Do home fire and safety checks by on-duty firefighters decrease the number of fires? Quasi-experimental evidence from Southern Sweden

Interventions for Preventing Residential Fires in Vulnerable Neighbourhoods and Indigenous Communities: A Systematic Review of the Literature

Globally, residential fires constitute a substantial public health problem, causing major fire-related injury morbidity and mortality. This review examined the literature on residential fire prevention interventions relevant to Indigenous communities and assessed their effectiveness on mitigating fire incidents and their associated human and economic burden. Electronic databases including MEDLINE, EMBASE, CENTRAL, and Web of Science Core Collection were reviewed for studies on fire prevention interventions published after 1990 and based on the 4E’s of injury prevention approaches (Education, Enforcement, Engineering, and Engagement). The grey literature and sources including indigenous organizational websites were also searched for eligible studies. Two authors independently screened, selected, and extracted data, in consultation with experts in the field. Outcomes measured included enhanced safety knowledge and practices, decreased residential fires incidents, reduced fire-related injuries and deaths, and lowered costs for healthcare needs. After removing duplicates, screening titles and abstracts, and assessing full texts, 81 articles were included in this review. Of the included studies, 29.1% implemented educational interventions within a variety of settings, including schools, community centres and homes, and included healthcare professionals and firefighters to raise awareness and the acquisition of fire safety skills. Engineering and environmental modifications were adopted in 20.2% of the studies with increased smoke alarm installations being the leading effective intervention followed by sprinkler inspections. Moreover, engagement of household members in hands-on safety training proved to be effective in enhancing household knowledge, fire safety decisions and practices. More importantly, effective outcomes were obtained when multi-faceted fire safety interventions were adopted, e.g., environmental modification and educational interventions, which together markedly reduced fire incidents and associated injuries. This review reveals the dearth of fire prevention evidence gathered directly within Indigenous communities. Nonetheless, relevant fire prevention recommendations can be made, calling for the adoption of combined and context-sensitive fire prevention interventions tailored to targeted Indigenous and vulnerable communities through multiple approaches and measures. Follow-ups and longitudinal studies are critical for accurate evaluation of the long-term outcomes and impacts on preventing residential fires.

A (Flexible) Synthetic Control Method for Count Data and Other Nonnegative Outcomes

The synthetic control method is a covariate balancing method that exploits data from untreated regions to construct a synthetic control that approximates a single, aggregate treatment unit on a time series of preintervention outcomes and covariates. The method is increasingly being used to evaluate population-level interventions in epidemiology. Although the original version can be used with bounded outcomes, it imposes strong constraints on the balancing weights to ensure that the counterfactuals are based solely on interpolation. This feature, while attractive from a causal inference perspective, is sometimes too conservative and can lead to unnecessary bias due to poor covariate balance. Alternatives exist that allow for extrapolation to improve balance but existing procedures may produce negative estimates of the counterfactual outcomes and are therefore inappropriate for count data. We propose an alternative way to allow for extrapolation, although ensuring that the estimated counterfactuals remain nonnegative. Following a related proposal, we add a penalty to the balancing procedure that favors interpolation over extrapolation whenever possible. As we demonstrate theoretically and using empirical examples, our proposal can serve as a useful alternative when existing approaches yield demonstrably poor or unrealistic counterfactuals. Finally, we provide functions to implement the method in R.