Fires are a major public safety problem, and can have devastating consequences including injuries, fatalities, and loss of property or infrastructure. Fires in the home present a particular hazard, accounting for the majority of fire-related fatalities, despite occurring in a location where most people feel safe and secure (Barnett, 2008; Roberts & Diguiseppi, 1999). It is also evident that adverse fire outcomes (particularly fatalities and injuries) can’t solely be attributed to fire severity, rather, some groups in society are disproportionately affected (Barnett, 2008). Thus, understanding risk factors specific to CFA’s jurisdiction is very important to guide prevention activities, and to target interventions to those most at risk. Using CFA’s Fire and Incident Reporting (FIRS) data, the current project aimed to answer two questions: (1) what do CFA data reveal about the causal factors influencing the incidence of residential fires?; and (2) what do CFA data reveal about the risk factors influencing the impact of residential fires? The incidence analysis was concerned with the risk of a residential fire incident occurring, regardless of the outcome of the fire. Incidence is particularly important, as fire ignitions are a good target for prevention. The incidence analysis considered the number of residential fires in each statistical area (using the Australian Bureau of Statistics Statistical Area Level 1 (SA1) as the spatial unit). Based on previous research, a range of socio-demographic variables were selected, including: household income, age of residents, educational attainment, and unemployment. Some of these variables were highly correlated, which essentially means that they measure the same underlying construct and thus only one of the correlated variables were included in the statistical models. Several socio-demographic variables were found to be related to fire incident risk. In terms of the rate per population, fire incident risk increased when: (1) the percentage of homes rented publicly increased; (2) the percentage of dwellings occupied only by those aged 65 years and over increased; and (3) the percentage of dwellings occupied only by unemployed persons increased. Fire incident risk decreased when the percentage of homes with a high equivalised income increased, and (2) the percentage of homes where occupants had moved in the last five years increased. In terms of the rate per number of homes, fire incident risk increased when: (1) the percentage of publicly rented dwellings increased; and (2) the percentage of dwellings occupied only by unemployed persons increased. In contrast, fire incident risk decreased when: (1) the percentage of homes where occupants had moved in the last five years increased; (2) the percentage of homes with a high equivalised income increased; and (3) the percentage of dwellings occupied only by those aged 65 years and over increased. These findings are broadly consistent with previous research that has linked fire incident risk with a range of socio-demographic variables. Older age and social and financial disadvantage have been shown in many studies to influence outcomes as a result of fire (e.g. Barnett, 2008; Xiong & Bruck, 2015). The current study provides evidence about their role in CFA-attended fires, and provides specific location data (at the SA1 level) relating to risk. Analyses also considered factors associated with the extent of property damage as a result of fire. Factors that were available for analysis included those relating to fire ignition, construction type and building materials. Consistent with previous research, the analyses found that various factors were related to fires extending beyond the room of origin (or higher estimated dollar loss). For example, fire impact was greater for: timber construction and cladding (compared with brick veneer); suspicious or failure to clean fires (such as fouled flue) when compared with operational deficiency (unattended) fires; and air conditioning or refrigeration equipment (compared to cooking equipment). Impact was greater when smoke alarms were not present, and when fires started in sleeping rooms. These factors are broadly consistent with a 2014 Productivity Commission report which reported that the most common risk factors for residential fires across Australia were misuse, failure or deficiency of ignition or ignited material, deliberate or suspicious fires, and natural causes (AGPC, 2014). While these analyses provide some interesting findings for CFA, it is important to acknowledge the data limitations when interpreting the evidence. FIRS captures only attended fires (e.g. incidents in CFA jurisdictions that were attended by CFA). Research indicates that the majority of house fires are not reported (e.g. Barnett, 2008) but unreported fires tend to be more minor and less likely to result in injury. Thus the current analyses represent only reported fires rather than the overall burden of fire. ‘Impact’ in the current study related to property damage only, and did not include other impacts of fire (for example, injury and death). This was due to incomplete recording of injury events, inadequate linkage to alternative injury datasets, and an insufficient number of fatality records for meaningful analysis. Two metrics were used to evaluate property damage impact: fire spreading beyond the room of origin, and estimated dollar loss. Both metrics have inherent limitations and more objective quantification of these measures may be useful (although it should be noted that both metrics were reasonably highly correlated and hence reflect similar outcomes). These results contribute to an evidence base which can be used by CFA when designing strategies and interventions to mitigate the effects of residential fires on communities. In particular, these analyses could be used in the development of a mapping tool to visually present the findings. Visual mapping tools would assist local level service delivery planners to target particular interventions to specific neighbourhoods and households with increased risk of residential fire occurrence, and increased risk of damage should a fire occur. To improve the strength of these analyses, it would be useful to extend data collection to the whole state of Victoria (including data from other agencies where possible), and to refine collection of injury data so impact can be more fully investigated.
|Commissioning body||Country Fire Authority (CFA) (Victoria)|
|Number of pages||183|
|Publication status||Published - 2016|