Abstract
A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.
Highlights
In order to improve a centralized and opportune emergency response [1], Ecuador created in 2012 the integrated security service, named ECU-911 [2]
In order to reach a better understanding of the existing qualitative information, we propose here a method that, while maintaining its simplicity, allows us to obtain statistically meaningful results and to support the managers to inspect the emergencies attended by First Response Institutions (FRIs), through the analysis of the reports routinely stored in the public safety answering point (PSAP) Data Base (DB)
We propose the use of multiple correspondence analysis (MCA) applied to FRIs, emergencies, and categories that are recorded in the emergency forms, in order to find out the possible relations among them with an easy-to-handle, yet statistically rigorous system
Summary
In order to improve a centralized and opportune emergency response [1], Ecuador created in 2012 the integrated security service, named ECU-911 [2]. In order to reach a better understanding of the existing qualitative information, we propose here a method that, while maintaining its simplicity, allows us to obtain statistically meaningful results and to support the managers to inspect the emergencies attended by FRIs, through the analysis of the reports routinely stored in the PSAP DB. A precedent of this type of principled analysis was proposed in our previous contribution in [12], which allowed to systematically obtain statistical, temporal, and spatial information for emergency events. Note that the proposal in [12] for statistical, spatial, and temporal analysis of emergency responses is extended here by making use of multiple correspondence analysis, to complete our knowledge and to figure out relationships among events, besides their spatio-temporal performance.
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