), demographic characteristics, and suicide means. Kernel density visualization was used to assess geospatial clustering of hotel suicides, and the degree of planning involved was assessed using the modified Suicide Intent Scale. Results: Hotels accounted for 2% of all suicide deaths and 6.2% of suicides occurring away from home. Females were over-represented (p < .0001), as were deaths by drug overdoses (p < .0001) and falls (p < .0001). Approximately 40% of incidents occurred within seven geospatial clusters. 85% of those who died were state residents, with a median distance from home of 13.0 km. Most individuals checked in to the hotel alone, for short stays, and displayed a high degree of suicidal planning. Limitations: Coronial records had limited information on narrative circumstances of deaths; other indicators of risk may not have been identified. A comparison against a general population of hotel guests, rather than all other suicide deaths would be more useful in terms of preventative activities, however these data were not readily available. Conclusion: This study identified characteristics, behaviors, and geographic locations associated with hotel suicides to inform training of hotel staff to recognize and respond to signs of risk. Males of working age who live locally and arrive alone for short stays could be considered at a higher risk of suicide, and prevention efforts should be prioritized in the identified high-risk areas.
Keywords: epidemiology; geospatial analysis; suicide clusters; suicide prevention.