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Asuinrakennuspalon riskin ja siihen vaikuttavien tekijöiden maantieteellinen mallinnus Helsingin pelastustoimen alueella (Geographical modelling of residential building fire risk and the factors affecting it in the Helsinki Rescue Service area)
In our article, we develop the concept of safety capital, which on the individual level includes internalized safety knowledge, behavior, and attitudes. The concept is useful both in terms of academic safety research and applied research. We strive to create a foundation for a multidisciplinary understanding of safety that is both focused on the individual and community levels. Increasing safety capital is an effective goal that is important for both structural and individual level safety. First, we open key concepts, such as safety and different forms of capital, then define the concept of safety capital, including attitudes, competence (knowledge and skills), feeling of safety, and trust. Finally, we consider how safety capital is developed and maintained. We present safety capital as its own form of capital, with elements of both cultural and social capital, which can be distinguished both as a resource of the individual, and more broadly, in society.
The sociodemographic inequalities in the ownership of residential fire safety equipment, fire prevention practices and fire protection knowledge was studied using an inductive and data-driven approach based on the responses to a national Swedish survey containing individual-level data on several dimensions of home fire safety practices (n = 7507). Cluster analysis was used to summarise home fire safety data and sociodemographic characteristics of the sample were then regressed on the data ordinal regression analysis. The results showed significant correlations between the level of fire protection and a range of factors (sex, age, family composition, income, housing type and country of birth), suggesting a positive effect of socioeconomic success. Further, the results imply that having experienced a residential fire has a positive impact on future fire protection practices, and that higher levels of fire protection interest increases the probability of having a functional smoke detector.
This article applies a Markov chain method to compute the probability of residential fire occurrence based on past fire history. Fitted with the fire incidence data gathered over a period of 10 years in Melbourne, Australia, the spatially-integrated fire risk model predicts the likely occurrence of fire incidents using space and time as key model parameters. The mapped probabilities of fire occurrence across Melbourne show a city-centric spatial pattern where inner-city areas are relatively more vulnerable to a fire than outer suburbia. Fire risk reduces in a neighborhood when there is at least one fire in the last 1 month. The results show that the time threshold of reduced fire risk after the fire occurrence is about 2 months. Fire risk increases when there is no fire in the last 1 month within the third-order neighborhood (within 5 km). A fire that occurs within this distance range, however, has no significant effect on reducing fire risk level within the neighborhood. The spatial–temporal dependencies of fire risk provide new empirical evidence useful for fire agencies to effectively plan and implement geo-targeted fire risk interventions and education programs to mitigate potential fire risk in areas where and when they are most needed.
In this report, we analyze urban social sustainability in the three largest city regions in Finland. We focus on the differentiation in housing conditions and on residential segregation by income and ethnicity in the 20 to 64 years old population. The aim is to provide a descriptive overview of basic tendencies in the regions and of differences between
the regions.
Our primary statistical data source is a register-based individual-level longitudinal dataset created in Statistics Finland for the URMI (Urbanization, Mobilities and Immigration) project, containing data for the total populations of the study regions. Additionally, we use secondary statistical data sources, and in an assessment of the development
of anti-segregation policies in the central cities of the regions (Helsinki,
Turku and Tampere) we use qualitative interview and document data.
In each of the study regions, we analyze (1) the development of income inequality, (2) residential segregation by ethnicity and income, (3) differentiation in housing conditions by country of birth and income, (4) housing subsidies for low-income households, and (5) anti-segregation policies of the central cities. Statistical analyses focus on the years 2005 to 2014, while the policy analysis pertains to a longer time span.
Income inequality is at a modest level in Finland in an international comparison. In the central cities of the study regions it is stronger, as measured by the Gini index, the strongest in Helsinki. As a whole, income inequality did not increase during the study period, although there had been clear increase earlier, in the 1990s.
