Data Sources and National Estimates 

Methodology Overview for the 

U.S. Fire Administration’s Topical Fire 

Report Series (Volume 20)

August 2019

Mission Statement

We support and strengthen fi re and Emergency Medical 

Services and stakeholders to prepare for, prevent, mitigate 

and respond to all hazards.

Data Sources and National Estimates 

Methodology Overview for the

U.S. Fire Administration’s Topical Fire 

Report Series (Volume 20)

National Fire Data Center

U.S. Fire Administration

August 2019

Table of Contents i

Table of Contents

Background .......................................................................................................................... 1

Data Sources ........................................................................................................................ 1

National Fire Incident Reporting System .................................................................. 1

National Fire Protection Association survey estimates .......................................... 2

National Estimates Overview ............................................................................................ 3

Structures versus buildings in the National Fire Incident Reporting System ...... 4

Residential buildings .................................................................................................... 4

Nonresidential buildings.............................................................................................. 5

National estimates of building fires and losses ....................................................... 6

National Fire Incident Reporting System Data Used in U.S. Fire Administration 

Analyses ......................................................................................................................... 7

Data Quality ......................................................................................................................... 9

Unknown Data Entries and Missing Values ..................................................................... 9

Incomplete Loss Reporting ................................................................................................ 11

Identifying Large Outliers .................................................................................................. 12

National Fire Incident Reporting System Analytic Resources....................................... 12

Resources ............................................................................................................................. 13
ii Data Sources and National Estimates Methodology Overview
Background / Data Sources 1

Background

The topical reports produced as part of the U.S. Fire Administration’s (USFA’s) Topical 

Fire Report Series explore facets of the fire problem in the U.S. as depicted through data 

collected in the USFA’s National Fire Incident Reporting System (NFIRS). Each topical 

report briefly addresses the nature of the specific fire or fire-related topic, highlights 

important findings from the data, and may suggest other resources to consider for further 

information. The national estimates presented in the topical reports are based on data 

from the NFIRS and the National Fire Protection Association’s (NFPA’s) annual Survey of 

Fire Departments for U.S. Fire Experience.

This document addresses national estimates, as well as the data sources used to derive 

the estimates, with an emphasis on the specific NFIRS data elements analyzed in the 

topical reports. NFIRS data quality, including “unknown” data entries and missing data 

values, is also discussed. Because the majority of the USFA’s topical reports address fires 

and losses in buildings, this overview focuses on buildings.

Data sources

National Fire Incident Reporting System

The NFIRS is the world’s largest collection of data for incidents to which fire departments 

respond. About 1.2 million fire incident records and 26.5 million nonfire incident records 

were added to the database in 2017.1 In 2017, the most recent year for available data, 

21,246 fire departments reported fire incidents to the NFIRS. Across participating entities, 

71% of U.S. fire departments reported fire incidents to the NFIRS in 2017.2 With at least 

two-thirds of all fire departments nationwide reporting fire incidents to the NFIRS, the 

reporting departments represent a very large dataset that enables the USFA to develop 

reasonable estimates of various aspects of the fire problem. Although some states do 

require their departments to participate in the state system, participation in the NFIRS is 

voluntary. Furthermore, if a fire department is a recipient of a Fire Act Grant, participation 

is required.3 For the years 2015 to 2017, NFIRS data were submitted by all 50 states, the 

District of Columbia and the Native American Tribal Authorities. It is important to note 

that not all fire departments within participating states report to the NFIRS.

Because the NFIRS incident reports are submitted voluntarily, the data do not represent a 

statistically selected sample. Additionally, NFIRS data are not stand-alone. Therefore, the 

USFA currently scales up raw NFIRS data or percentages to the NFPA’s annual national survey 

estimates. This approach is discussed further in the National Estimates Overview section.

