Issue 8 and Volume 12.

Take a look out the windows of your firehouse; what do you see? You see the epicenter of your first-due response area containing its infrastructure, common building types and their adjacency, population density common to the socioeconomics of the neighborhood, and all the above’s inherent risk to your fire department. It’s a lot to take in when looking at it holistically. Now ask the firefighters in your company if they see the same thing you do, the same thing your fire chief does, the same thing your elected officials do. It’s a safe bet that you’ll get varying descriptions of risk analyses, even from within your own fire department. There is even more to see, however, when you take a much deeper look into your first-due response area that you probably never even knew existed, much less thought mattered. What’s there is your first-due response area’s latitudes and longitudes, census tracts, number of housing units, median household income, number of renters, age and vintage of those buildings, age group counts, and a social vulnerability index. That’s just to name some of the things that are there every time you leave the firehouse for an emergency or detail. So, what does all this mean or actually matter to the fire department? Everything!

When developing deployment and staffing strategies for fire departments, virtually every fire department relies on National Fire Protection Association (NFPA) 1710, Standard for the Organization and Deployment of Fire Suppression Operations, Emergency Medical Operations, and Special Operations to the Public by Career Fire Departments, with regard to its standardized response metrics, with perhaps some consideration for its structural hazard categorization to determine some form of risk analysis to correlate staffing and to manage against. Furthermore, some fire departments use response times only through myriad geographic information system (GIS) analyses to see what apparatus and equipment should go where. Although both NFPA 1710 and GIS are helpful in many respects, relying on them exclusively often leads to outcomes that are a mile wide and an inch deep when considering neighborhood and community risk and vulnerability. With today’s quantum leaps in data analytics, there exist several programs that allow for innumerable inputs of metrics from fire departments and communities and, much to their credit, available, open data to paint a much clearer picture for fire department planners. These leaps notwithstanding, there is now a program developed exclusively for the fire service that paints perhaps the most vivid picture for fire departments’ risk analysis and management nationwide, one that allows fire chiefs and city administrators the ability to deploy resources to match the inherent hazards to the community: The Community Assessment Risk/Response Evaluation System, better known as FireCARES.

Quantitative Information

FireCARES is a “Big Data” analytical system that provides the necessary and quantitative information to fire service and community leaders about the response capabilities of their fire departments. Moreover, it provides the same view of the community’s risk environment in which firefighters will be operating, thereby allowing fire department planners to manage the risks to firefighters as well. FireCARES is a project funded by the Federal Emergency Management Agency’s Assistance to Firefighters Grant program. In addition, it has been developed by the same researchers, academics, and fire service professionals who conducted the National Institute of Standards and Technology (NIST) Residential Fireground and High-Rise Fireground Experiments, or NIST TN 1661 and NIST TN 1797, respectively. Further partners in the project include the International Association of Fire Fighters, the International Association of Fire Chiefs (IAFC), the Commission on Fire Accreditation, Underwriters Laboratories, the Urban Institute, the University of Texas, and Worcester Polytechnic (FireCARES, 2017). That’s a lot of firepower behind a program that also has an endorsement from the IAFC’s Metro Fire Chiefs. In other words, the fire service’s principle stakeholders are all on board with FireCARES.

FireCARES identifies a community’s risk of fire based on several major demographics such as infrastructure, built environment, population, and socio-economic risk factors, also known in the econ and data industries as social-welfare criteria (FireCARES, 2017). These are important demos to use as they give an overall, inclusive base of analytics to correlate. Simply using response times, exclusively, in planning and deployment strategies only tells you when a unit arrives, based on simple GIS analysis, but doesn’t completely portray how this metric reduces and impacts overall risk. In fact, any firefighter will tell you that it’s the numbers on the first few companies that make a difference – not how many eventually get there but having knowledge of what’s there in the first place completes a risk-benefit analysis. Regardless of staffing levels, any fire company can initiate some type of firefighting operation, but knowing the inherent risks to the responding firefighters and those occupying the structures they’re responding to becomes a much clearer portrayal of the efficacy of any fire department’s response plan. That’s what fire departments and elected officials spend so much time budgeting and developing, so why not have the most quantitative and objective variables to develop these response plans?

