Statistical, Spatial and Temporal Mapping of 911 Emergencies in Ecuador

Abstract

A public safety answering point (PSAP) receives alerts and attends to emergencies that occur in its responsibility area. The analysis of the events related to a PSAP can give us relevant information in order to manage them and to improve the performance of the first response institutions (FRIs) associated to every PSAP. However, current emergency systems are growing dramatically in terms of information heterogeneity and the volume of attended requests. In this work, we propose a system for statistical, spatial, and temporal analysis of incidences registered in a PSAP by using simple, yet robust and compact, event representations. The selected and designed temporal analysis tools include seasonal representations and nonparametric confidence intervals (CIs), which dissociate the main seasonal components and the transients. The spatial analysis tools include a straightforward event location over Google Maps and the detection of heat zones by means of bidimensional geographic Parzen windows with automatic width control in terms of the scales and the number of events in the region of interest. Finally, statistical representations are used for jointly analyzing temporal and spatial data in terms of the "time-space slices". We analyzed the total number of emergencies that were attended during 2014 by seven FRIs articulated in a PSAP at the Ecuadorian 911 Integrated Security Service. Characteristic weekly patterns were observed in institutions such as the police, health, and transit services, whereas annual patterns were observed in firefighter events. Spatial and spatiotemporal analysis showed some expected patterns together with nontrivial differences among different services, to be taken into account for resource management. The proposed analysis allows for a flexible analysis by combining statistical, spatial and temporal information, and it provides 911 service managers with useful and operative information.

Multiple Correspondence Analysis of Emergencies Attended by Integrated Security Services

“…In the previous equations, b indicates the number of resamples that we are building. After resample b is built, a Bootstrap replication can be built for the statistical distribution of any of the described statistical elements [12,17]. The resampling and replication processes are repeated B times (typically B = 50, 100, 200, or 500 times), which provides an estimation of the empirical distribution function of the statistical element.…”

“…From the seven FRIs coordinated by our PSAP, we considered its participation percentage as shown in Table 4, the information detailed in Table 3, and the results of temporal analysis described in [12]. This allowed us to divide the institutions into two groups.…”

“…This work points to the possibility of emergency event detection based on outlier detection. In the same direction, [12] proposed a statistical, spatial, and temporal analysis of emergency responses by using simple, yet robust and compact, event representations.…”

“…By applying Multiple Correspondence Analysis (MCA) techniques to the FRIs considered as grouping variables, and to the emergencies attended as categories, we hypothesize here that we can obtain even an improved statistical description if we combine them with bootstrap resampling techniques and Parzen windowing. 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. In this setting, we now obtain relevant information, its statistical significance, and intuitive 3D representations of the trends and relationships of the information taken from the DB, which is compatible with a rigorous statistical background and description of the characteristics of the events.…”

“…Our analysis paid attention to different FRIs, either individually or jointly considered, and to a comprehensive set including most of the relevant emergency categories in the ECU-911 DB that were stored during 2014. Note that the proposal in [12] for statistical, spatial, and temporal analysis of emergency responses is then 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.…”