There were no large changes in the level of residential segregation in the study regions during the study period, as measured by the index of dissimilarity. However, a slight increase in ethnic segregation was observed, and the shares of immigrants in the regional populations also increased, leading to higher shares in neighbourhood populations.
Ethnic segregation is strongest in the Turku region. In all regions, ethnic segregation in the 0-17-years-old population by background country – based on parents’ countries of birth – is stronger than ethnic segregation among the working-age population. Increase in income segregation occurred in the Turku and Tampere regions. The Helsinki region differs from the other regions by stronger segregation between the
high-income population and the rest, especially when looking only at the city of Helsinki, and by weaker segregation between the low- and middle-income populations.
The differentiation by income in the level of homeownership increased in all study regions between 2005 and 2014. Immigrants have lower homeownership rates in all income categories, but higher income predicts higher homeownership rates also among them. Homeownership has become more common in several immigrant groups, although
large differences between the groups remain. The association between income and overcrowding has become a little stronger. The standard of equipment in dwellings is generally good and differences are small in this respect. Immigrants do not live more commonly in sub-standard dwellings, as they are concentrated in newer dwellings
built since the 1960s.
Housing costs in the central cities of the regions have risen so much – the most in Helsinki – that many low-income households need both housing assistance and social assistance to cover their housing costs. Also state-subsidized rental dwellings have been important: in Helsinki, over 20 per cent of housing stock has consisted of them, and slightly less in Turku and Tampere. In Helsinki, rents per square meter are significantly
lower in state-subsidized rental dwellings than in the private rental dwellings. A larger proportion of the low- and middle-income population lives in state-subsidized rental dwellings in Helsinki than in the other cities.
All three central cities have had anti-segregation policies. However, the cities of Helsinki and Tampere have had more persistent social mix policies, where mixing of different housing tenures spatially in new housing construction has been a central instrument. The city of Turku has had similar overt aims, but they have not led similarly to action. Corresponding to these differences in policies, state-subsidized rental dwellings have a more even spatial distribution in Tampere and Helsinki than in Turku. In all cities, targeted area-based policies have been conducted for decades. The resources for these have been the strongest and the most constant in Helsinki. Area-based policy programs launched by the state have so far been terminated and this has led to a situation
in which local solutions are emphasized.
All in all, the changes occurring in income inequality, residential segregation, and housing conditions between 2005 and 2014 have not been large in the Helsinki, Turku and Tampere regions. However, those changes that have happened have primarily increased differentiation by income and ethnicity. Therefore, the regions may be moving slowly towards stronger internal differentiation. Based on existing international comparisons of the city of Helsinki or the metropolitan area around the city, residential segregation by income or ethnicity has so far been at a rather modest level. The main exception to this finding of rather low levels of segregation seems to be the higher level of ethnic segregation in Turku. We do not observe such levels of segregation indices that would typically be considered to be very high, however. Possibilities for sustainable urban development certainly exist in the cities, offering good opportunities to strengthen other dimensions of sustainability
as well.
Urban fire occurs within the built environment, usually involving casualties and economic losses, and affects individuals and socioeconomic activities in the surrounding neighborhoods. A good understanding of the spatiotemporal dynamics of fire incidents can offer insights into potential determinants of various fire events, therefore enabling better fire risk estimation which can assist with future allocation of prevention resources and strategic planning of mitigation programs. Using a twelve-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatiotemporal dynamics of urban fires using a range of exploratory spatial data analysis (ESDA) approaches. Of particular interest here are the fire incidents involving residential properties and local facilities due to their relatively higher occurrence frequencies. The results indicate that the overall amount of urban fires has greatly increased in the last decade and the spatiotemporal distribution of fire events varies among different incident types. The identified spatiotemporal patterns of urban fires in Nanjing can be linked to the urban development strategies and how they have been reflected in reality in recent years.
