Abstract
Aim: Description and justification of the stochastic model of the firefighting and rescue system in response to critical incidents.
Introduction: Recognition of reality is always associated with the cognitive construction of models, representing an analysis of events, arrangements and systems. These are created so that: • mechanisms controlling a given event, arrangement and system can be understood; • links between variables and predictions of event developments can be explored; • the impact of particular variables on the effects of this process can be established. Constructed models are not exact copies of reality, but only simplified images. For that reason they ought to be characterised by straightforwardness and cognitive simplicity, and compliance with empirical data at an acceptable research level. This article contains a proposed stochastic model of emergency response to critical incidents, based on the data accumulated by the National Fire Service database. The authors believe that the proposed model may be of use in the development of a computer programme, which could be harnessed to support decisions about the distribution of fire stations, accompanying personnel and equipment, so as to adequately address mapped critical incident risks.
Methodology: Statistical analysis and statistical modelling.
Conclusions: The proposed emergency reaction model to emerging critical incidents, based on historical data, takes into account a range of factors, which could not be incorporated in deterministic models. These include: • customised training level of rescue teams; • road network for a given area; • design of information systems; • technical parameters of equipment used by rescue teams. For the aforementioned reasons, the stochastic model is much more accurate and better describes efficiency of the rescue system in a given area. It also has a number of disadvantages: • It is labour intensive in practice; • It requires reliable historical data (Integrity of data made available for this study was somewhat weak) • Derived result depends on the assumed priori confidence level; • the result from calculations is not a specific number but a range of numbers. Despite identified drawbacks, it is considered that the use of the model is worthwhile, especially when linked to an investment appraisal of resources necessary for the creation of a firefighting rescue system. A comprehensive appraisal, taking account of outlays and derived economic outcomes, may be helpful with the reorganisation of the rescue system.
Keywords: statistical modelling, statistical analysis, examination of data
Type of article: case study