Community Risk Score

So how does FireCARES do this? FireCARES includes accumulation of “Big Data” to combine large sets of this data from various sources to essentially tell the story of a fire department with regard to its risk environment, resource capacity, and overall capability to respond to emergency incidents. This puts it in an easy-to-understand format that everyone can use to assist with planning and deployment, as it’s summed up as a community’s “Safe Grade.” The construct of FireCARES involves accumulation of more than a decade’s worth of National Fire Incident Reporting System (NFIRS) data. More than 40 million fires were analyzed using regressive statistical models to predict various types of risk as a function of community attributes. In addition to NFIRS data, municipal data including census tracts were used to develop the Community Risk Score part of the Safe Grade. Also using NFPA 1710’s low-, medium-, and high-hazard structure categorization as variables in the models, the risks analyzed included the following (FireCARES, 2017):

  • Number of reported structure fires.
  • Percentage of reported fires that spread beyond the room of origin.
  • Percentage of reported fires that spread beyond the room of origin and spread beyond the structure of origin (exposure fires).
  • Number of reported injuries resulting from structure fires.
  • Number of reported deaths resulting from structure fires.

NFPA 1710’s hazard categorization, as mentioned, is based on three classifications of fire buildings (Fire CARES, 2017):

  • Low hazard: one-, two-, or three-family dwellings and small business and industrial occupancies.
  • Medium hazard: apartments, offices, mercantile and industrial occupancies that may require extensive use of firefighting forces.
  • High hazard: high-rise buildings, hospitals, schools, nursing homes, explosives plants, refineries, public assembly structures, and other high-life hazard or large fire potential occupancies.

In addition to the metrics listed above, FireCARES also estimated community risk as a function of socio-demographic and the geographic characteristics of locations (census tracts) of these reported structure fires over a seven-year period of 2007-2013 using available United States Census, public health, and NFIRS data. These socio-demographic attributes include the following (FireCARES, 2017):

  • Population characteristics (size of the department, population, number of males, age group counts, race counts).
  • Housing characteristics (total housing units, total vacancies, size of home, number of renters, age of units).
  • Household characteristics (median household income, social vulnerability index).
  • Geographic region.

Fire Department Performance Score

This analysis of community risk is only one-half of the equation of a community’s Safe Grade. The Safe Grade is a comparison of the above Community Risk Score and a department’s actual Fire Department Performance Score. The second component of the Safe Grade, the Fire Department Performance Score, is the model that defines how the fire department would perform if it were acting as a standard, idealized version of itself. In other words, if a fire department would meet or exceed NFPA 1710’s turnout time, response time, etc., in addition to some of the performance standard metrics developed during NIST’s Fireground Experiments (NIST TN 1661 and NIST TN 1797), it would be considered “ideal” as meeting consensus and national performance standards. Although it is very difficult for fire departments to meet all the above, it must be something for which fire department administrators and elected officials strive; otherwise, what are we doing for our communities and ourselves?

(Image by FireCARES.)

Obviously, a fire department is required to initiate operations on its arrival, so FireCARES opted to use the task-time data from the NIST’s Fireground, data that are also currently being used by the National Fire Operating Reporting System, another great platform to accumulate important metrics, in conjunction with available NFIRS data. These metrics have been validated by FireCARES’ aforementioned stakeholders, so there is validity and objectivity in their use as part of a Performance Score. These metrics include the following (FireCARES, 2017):

  • Time to alarm: time required before the fire is noticed and some form of action is taken.
  • Time to dispatch: time required for the dispatch operator to obtain enough information regarding the fire and location to issue a dispatch.
  • Time to turnout: time required for donning personal protective equipment and turn out of quarters.
  • Time to arrival: transit time for the apparatus between the station and the fire location.
  • Time to ascend: transit time required for firefighters to ascend to the staging floor for fires in buildings. This metric is only included if staging would occur above ground level.
  • Time to suppress: time required for firefighters on scene to put water on the fire (size-up, hose connection, etc.).