Rapid response to fire incidents is critical as delays in the departure and arrival at the scene can have significant consequences in terms of damage, injury and death. Research on the dynamics of residential fire incident response times has barely begun, a situation arguably underpinned by limited access to disaggregate command and control data. In this paper we draw on unit record data and employ quantile regression to examine the role that socio-demographic, infrastructure characteristics and temporal factors play on response times. Results reveal that response times are slower during the winter, in locales with larger numbers of children (aged 14 years and below) and low socioeconomic households, and in areas that have more complex street layouts. We conclude through emphasising the importance of these findings in their capacity to contribute to a new evidence base to inform policy decisions from a resource allocation perspective through the spatial allocation of finite fire resources.
An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.
Socioeconomic inequality is on the rise in major European cities, as are concerns over it, since it is seen as a threat to social cohesion and stability. Surprisingly, relatively little is known about the spatial dimensions of rising socioeconomic inequality. This paper builds on a study of socioeconomic segregation in 12 European cities: Amsterdam, Athens, Budapest, London, Madrid, Oslo, Prague, Riga, Stockholm, Tallinn, Vienna, and Vilnius. Data used derive from national censuses and registers for 2001 and 2011. The main conclusion is that socioeconomic segregation has increased. This paper develops a rigorous multifactor approach to understand segregation and links it to four underlying, partially overlapping, structural factors: social inequalities, globalization and economic restructuring, welfare regimes, and housing systems. Taking into account contextual factors resulted in a better understanding of actual segregation levels, while introducing time lags between structural factors and segregation outcomes will likely further improve the theoretical model.
Fires in urban areas can cause significant economic, physical and psychological damage. Despite this, there has been a comparative
lack of research into the spatial and temporal analysis of fire incidence in urban contexts. In this paper, we redress this
gap through an exploration of the association of fire incidence to weather, calendar events and socio-economic characteristics
in South-East Queensland, Australia using innovative technique termed the quad plot. Analysing trends in five fire incident
types, including malicious false alarms (hoax calls), residential buildings, secondary (outdoor), vehicle and suspicious fires,
results suggest that risk associated with all is greatly increased during school holidays and during long weekends. For all
fire types the lowest risk of incidence was found to occur between one and six a.m. It was also found that there was a higher
fire incidence in socially disadvantaged neighbourhoods and there was some evidence to suggest that there may be a compounding
impact of high temperatures in such areas. We suggest that these findings may be used to guide the operations of fire services
through spatial and temporal targeting to better utilise finite resources, help mitigate risk and reduce casualties.
Geographically weighted regression (GWR) is an important local technique for exploring spatial heterogeneity in data relationships. In fitting with Tobler's first law of geography, each local regression of GWR is estimated with data whose influence decays with distance, distances that are commonly defined as straight line or Euclidean. However, the complexity of our real world ensures that the scope of possible distance metrics is far larger than the traditional Euclidean choice. Thus in this article, the GWR model is investigated by applying it with alternative, non-Euclidean distance (non-ED) metrics. Here we use as a case study, a London house price data set coupled with hedonic independent variables, where GWR models are calibrated with Euclidean distance (ED), road network distance and travel time metrics. The results indicate that GWR calibrated with a non-Euclidean metric can not only improve model fit, but also provide additional and useful insights into the nature of varying relationships within the house price data set.
Residential fires are the most important cause of fire-related mortality in the United States. Previous research has concentrated on fatal fires in urban areas; considerably less is known about fatal fires in rural areas.
We studied fatal and nonfatal residential fires in predominantly rural areas. Using a case-control design, we compared all 151 fatal fires (cases) in single-family dwellings in North Carolina during a 13-month period with a sample of nonfatal fires (controls). Case fires were identified through the medical-examiner system, and control fires that occurred within a few weeks of the case fires were chosen from the records of randomly selected fire departments statewide. For each fire, fire officials were interviewed about the dwelling, the fire, the people involved, and the fire-response system.
Although heating incidents were the leading cause of fires, fatal fires were more likely to have been caused by smoking (31 percent of fatal fires vs. 6 percent of nonfatal fires). Mobile homes posed a higher risk of death if a fire occurred (odds ratio, 1.7; 95 percent confidence interval, 1.1 to 2.6), as did the absence of a smoke detector (odds ratio, 3.4; 95 percent confidence interval, 2.1 to 5.6). Smoke detectors were more protective against death in fires involving young children and when no one present was impaired by alcohol or drugs or had a physical or mental disability. The presence of an alcohol-impaired person was the strongest independent risk factor for death in the case of a fire (odds ratio, 7.5; 95 percent confidence interval, 4.4 to 12.7).
Residential fires are most likely to be caused by heating equipment or smoking materials. The risk of death is greatest in fires in mobile homes, in those involving alcohol-impaired persons, and in those in houses without smoke detectors.
The relationship between urban spaces, associated risk, and the notion of proximity has until now been subject to very little critical examination. It is, however, crucial to conduct a discussion on the subject, especially in view of the latest disasters that have made the headlines (notably in New York and Toulouse in September 2001, in Madrid in March 2004). On the one hand, it is widely understood that the consequences of risk tend to be more severe in urban environments; on the other, the categorisation of different risks (industrial, social, environmental risks, etc.) within a space reinforces the probability of all kinds of disaster occurring. This line of reasoning will be questioned through a case study. By observing the practices amongst the different parties involved in identifying and managing the risk of fire in Geneva (Switzerland), we will propose the notion of connexity as a complement to that of proximity, as it is more closely related to the practices in action in this field.
Objectives
This study aimed to investigate the association between sociodemographic factors and residential fire fatalities in Sweden. A majority of fatal fires occur in housing. An understanding of risk factors and risk groups is a must for well-founded decisions regarding targeted prevention efforts. There is a lack of consideration of the interrelation between sociodemographic factors and fire fatalities and there is a lack of high quality large-scale studies.
Methods
In this matched case-control study, residential fire fatalities (cases, n=850) (age above 19 years old) were identified in the national register on fatal fires. Four controls per case were randomly matched by gender and age. ORs were calculated to assess the association between different sociodemographic factors with residential fire fatalities using conditional logistic regression.
Results
Having low income, receiving social allowance and receiving health-related early retirement pension were associated with an increased risk of dying in residential fires. The results also show clearly that adults dying in residential fires to a significantly lower extent were living together with a partner, were in work, were highly educated and lived in urban areas. However, contrary to previous research, living in rented apartments appeared not to influence the risk of death.
Conclusions
In this study, we show that fatalities due to residential fires in Sweden are associated with some but not all of previously published sociodemographic risk factors. The results provide valuable information that can improve the guiding and targeting of fire mortality prevention strategies in Sweden.
Objective
To identify the distinguishing risk factors associated with unintentional house fire incidents, injuries and deaths.
Study design
Systematic review.
Methods
A range of bibliographical databases and grey literature were searched from their earliest records to January 2016. To ensure the magnitude of risk could be quantified, only those study types which contained a control group, and undertook appropriate statistical analyses were included. A best evidence synthesis was conducted instead of a meta-analysis due to study heterogeneity.
Results
Eleven studies investigating a variety of risk factors and outcomes were identified. Studies ranged from medium to low quality with no high quality studies identified. Characteristics commonly associated with increased risk of house fire incidents, injuries and fatalities included: higher numbers of residents, male, children under the age of 5 years, non-working households, smoking, low income, non-privately owned properties, apartments and buildings in poor condition. Several risk factors were only associated with one outcome (eg, living alone was only associated with increased risk of injurious fires), and households with older residents were at increased risk of injurious fires, but significantly less likely to experience a house fire in the first place.
Conclusions
This best evidence synthesis indicates that several resident and property characteristics are associated with risk of experiencing house fire incidents, injuries or death. These findings should be considered by the Fire and Rescue Services and others with a role in fire prevention. Future research should adopt robust, standardised study designs to permit meta-analyses and enable stronger conclusions to be drawn.
Despite the considerable reduction in rates of fire that have been seen in the UK in recent years analysis of three years of service data from a large UK fire service reveals that there continue to be striking inequalities in the way in which fire is distributed through society. The use of principal component analysis (PCA) and ordinary least squares regression enabled the development of a model that explains around one third of the variance in rates of fire at small neighbourhood level using just three predictor variables: the proportion of residents identifying as Black, the proportion of residents who have not worked for more than five years or have never worked, and the proportion of single person households where the resident is aged under 65. The value of PCA in addressing problems of collinearity between potential predictor variables is particularly highlighted. The findings serve to update understanding of the distribution of fire in the light of the ongoing reduction in fire rates of recent years. They will help fire services to target fire safety interventions to those neighbourhoods and communities where they are most needed and have the greatest potential to bring about reductions in the rate of fire.
Whilst determinants for fire mortality and morbidity are well documented, the determinants of residential fires, regardless of outcome, are less known. This study aimed to investigate socio-demographic differences between households having experienced a fire and those who had not. Using a cross-sectional study design, a questionnaire was sent to a stratified sample (n = 20,000) of the Swedish population regarding if the household had experienced a fire during the past 5 years. Pearson’s χ2-test was used to test for bivariate associations between residential fires and socio-demographic covariates, and log-binomial regression models were applied to obtain covariate-adjusted risk ratios. Significant factors associated with an increased risk of residential fires were a high education level, being born outside of the Nordic countries and having children 6-12 years living at home. A significant decreased risk was observed amongst elderly and those living in rented, multi-family houses. There seems to be a lack of agreement between determinants for fires and for fire mortality. This would indicate that the risk of fire mortality per residential fire is greatly increased for certain groups and that the increased risk of fire mortality is not due to a more common occurrence of fires.
The risk assessment chapters in this section describe concepts and methods to be used in answering the three questions: What could happen? How bad would it be? How likely is it? This chapter in particular is intended to provide an overview of fire risk analysis as a whole, indicating how the subsequent chapters fit together and how a completed fire risk analysis connects to other evaluative and management activities. The purpose of this introductory chapter is threefold © Society of Fire Protection Engineers 2016. All rights reserved.
The spatial patterns of fire occurrence were analyzed in two regions of Southern Europe, focusing on the long-term factors that influence fire distribution. The relationship between fire occurrence and the physical and anthropogenic variables collected was investigated with Geographically Weighted Regression (GWR) and the results were compared with Ordinary Least Squares (OLS). Local patterns of the significant variables were explored and a strong spatial variability of their explanatory power was revealed. Climate (precipitation), livestock and land cover (shrubland) were found to be significant in both regions, although in particular areas and to different extents. Regarding model performance, GWR showed an improvement over OLS in both regions.
The investigation of the spatial variation in the importance of the main drivers over a broad study area, gives a valuable contribution to the improvement of fire management and prevention strategies, adjusted to the particular conditions of different areas.
We examine the causal factors involved in unintentional dwelling fire incidents within the Merseyside area of the North West region of the United Kingdom. The approach of all-subsets multiple linear regression was used to develop an unintentional dwelling fire risk model for the region. The risk model was based on data obtained from UK government agencies relating to causal factors identified by earlier published studies. In the region studied, mental health problems, disability and residents living alone were the most significant factors associated with unintentional dwelling fire fatalities. However, in a separate model of the incidence of unintentional dwelling fires within the region, binge drinking and smoking were additional statistically significant factors.
This paper focuses on a systematic risk mapping for mitigation purposes, which plays a crucial role in the context of the emergency management. It applies principles of the knowledge discovery and data mining to support development of the fire risk model at a city level. The study offers a set of advanced methods of the spatial and spatio-temporal analysis that share the same goal – to unveil causal relationships in the incident data. Each of the methods, however, reveals different aspects of the relations, which represents a valuable source of information. The results of this research thus enhance understanding of the phenomenon being studied and enable more accurate risk maps to be created.
This article presents a literature review of the socioeconomic modeling of fire incidence, with an emphasis on urban residential fires. The development and history of socioeconomic models of fire incidence are reviewed from the perspectives of ecology and location economics within the urban planning discipline, which encompasses sociological, economic, epidemiological, and interdisciplinary approaches. The predominant methodology used is a thematic type of qualitative analysis, and detailed information on variables selected and results are offered where appropriate. The article closes with suggestions for further research.
In our previous research we applied spatial statistics and regression analysis to explore the relationships between the types of socio-economic factors that are associated with different fire incident types for an area of South Wales, UK. In this paper, we extend this analysis by using a comparative approach applying regression analysis to examine intra-urban trends in fire incidence using the case studies of Brisbane (Australia) and Cardiff (United Kingdom). Whilst drawing attention to the problems faced by researchers using spatial data in comparative contexts, this has revealed some important similarities and differences in associations, for example in relation to the residential patterns of the two cities which is reflective of their respective wider urban geography. We conclude by demonstrating the differences in trends between Cardiff and Brisbane and by highlighting outcomes from this research that are of relevance to policy makers in urban contexts. The latter could include for example those charged with identifying high risk communities, designing possible intervention strategies such as safety campaigns or with implementing educational programmes.
An exploratory data analysis tool termed the comap is introduced. This is essentially a geographical variant of the coplot, an exploratory graphical method to investigate the relationship between a pair of variables conditioned on a third variable (and perhaps also a fourth). In the comap, the first pair of variables represent geographical location, and the graphical technique is adapted to reflect this. After the concept of the comap is discussed and an example is given, computational aspects are considered. The paper concludes with a brief discussion.
The spatio-temporal analysis of residential fires could allow decision makers
to plan effective resource allocations in fire management according to fire
clustering levels in space and time. In this study, we provide guidelines for
the use of various methods in detecting the differences in clustering patterns
of fire and non-fire (i.e., background residential) locations and how these
patterns change over time. As a preliminary analysis step, various exploratory
data analysis methods, such as, intensity plots (i.e., kernel density
estimates) are used. Moreover, the use of Diggle's D-function (a second order
analysis technique) is proposed for detecting the clustering of residential
fire locations (if any) and whether there is additional clustering (or
regularity) in the locations of the fires compared to background residential
pattern. A test for trend over time (in years, months, and weeks) of the fire
location patterns are provided with a space-time interaction analysis by
spatio-temporal K-function. Residential fire data from \c{C}ankaya Municipality
of Ankara, Turkey is used as an illustrative example. The presented methodology
is also applicable to residential fire data from similar urban settings.
Spatial nonstationarity is a condition in which a simple “global” model cannot explain the relationships between some sets of variables. The nature of the model must alter over space to reflect the structure within the data. In this paper, a technique is developed, termed geographically weighted regression, which attempts to capture this variation by calibrating a multiple regression model which allows different relationships to exist at different points in space. This technique is loosely based on kernel regression. The method itself is introduced and related issues such as the choice of a spatial weighting function are discussed. Following this, a series of related statistical tests are considered which can be described generally as tests for spatial nonstationarity. Using Monte Carlo methods, techniques are proposed for investigating the null hypothesis that the data may be described by a global model rather than a non-stationary one and also for testing whether individual regression coefficients are stable over geographic space. These techniques are demonstrated on a data set from the 1991 U.K. census relating car ownership rates to social class and male unemployment. The paper concludes by discussing ways in which the technique can be extended.
The application of mapping and spatial analytical techniques to explore geographical patterns of crime incidence is well established. In contrast, the analysis of operational incident data routinely collected by fire brigades has received relatively less research attention, certainly in the UK academic literature. The aim of this paper is to redress this balance through the application of spatial analytical techniques that permit an exploration of the spatial dynamics of fire incidents and their relationships with socio-economic variables. By examining patterns for different fire incident types, including household fires, vehicle fires, secondary fires and malicious false alarms in relation to 2001 Census of Population data for an area of South Wales, we demonstrate the potential of such techniques to reveal spatial patterns that may be worthy of further contextual study. Further research is needed to establish how transferable these findings are to other geographical settings and how replicable the findings are at different geographical scales. The paper concludes by drawing attention to the current gaps in knowledge in analysing trends in fire incidence and proposes an agenda to advance such research using spatial analytical techniques.
Temporal, spatial, and spatiotemporal analyses of structural fire incidents occurring in Toronto, Ontario, Canada from 2000 to 2006 are carried out. The aim of the study is to gather and analyze data on various causes of fires in order to determine the extent to which existing data can be used as a baseline to improve fire prevention and response activities at local levels. This research uses spatiotemporal techniques to illustrate how the patterns of structural fire incidents in Toronto vary with the time of the day, the day of the week, and the month of the year. The application of these techniques has the potential to help decision makers with proactive preventive measures over time and space in addition to improved resource allocations after an emergency has occurred. It is shown that significant differences exist with respect to fire causation over time and space.
A cross-sectional study was undertaken in Aotearoa New Zealand to investigate the relationship between socioeconomic deprivation and risk of an unintentional fatal domestic fire incident. Addresses of unintentional fatal domestic fire incidents were geocoded to small area (census meshblock) level and analysed with the New Zealand index of socioeconomic deprivation. Fatal unintentional domestic fire incidents occurred disproportionately in dwellings in the most socioeconomically deprived meshblocks. Annual rates of fatal unintentional fire incidents per 100,000 households in the most deprived decile were significantly higher than rates in the least deprived decile (RR 5.6, 95%CI 1.9–16). Strategies to prevent fire related deaths must overcome barriers to household fire safety in population groups experiencing increased risk, including the socioeconomically deprived, seniors, and ethnic minorities. Specific intervention strategies relevant to risks associated with socioeconomic deprivation include improving quality and affordability of housing; increasing prevalence of installed and functioning smoke detectors; and regulation of specific characteristics of cigarettes to reduce risk of ignition from abandoned heat sources. Substantial progress awaits reduction of the underlying socioeconomic determinants of disadvantage.
London is a large capital city with a population of approximately seven million people. It shares many problems with other large cities around the world, including deaths due to fire. Many of these fire deaths can be linked to social problems such as poor housing, loneliness, illness, etc.Data from the London Fire Brigade Real Fire Library—a unique database of information collected from real fire incidents by dedicated teams of fire investigators operating in the Greater London Area has been used to obtain a range of statistics about fatal fires and fire death victims for the 5-year period from 1996 to 2000. Most deaths occurred in unintentional dwelling fires. The statistical information has therefore been analysed to identify the main factors involved as to why people die in unintentional dwelling fires and see what lessons can be learnt from these deaths.Common risk factors identified in the unintentional dwelling fire deaths investigated include smoking, alcohol, old age, disability, illness, living alone, social deprivation and not having a working smoke alarm fitted. Comparisons are also made with the results found from other studies and measures for preventing unintentional dwelling fire deaths are examined.
Domestic fires at the city level, being causes for casualties and causing significant material damages, are stored as a point pattern in a GIS. In this paper we apply a statistical point pattern analysis to derive major causes from related layers of information. We fit a G-function to analyse neighbourhood relations and a Strauss process for inferring causal relations. Using open-source software we find significant differences in patterns and explaining factors between the different parts of the day, in particular for different building types and income groups. We conclude that a quantitative spatial model can be fitted and that this provides a useful opportunity for fire brigades to improve planning their efforts.
Comparison of characteristics of fire with non-fire households to determine factors differentially associated with fire households (fire risk factors).
National household telephone survey in 2004-2005 by the US Consumer Product Safety Commission with 916 fire households and a comparison sample of 2161 non-fire households. There were an estimated 7.4 million fires (96.6% not reported to fire departments) with 130,000 injuries.
Bivariate analysis and multivariate logistic regression analyses to assess differences in household characteristics.
Significant factors associated with fire households were renting vs. owning (OR 1.988 p<0.0001); household members under 18 year of age (OR 1.277 p<0.0001); lack of residents over 64 years old (OR 0.552 p=0.0007); and college or higher education (some college OR 1.444 p=0.0360, college graduate OR 1.873, p<0.0001, postgraduate OR 2.156 p<0.0001). Not significant were age of house; race; ethnicity; and income. Number of smokers was borderline significant (OR 1.132 p=0.1019) but was significant in the subset of fire households with non-cooking fires (OR 1.383 p=0.0011). Single family houses were associated with non-fire households in the bivariate analysis but not in the multivariate analyses.
Renting, household members under 18 years old and smokers are risk factors for unattended fires, similar to the literature for fatal and injury fires. Differences included household members over 65 years old (associated with non-fire households), college/postgraduate education (associated with fire households) and lack of significance of income. Preventing cooking fires (64% of survey incidents), smoking prevention efforts and fire prevention education for families with young children have the potential for reducing unattended fires and injuries.
This paper investigates the relationships between areas of building fire incidence, levels of socio-economic disadvantage and the underlying socio-economic characteristics in the South East Queensland (SEQ) region, Australia. Disaggregated fire incident data was acquired from the Queensland Fire and Rescue Service (QFRS) and then aggregated to the Statistical Local Area (SLA) level. The Australian Bureau of Statistics (ABS) defined index of socio-economic disadvantage (called 'SEIFA') has been used as the basis to identify relationships between socio-economic disadvantage and building fires. A regression model was then developed to predict the incidence of building fires using a range of socio-economic variables. Five significant predictors were identified that include: i) percentage of unemployed, ii) proportion of Indigenous population, iii) families living in separate dwellings, iv) one parent, and v) parent families with children less than fifteen years of age. Results also show that the distribution of building fires varies markedly across the SEQ region, with some of the Brisbane inner suburbs, areas of high socio-economic disadvantage, and parts of inland SEQ associated with relatively high fire rates.
In further exploration of structural fire as an urban parasite, the influence of areal population density and housing overcrowding on incidence and average size of structural fires is analyzed. Because the more people per square mile and per room the greater the incidence and size of the structural fires, the destruction of housing by fire and fire-related building abandonment creates fertile ground for even greater fire damage due to the crowding of the refugees into the remaining housing stock. The vicious circle of housing overcrowding and fire holds serious implications with respect to other density dependent factors, such as public health, the public transportation system, and sanitation. Parasitology continues to provide insight into the mechanisms of the behavior of structural fire and its impacts.
This study investigates the social and demographic correlates of nonfatal structural fire injury rates for the civilian population for Philadelphia census tracts during 1993-2001.
The author analyzed 1,563 fire injuries by census tract using the 1990 census (STF 3) and unpublished data from the Office of the Fire Marshal of the Philadelphia Fire Department. Injury rates were calculated per 1,000 residents of a given census tract. Multiple regression was used to determine significant variables in predicting fire injuries in a given census tract over a nine-year period and interaction effects between two of these variables-age of housing and income.
Multiple regression analysis indicates that older housing (prior to 1940), low income, the prevalence of vacant houses, and the ability to speak English have significant independent effects on fire injury rates in Philadelphia. In addition, the results show a significant interaction between older housing and low income.
Given the finding of very high rates of fire injuries in census tracts that are both low income and have older housing, fire prevention units can take preventative measures. Fire protection devices, especially smoke alarms, should be distributed in the neighborhoods most at risk. Multiple occupancy dwellings should have sprinkler systems and fire extinguishers. Laws concerning the maintenance of older rental housing need to be strictly enforced. Vacant houses should be effectively boarded up or renovated for residential use. Fire prevention material should be distributed in a number of languages to meet local needs.
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