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Citation |
Behrendt A, Payyappalli VM, Zhuang J. Risk Anal. 2019; 39(6): 1358-1381. |
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Affiliation |
Department of Industrial and Systems Engineering, The State University of New York at Buffalo, Buffalo, NY, USA. |
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Copyright |
(Copyright © 2019, Society for Risk Analysis, Publisher John Wiley and Sons) |
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DOI |
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PMID |
30650199 |
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Abstract |
The estimated cost of fire in the United States is about $329 billion a year, yet there are gaps in the literature to measure the effectiveness of investment and to allocate resources optimally in fire protection. This article fills these gaps by creating data-driven empirical and theoretical models to study the effectiveness of nationwide fire protection investment in reducing economic and human losses. The regression between investment and loss vulnerability shows high R2 values (≈0.93). This article also contributes to the literature by modeling strategic (national-level or state-level) resource allocation (RA) for fire protection with equity-efficiency trade-off considerations, while existing literature focuses on operational-level RA. This model and its numerical analyses provide techniques and insights to aid the strategic decision-making process. The results from this model are used to calculate fire risk scores for various geographic regions, which can be used as an indicator of fire risk. A case study of federal fire grant allocation is used to validate and show the utility of the optimal RA model. The results also identify potential underinvestment and overinvestment in fire protection in certain regions. This article presents scenarios in which the model presented outperforms the existing RA scheme, when compared in terms of the correlation of resources allocated with actual number of fire incidents. This article provides some novel insights to policymakers and analysts in fire protection and safety that would help in mitigating economic costs and saving lives. Language: en |
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Keywords |
Cost-benefit analysis; fire protection; firefighting; resource allocation; risk assessment |