Once water has been started on a fire, the Performance Score assumes the fire has reached its peak size or is fully involved, for purposes of the score. Using these data described above, comparison takes place comparing the performance score to the community’s set of risk scores previously discussed. From this comparison, a Safe Grade is calculated based on how resources are deployed to match the actual level of risk within the community.

Safe Grade

There are three Safe Grade comparison categories that are analyzed (FireCARES 2017):

  • Performance based on number of fires.
  • Performance based on fire spread.
  • Performance based on injury and death.

When analyzing the distribution of fire spread, FireCARES developed a metric that uses the American Housing Survey (AHS) national survey of residential homes to model fire area damage at suppression time. This allows a metric to be developed that takes this time-to-suppression and fire area damage and correlates it to proper room and building size using the AHS criteria. Using the above three Safe Grade comparison categories, the Performance Score metric is then used to determine the “correction” between the ideal fire department’s score and the one being analyzed or, rather, the difference between your fire department one and the “ideal” one. This difference between the two becomes the Performance Score that your fire department is given. These are portrayed in their comparative and analytical form as low-, medium-, and high-risk scores (FireCARES, 2017).

There are five safe grading criteria used. Three of these compare a fire department against similar departments (comparables) while the other two compare the individual fire department against the national level (all fire departments that have the same risk score). These scores are based on the low-, medium-, and high-risk groups in the community. For instance, if a fire department has a low-risk score, it is placed in rank order of its Performance Score against all similar or “like” departments that also have a low-risk score. Finally, a complete Safe Grade is established and places fire departments into three obvious and common group typings with which to compare and plan against to determine if the fire department deploys the proper resources that match the inherent risk (FireCARES, 2017). The three groups include the following:

  • Good: Less than 25 percent of fire departments have an equal or better Performance Score.
  • Fair: 25-75 percent of fire departments have a better Performance Score.
  • Poor: More than 75 percent of fire departments have an equal or better Performance Score.

The Next Step

So, you’ve analyzed the community risk, determined your fire department’s performance, and obtained your Safe Grade. The next step is to ensure that there is a plan in place to update your fire department’s and municipality’s data. Station location changes, increases or decreases in population, changes to a fire station’s response area (first-due area), and improvements or reduction in infrastructure should be routine inputs into FireCARES. FireCARES has great mechanisms in place to ensure that future data submitted will be used and incorporated into your fire department’s Safe Grade. Without clean data and proper input, any system will provide inaccurate outcomes. It is only fair to give the citizenry, elected officials, and firefighters the most accurate scoring in FireCARES so this, like any data system, is the most important piece. If the data are correct, so too will be the Safe Grade. The responsibility is on fire service leaders to log in and check your data, see if your jurisdiction border is correct, see if your station list is correct, and load your data in the station apparatus/staffing tables. Moreover, FireCARES staff can add any GIS data layer to further assist fire departments in geospatially plotting things including community risk reduction contacts, building inspections, hydrant locations, poor street conditions (potholes, etc.), and vacant buildings. All FireCARES needs is the proper files and lats and longs, and it will do the rest.

(Image by FireCARES.)

Now that fire departments have the best system at their fingertips, the goal should be to use FireCARES in your fire department’s deployment planning and strategy. The user can also dig down into individual fire stations’ response areas (using geographic boundaries, polygons, etc.) and see the response times and community risk in said areas. A fire station’s apparatus and staffing are also displayed so that elected officials, unions, and fire chiefs can see what resources are required in that station’s area on the same platform that everyone can understand and analyze. This is something that the fire service has struggled with, as many cities conduct analyses on myriad platforms with little to no interface for the data they have at their fingertips, with some of it being open data that already have accumulated for the general public, academics, and analysts to grab at any time. FireCARES offers a simple solution to this using complex algorithms to allow an easy-to-navigate and intuitive system that decision makers will be glad to have. No longer do fire chiefs have to explain why the fire department is important to the community; instead, they can explain how important the fire department is and how capable it is at meeting the risks citizens rely on them to handle safely and effectively. To put it simply, FireCARES becomes the “fair shake” for which fire departments and communities have been waiting.


FireCARES (2017). www.firecares.org.

Statements from FireCARES team/project partners:

Statements from industry leaders: