# Multiple Correspondence Analysis of Emergencies Attended by Integrated Security Services
## 4 Emergency DB  
In this research, we used information from the DB of events occurred during 2014 in the city of Quito attended by the ECU-911 service, consisting of 1,078,846 emergencies distributed in time as shown in Table 1. The DB is composed of 121 fields with entries provided during the emergency attention process. To better group this information, we considered two types of variables according to their kind of information. First, operative information refers to the emergency details like alert mechanism, the identity of involved persons, type of emergency, locations, time, date, province, moved resources, or contacted PSAPs, among others. On the other hand, control information is used for internal control and quality of service (QoS) purposes inside the Integrated Security Services or in the respective Institution. Here we can find internal codes, times of transfer, assigned dispatch, time of arrival to the event, time of emergency close, a summary of used resources, and others. In our case, the variables are the First Response Institutions (FRIs), namely, Fire Brigades (FB), Risk Management Secretary (RMS), Military (M), Police (P), Health Services (HS), Municipal Services (MS), and Transit (T). Their categories are given by any of the 127 possible events attended by FRIs along time. Table 3 shows the categories when ordered according to their percentage of occurrence. Note at this point that the Categories (C) are given here by the specific type of emergencies attended by each FRI, for instance, fire brigades has 15 categories, as can be observed in Table 2.  
We applied a data prepossessing stage to filter the valid data before applying MCA. One should note that an event could be reported for more than one alert call, in other words, several institutions could be required to be dispatched in order to attend a specific emergency. Table 4 shows the participation of emergencies attended by each FRI during 2014. Police had a higher participation percentage, followed by Health Services and Transit, Fire Brigades comes next, and with significantly lower participation, they are followed by Municipal Services, Military, and Risk Management Secretary.  
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. The first group, with four FRIs and 95% of the emergencies registered, included Police (45 event categories), Health Services (41), Transit (13), and Fire Brigades (3). The second group, with three FRIs representing 5% of the events, included Municipal Services (8), Military (2), and Risk Management Secretary (3). Starting from this taxonomy, we analyzed the relationships inside each FRI, among institutions, and among categories.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Order** & **Month** & **Emergencies** \\ \hline
1 & January & 74,358 \\
2 & February & 70,010 \\
3 & March & 88,119 \\
4 & April & 86,192 \\
5 & May & 91,265 \\
6 & June & 84,627 \\
7 & July & 89,300 \\
8 & August & 98,531 \\
9 & September & 99,878 \\
10 & October & 94,322 \\
11 & November & 93,897 \\
12 & December & 108,347 \\ \hline  & **Total** & **1,078,846** \\ \hline \hline \end{tabular}
\end{table}
Table 1: Emergencies attended by the Public Safety Answering Point (PSAP) of Quito in 2014.  
It is important to note that 94 categories had participation below 1% of the total number of the studied events, and some of these categories did not register any event. The information presented in Table 3 allows us to set a percentage of occurrence in order to scrutinize only the representative categories for each case.