Fatality and influence factors in high-casualty fires: A correspondence analysis

The technology of correspondence analysis was applied to high-casualty fire data in China. The aim of this study was to investigate the associations between fatality levels and influence factors that involve place, cause, time of day, month, year and province. The variable fatality in a fire has four levels: 3, 4–5, 6–9 and ⩾10. The results show that hotels, welfare houses and hospitals tend to be strongly associated with fatality level ⩾10. The fires caused by work-related tasks tend to precipitate a relatively high number of fatalities and are strongly associated with fatality level 6–9. Fires that occur in the daytime (8:00–19:59) are associated with higher fatalities than fires that occur at night (20:00–7:59). The months in the cold season, such as winter or the beginning of spring, tend to be associated with fatality levels 4–5, 6–9 and ⩾10. CA dynamically portrayed the fatality tendency over the past 8 years, and 2007 tended to be associated with fatality level ⩾10. Fatality characteristics of provinces are identified, and Beijing, Shandong and Jilin are strongly associated with fatality level ⩾10. To explore whether associations between influence factors and fatality levels of high-casualty fires in China resemble corresponding associations of HCFs in the United States, data on fires with fatality level ⩾5 in the two countries were collected. The results of four sets of comparisons indicate that the associations between influences and fatality levels in the two countries present contrasting features. Some practical applications are briefly discussed.

► Associations among six factors and fatality levels of high-casualty fire are studied.
► Correspondence analysis is used for exploring the associations.
► Influence factors involve place, cause, time of day, month, year and province.
► Fatality in a high-casualty fire is divided into four levels: 3, 4–5, 6–9 and ⩾10.
► There are some factors that tend to be associated with very high fatality levels.