1

U.S. Fire Administration (USFA), National Fire Incident Reporting System (NFIRS), https://www.usfa.fema.gov/

data/nfirs/about/index.html. 2For 2017, the National Fire Protection Association (NFPA) estimated that there were 29,819 fire departments 

in the U.S. Source: NFPA, U.S. Fire Department Profile 2017, https://www.nfpa.org/News-and-Research/Dataresearch-and-tools/Emergency-Responders/US-fire-department-profile, March 2019. 3From the fiscal year (FY) 2017 Assistance to Firefighters Grant (AFG) Notice of Funding Opportunity (NOFO) — 

while NFIRS reporting is strongly encouraged, NFIRS reporting is not a requirement to apply for or be awarded a 

grant within the AFG Program. However, fire departments that receive funding under this program must agree 

to provide information to the NFIRS for the period covered by the assistance. If a recipient does not currently 

participate in the NFIRS and does not have the capacity to report at the time of the award, that recipient must 

agree to provide information to the system for a 12-month period commencing as soon as possible after it 

develops the capacity to report. Capacity to report to the NFIRS must be established prior to the termination 

of the one-year performance period. In order to be compliant and close out the grant, the grantee may be 

asked by the Federal Emergency Management Agency to provide proof of compliance in reporting to the NFIRS. 

Any grantee that stops reporting to the NFIRS during the grant’s period of performance is subject to having 

the award(s) modified or withdrawn. See the FY 2017 AFG NOFO at https://www.fema.gov/media-librarydata/1515081517499-e26f234398e048e897410250055c916e/NOFO1.3.18.pdf.
2 Data Sources and National Estimates Methodology Overview

National Fire Protection Association survey estimates

The NFPA’s Survey of Fire Departments for U.S. Fire Experience is based on a stratified 

random sample of U.S. fire departments.4

 The sample of departments is stratified by size 

of community protected, and ratio estimation methodology is used to develop nationallevel summary estimates on fire-loss statistics (the total numbers of reported fires, fire 

deaths, fire injuries and direct dollar loss), as well as summary estimates of fires and losses 

by major incident types (i.e., structure, vehicle, outside and other).

The 2015 to 2017 NFPA estimates of residential structure fires and losses used to develop 

the USFA’s national estimates of residential building fires are presented in Table 1. From 

2015 to 2017, the NFPA survey produced an annual average estimate of 379,500 residential 

structure fires, resulting in 2,705 civilian fire deaths, 11,200 civilian fire injuries and $7.5 

billion in property damage each year.5 Of these NFPA residential structure fire and loss 

estimates, 70% of fires, 58% of deaths, 59% of injuries and 64% of dollar losses were 

reported to the NFIRS during this three-year period.

Table 1. NFPA estimates of residential structure fires and losses (2015-2017)

Year Residential 

structure fires

Residential 

structure fire 

deaths

Residential 

structure fire 

injuries

Residential 

structure fire 

dollar loss

(in millions)

2015 388,000 2,605 11,575 7,210

2016 371,500 2,800 11,125 7,421

2017 379,000 2,710 10,910 7,900

Source: NFPA, “Fire Loss in the United States,” 2015 to 2017.

The 2015 to 2017 NFPA estimates of nonresidential structure fires and losses used to 

develop the USFA’s national estimates of nonresidential building fires are presented in 

Table 2. From 2015 to 2017, the NFPA survey produced an annual average estimate of 

112,500 nonresidential structure fires, resulting in 110 civilian fire deaths, 1,450 civilian fire 

injuries and $3.0 billion in property damage.6 Of these NFPA nonresidential structure fire 

and loss estimates, 68% of fires, 70% of deaths, 46% of injuries and 90% of dollar losses 

were reported to the NFIRS during this three-year period.

Table 2. NFPA estimates of nonresidential structure fires and losses (2015-2017)

Year Nonresidential 

structure fires

Nonresidential 

structure fire 

deaths

Nonresidential 

structure fire 

injuries

Nonresidential 

structure fire 

dollar loss

(in millions)

2015 113,500 80 1,425 3,070

2016 104,000 150 1,650 2,979

2017 120,000 105 1,250 2,800

Source: NFPA, “Fire Loss in the United States,” 2015 to 2017.

4For detailed information regarding the NFPA’s survey methodology, see the NFPA’s report “Fire Loss in the 

United States During 2017,” September 2018, http://www.nfpa.org/news-and-research/fire-statistics-andreports/fire-statistics/fires-in-the-us/overall-fire-problem/fire-loss-in-the-united-states. 5Fires are rounded to the nearest 100, deaths to the nearest five, injuries to the nearest 25, and dollar loss to 

the nearest 100 million. Note: The NFPA revised their dollar loss estimates for 2016, https://www.nfpa.org/-/

media/Files/News-and-Research/Fire-statistics-and-reports/Errata/ErrataFireLoss2016.ashx?la=en (Errata 

No.: FLX10-September 2017_01).

6Fires are rounded to the nearest 100, deaths to the nearest five, injuries to the nearest 25, and dollar loss to 

the nearest 100 million. Note: The NFPA revised their 2016 dollar loss estimates for 2016, https://www.nfpa.

org/-/media/Files/News-and-Research/Fire-statistics-and-reports/Errata/ErrataFireLoss2016.ashx?la=en

(Errata No.: FLX10-September 2017_01).
National Estimates Overview 3

National Estimates Overview

National estimates presented in the USFA’s Topical Fire Report Series (Volume 20) are 

based on NFIRS data from 2015 to 2017, the NFPA’s annual surveys of structure fire-loss 

estimates from 2015 to 2017, and the USFA’s building fire-loss estimates from 2015 to 2017.

Overall estimates of the fire problem come from the NFPA’s annual Survey of Fire 

Departments for U.S. Fire Experience.7 As previously noted, this survey produces nationallevel summary estimates on fire-loss statistics (the total numbers of reported fires, fire 

deaths, fire injuries and direct dollar loss), as well as summary estimates of fires and 

losses by major incident types (i.e., structure, vehicle, outside and other). The summary 

estimates by major incident type are further broken down to the next tier (e.g., residential 

structures, highway vehicles and the like). The raw NFPA survey data are not available to 

the public, the USFA or various other national fire data analysts.

All nationally based estimates on subsets of fire data are derived by scaling up the raw NFIRS 

data. These estimates are based on a method of apportioning the NFPA estimates for total 

fires and structure, vehicle, outside and other fires.8 Generally, these national estimates 

are derived by computing a percentage of fires, deaths, injuries or dollar loss in a particular 

NFIRS category and multiplying it by the corresponding total estimate from the NFPA annual 

survey.9 This methodology is the accepted practice of national fire data analysts.

One problem with this approach is that the proportions of fires and fire losses differ 

between the large NFIRS dataset and the NFPA survey sample.10 Nonetheless, to be 

consistent with approaches being used by other fire data analysts, the NFPA estimates 

of fires, deaths, injuries and dollar loss are used as a starting point. The details of the 

fire problem below this level are based on proportions from the NFIRS. Because the 

proportions of fires and fire losses differ between the NFIRS and the NFPA estimates, from 

time to time, this approach leads to inconsistencies. These inconsistencies will remain until 

all estimates can be derived directly from NFIRS data.

Ideally, one would like to have all of the data come from one consistent data source — the 

NFIRS. One of the critical pieces of data necessary to do so is missing: the overall population 

protected by all reporting fire departments. This “residential population protected” is not 

reported to the NFIRS, nor is the data easy to come by, especially where a county or other 

jurisdiction is served by several fire departments that each report their fires independently.

Other issues (such as full reporting because of reporting deadlines, data access and 

budgetary considerations) add a layer of complexity to using the NFIRS data to create 

7For detailed information regarding the NFPA’s survey methodology, see the NFPA’s report “Fire Loss in the 

United States During 2017,” September 2018, http://www.nfpa.org/news-and-research/fire-statistics-andreports/fire-statistics/fires-in-the-us/overall-fire-problem/fire-loss-in-the-united-states.

8The foundation of computing national estimates is based on “The National Estimates Approach to U.S. Fire 

Statistics” by Hall, J.R. and Harwood, B., https://www.nfpa.org/-/media/Files/News-and-Research/Fire-statisticsand-reports/NFPA-estimates-and-methodology/NationalEstimatesApproach.pdf.

9The NFPA summary estimates are used for the overall U.S. fire losses; fire losses from structure, vehicle, outside 

and other fires; and as the basis for the USFA’s estimates of residential and nonresidential building fires and 

losses. The alternative approach for these summary numbers is to use the relative percentage of fires (or other 

loss measures) from the NFIRS and scale up (multiply by) to the NFPA estimate of total fires.

10For additional information regarding the differences in proportions of fires and losses between NFIRS data 

and the NFPA survey, see the section titled “Differences between the National Fire Incident Reporting System 

data and the National Fire Protection Association survey data” in USFA’s “Fire in the United States 2006-2015,” 

19th edition, December 2017, https://www.usfa.fema.gov/downloads/pdf/publications/fius19th.pdf.
4 Data Sources and National Estimates Methodology Overview

estimates. Nonetheless, with such a large wealth of fire-incident data, the USFA believes 

it is possible to harness NFIRS data to produce national estimates of the U.S. fire problem.

Through the years, a number of ad hoc studies have been undertaken to identify NFIRS 

representativeness — none of which have identified major reporting issues. Most NFIRS 

data exhibit stability from one year to the next without radical changes. Results based on 

the full dataset are generally similar to those based on part of the data, another indication 

of data reliability. In short, the NFIRS data are a very large and reasonably stable dataset 

that is used as input to develop national estimates.

Structures versus buildings in the National Fire Incident Reporting 

System

The NFIRS allows for the differentiation between buildings and nonbuildings. In the NFIRS, a 

structure is a built object and can include nonbuildings, such as platforms, tents, connective 

structures (e.g., bridges, fences, telephone poles), and various other structures, in addition 

to buildings. Analyses of 2015 to 2017 NFIRS structure fire data show that, by and large, the 

majority (97%) of structure fires occurred in buildings.

The distinction between buildings and nonbuildings is particularly important when 

determining the effectiveness of nonbehavior-based fire safety mechanisms, such as 

smoke alarms and residential sprinklers. These important components of early fire 

detection apply to buildings and not necessarily to these other types of structures. To 

facilitate analysis of these components and to acknowledge that prevention efforts 

are generally centered on buildings, the USFA separates buildings from the rest of the 

structures. For these reasons, the USFA focuses on producing building fire and loss 

estimates separately for residential and nonresidential buildings.

Residential buildings

Table 3 shows the raw numbers of residential building fires and losses reported to the 

NFIRS from 2015 to 2017.

Table 3. Residential building fires and losses reported to the NFIRS (2015-2017)

Year Residential 

building fires

Residential 

building fire 

deaths

Residential 

building fire 

injuries

Residential 

building fire 

dollar loss

(in millions)

2015 264,531 1,495 6,803 4,548

2016 264,860 1,607 6,533 4,825

2017 257,536 1,593 6,390 4,806

Source: USFA, 2015 to 2017 NFIRS.
National Estimates Overview 5

Table 4 shows the raw numbers of residential structure fires and losses reported to the 

NFIRS from 2015 to 2017. On average, from 2015 to 2017, 98% of residential structure fires, 

99% of associated deaths, 99% of injuries and 99% of dollar losses reported to the NFIRS 

occurred in residential buildings.

Table 4. Residential structure fires and losses reported to the NFIRS (2015-2017)

Year Residential 

structure fires

Residential 

structure fire 

deaths

Residential 

structure fire 

injuries

Residential 

structure fire 

dollar loss

(in millions)

2015 269,449 1,517 6,866 4,619

2016 270,104 1,621 6,591 4,891

2017 262,759 1,601 6,436 4,870

Source: USFA, 2015 to 2017 NFIRS.

Nonresidential buildings

Table 5 shows the raw numbers of nonresidential building fires and losses reported to 

the NFIRS from 2015 to 2017.

Table 5. Nonresidential building fires and losses reported to the NFIRS (2015-2017)

Year Nonresidential 

building fires

Nonresidential 

building fire 

deaths

Nonresidential 

building fire 

injuries

Nonresidential 

building fire 

dollar loss

(in millions)

2015 68,706 50 587 2,249

2016 71,800 109 610 2,204

2017 73,340 62 666 3,010

Source: USFA, 2015 to 2017 NFIRS.

Table 6 shows the raw numbers of nonresidential structure fires and losses reported to 

the NFIRS from 2015 to 2017. On average, 93% of nonresidential structure fires, 94% of 

deaths, 94% of injuries and 94% of dollar losses reported to the NFIRS from 2015 to 2017 

occurred in nonresidential buildings.

Table 6. Nonresidential structure fires and losses reported to the NFIRS (2015-2017)

Year Nonresidential 

structure fires

Nonresidential 

structure fire 

deaths

Nonresidential 

structure fire 

injuries

Nonresidential 

structure fire 

dollar loss

(in millions)

2015 74,528 56 636 2,566

2016 77,173 111 650 2,306

2017 79,290 68 688 3,099

Source: USFA, 2015 to 2017 NFIRS.
6 Data Sources and National Estimates Methodology Overview

National estimates of building fires and losses

Based on the raw numbers of building fires and structure fires reported to the 

NFIRS, along with the NFPA survey estimates of structure fires, the USFA developed a 

methodology for computing national estimates of residential and nonresidential building 

fires and losses.11 The USFA uses these national building fire estimates in the Topical 

Fire Report Series, Fire Estimate Summary Series and various other fire data reports.12

Tables 7 and 8 present the USFA’s national estimates of fires and losses for residential 

and nonresidential buildings, respectively.

Table 7. USFA’s national estimates of residential building fires and losses 

(2015-2017)

Year Residential 

building fires

Residential 

building fire 

deaths

Residential 

building fire 

injuries

Residential 

building fire 

dollar loss — 

adjusted to 

2017 dollars

(in millions)

2015 380,900 2,565 11,475 7,342

2016 364,300 2,775 11,025 7,478

2017 371,500 2,695 10,825 7,797

Source: USFA, Fire Estimate Summary Series (2008 to 2017).

Table 8. USFA’s national estimates of nonresidential building fires and losses 

(2015-2017)

Year Nonresidential 

building fires

Nonresidential 

building fire 

deaths

Nonresidential 

building fire 

injuries

Nonresidential 

building fire 

dollar loss — 

adjusted to 

2017 dollars

(in millions)

2015 104,600 70 1,325 2,783

2016 96,800 145 1,550 2,908

2017 111,000 95 1,200 2,719

Source: USFA, Fire Estimate Summary Series (2008 to 2017).

11The USFA’s methodology for computing national estimates of residential and nonresidential building fires and 

losses is detailed in the USFA’s “National Estimates Methodology for Building Fires and Losses,” August 2012, 

https://www.usfa.fema.gov/downloads/pdf/statistics/national_estimate_methodology.pdf. 12The USFA’s Fire Estimate Summary Series, as well as 2003 to 2017 national estimates of residential and 

nonresidential building fires and losses, are published at https://www.usfa.fema.gov/data/statistics/. The USFA’s 

Topical Fire Report Series and various other fire data reports are available at https://www.usfa.fema.gov/data/

statistics/reports/. Note: The 2016 dollar loss estimates for residential and nonresidential buildings used in this 

document were revised based on an updated release of 2016 NFPA dollar loss estimates (NFPA Errata No.: FLX10-

September 2017_01) and do not match those published in the 2008-2017 Fire Estimate Summary Series for 2016.
National Fire Incident Reporting System Data Used in U.S. Fire Administration Analyses 7

National Fire Incident Reporting 

System Data Used in U.S. Fire 

Administration Analyses

Although the NFIRS contains hundreds of data elements, only a few are used in producing 

the USFA’s topical reports. Most of these data elements are required to be completed for 

each fire incident type; however, for small, confined fires (i.e., Incident Types 113 to 118), 

outside rubbish fires with no value (i.e., Incident Types 150 to 155), and other unclassified 

fires, certain data elements are not required to be completed.

A complete list of NFIRS data elements is documented in the “National Fire Incident 

Reporting System Complete Reference Guide.”13 Table 9 identifies the NFIRS data elements 

that are used most often in fire data analyses in the topical reports produced by the USFA.

Table 9. NFIRS data elements used in USFA analyses

Data element Description

Required data 

element

for all fires

Incident Type The actual situation found on-scene 

when emergency personnel arrived. Yes

Property Use

The actual use of the property where 

the incident occurred, not the overall use 

of mixed-use properties of which the 

property is a part.

Yes

Incident Date The month, day and year of the incident. Yes

Alarm Time

The actual month, day, year and time of 

day (hour, minute and seconds) when 

the alarm was received by the fire 

department.

Yes

Death

A civilian fire death resulting from 

the incident or occurring during the 

mitigation of the incident (includes 

emergency personnel who are not part 

of the fire department, such as police 

officers or utility workers).

Yes

Injury

A civilian fire injury resulting from 

the incident or occurring during the 

mitigation of the incident (includes 

emergency personnel who are not part 

of the fire department, such as police 

officers or utility workers).

Yes

Dollar Loss The sum of the total property and 

contents dollar losses. Yes

13“National Fire Incident Reporting System Complete Reference Guide,” USFA, January 2015, https://www.usfa.

fema.gov/downloads/pdf/nfirs/NFIRS_Complete_Reference_Guide_2015.pdf.
8 Data Sources and National Estimates Methodology Overview

Table 9. NFIRS data elements used in USFA analyses — continued

Data element Description

Required data 

element

for all fires

Fire Spread14 The extent of fire spread in terms of how 

far the flame damage extended. No

Area of Fire Origin The primary use of the area where the 

fire started within the property. No

Heat Source The source of heat that ignited the “item 

first ignited” to cause the fire. No

Item First Ignited

The use or configuration of the item or 

material first ignited by the heat source. 

The item that had sufficient volume or 

heat intensity to extend to uncontrolled 

or self-perpetuating fire.

No

Factors Contributing to 

Ignition

The contributing factors that allowed the 

heat source and combustible material to 

combine to ignite the fire.

No

Presence of Detectors The existence of fire-detection equipment 

within its designed range of the fire. No

Presence of Automatic 

Extinguishing System (AES)

The existence of an AES within the AES’s 

designed range of a fire. No

Source: “National Fire Incident Reporting System Complete Reference Guide,” USFA, January 2015.

In addition to the data elements presented in Table 9, “fire cause” is a data characteristic 

included in almost every USFA topical report analysis; however, it is not directly collected 

in the NFIRS. Fire cause is determined for all structure fires based on an algorithm using 

cause-related data elements from the NFIRS, such as the heat source, item first ignited, 

cause of ignition, factors contributing to ignition, and equipment involved in ignition. Fire 

causes are often a complex chain of events. To make it easier to grasp the “big picture,” 

16 midlevel categories of fire causes, such as heating, cooking and electrical malfunction, 

are used by the USFA to define structure fire causes.

Structure fires are assigned to one of the 16 midlevel cause groupings using a hierarchy 

of definitions. A fire is included in the highest category into which it fits on the list. If it 

does not fit the top category, then the second one is considered; and if not that one, the 

third; and so on. Once a match is found, the cause is assigned, and no further checking of 

subsequent categories is done in the matrix. If no match is found, the incident is assigned 

a fire cause of “unknown.”15

14Fire spread is not a required data element for all fires. Although not required for confined fires (i.e., Incident 

Types 113 to 118), the confined fire Incident Types were designed to reflect small, low-loss fires, typically with 

a fire spread that is limited to the object of fire origin. In addition, fire spread is only a required element in the 

fire module when the Structure Type is coded as an enclosed building or fixed portable or mobile structure. 

Therefore, when analyzing NFIRS building fire data only, fire spread is either required or could be inferred for 

confined fires, and essentially it contains no missing data values.

15The USFA’s detailed structure fire cause methodology and definitions are available in the document “National 

Fire Incident Reporting System Version 5.0 Fire Data Analysis Guidelines and Issues,” July 2011, https://www.

usfa.fema.gov/downloads/pdf/nfirs/nfirs_data_analysis_guidelines_issues.pdf.
Data Quality / Unknown Data Entries and Missing Values 9

Data Quality

Data quality is an area of great importance. The following three criteria are used in 

monitoring data in the NFIRS during the year: the data are complete, the data are accurate, 

and the data are current. These criteria are monitored by creating reports from the 

database that show the number of reporting fire departments, the number of incidents 

by state, the number of invalid incidents and the number of unreleased incidents. The 

USFA provides the reports to the state NFIRS program managers and works with them 

to resolve any data issues. Technical assistance (e.g., telephone support or site visits) is 

provided to states to help address any data quality and data reporting needs.

Audits of the data are performed during the year to identify any inconsistencies. The 

audits focus on three criteria: gaps in reporting, critical errors in the data and outliers in 

the data. In particular, the USFA works closely with states to monitor the quality of data 

coming from third-party vendor software. The USFA assists states in monitoring vendor 

data quality issues or contacts vendors directly to discuss an issue at a state’s request. 

Other data quality issues are questionable, high dollar-loss incidents and a questionable, 

high number of fire deaths. Annually, USFA staff query the database for questionable 

values (i.e., outliers) and verify the values with state- and local-level NFIRS program 

managers. The data quality steps are important to ensure that the data meet the USFA’s 

three criteria before the data are released in the NFIRS Public Data Release format.

The USFA published the report “Review and Assessment of Data Quality in the National Fire 

Incident Reporting System” (May 2017). This document covers a review of the system, the 

many robust data quality checks and mechanisms which are an integral part of the NFIRS, 

and an assessment of the data quality both at the state level and at the data element level. 

The data element assessment focuses on the most common data elements used in NFIRS 

data analyses. NFIRS data were reviewed from the three most recent years available at the 

time of the report’s development (2009 to 2011). Additionally, the report includes a section 

drawn from published NFPA documents covering the NFPA survey methodology.16

Unknown entries, incomplete loss reporting and unreported fires are also important 

considerations when assessing NFIRS data quality. These topics are discussed in more 

detail in the sections that follow.

Unknown Data Entries and Missing 

Values

On a fraction of the incident reports or casualty reports submitted to the NFIRS, the 

desired information for many data elements is either reported as “unknown” or is not 

reported at all. The total number of unknown entries or missing (i.e., blank or null) values 

is often larger than some of the important subcategories. For example, 48% of fatal fires 

in residential buildings reported from 2015 to 2017 did not have sufficient data recorded 

in the NFIRS to determine fire cause. The lack of data, especially for these residential fatal 

fires, masks the true picture of the fire problem.

16The “Review and Assessment of Data Quality in the National Fire Incident Reporting System” document is 

available at https://www.usfa.fema.gov/downloads/pdf/publications/nfirs_data_quality_report.pdf.
10 Data Sources and National Estimates Methodology Overview

Many prevention and public education programs use the NFIRS data to target at-risk 

groups or to address critical problems. Fire officials use the data in decision-making that 

affects the allocation of firefighting resources. Consumer groups and litigators use the 

data to assess product fire incidence. When the unknowns are large, the credibility of 

the data suffers. In some cases, even after the best attempts by fire investigators, the 

information is truly unknown. In other cases, the information reported as “unknown” in 

the initial NFIRS report is not updated after the fire investigation is completed. Reporting 

fire departments need to be more aware of the effect of incomplete data reporting and 

the need to update the initial NFIRS report if additional information is available after 

investigation. Efforts have been undertaken at the national level to encourage fire 

departments to close the loop on fires after investigations are completed.

In analyses, the unknown and missing data values should not be ignored. The approach 

taken by the USFA in presenting the data is to provide not only the “raw” percentages of 

each category, but also the “adjusted” percentages computed using only those incidents 

for which data were provided. This calculation, in effect, distributes the fires for which 

the data are unknown in the same proportion as the fires for which the data are known, 

which may or may not be approximately right. Both the reported data and the adjusted 

data (if unknowns are present) are plotted on bar charts in the USFA reports.

The following example illustrates distributing the fires for which the data are unknown 

using the cause of residential building fires: Cooking was determined as the fire cause for 

42.1% of reported residential building fires from 2015 to 2017; another 17.4% of reported 

fires had unknown causes. Thus, the percent of fires that had their cause reported was 

100 minus 17.4, which equals 82.6%. With the unknown causes apportioned like the known 

causes, the adjusted percent of cooking fires in residential buildings can then be computed 

as 42.1 divided by 82.6, which equals 51.0%.

It is important to note that null and blank values are considered unreported data and differ 

in meaning and substance from “unknown” data. In data elements where information is 

required, a null or blank value may invalidate the record and cause it to be excluded from 

analyses. In addition, many fire data elements are not required for NFIRS confined fires 

(i.e., Incident Types 113 to 118) and, thus, contain missing or null values. Therefore, the 

USFA excludes confined fires from the analyses of these nonrequired data elements for 

building fires.

The following section focuses on data elements where information is required for 

nonconfined fires (i.e., Incident Types 111 and 120 to 123); however, the data entries for 

these elements may contain valid unknown values. Tables 10 and 11 show the percentages 

of unknown data values for NFIRS data elements that are required for only nonconfined 

residential and nonresidential building fires (i.e., the percentages do not reflect confined 

fires), with the exception of “fire cause.” Although the USFA’s fire cause, as previously 

discussed, is not a collected NFIRS data element per se, but rather assigned based on 

an algorithm using cause-related data elements from the NFIRS, it is included in these 

tables for ease of presentation. It is important to note that percentages of unknown data 

values for “fire cause,” unlike the rest of the required data elements for nonconfined fires 

presented in the tables, reflect both confined and nonconfined fires. For 2015 to 2017, the 

percentages of unknown values for each data element in Tables 10 and 11 are relatively 

consistent from one year to the next, with the exception of the presence of detectors and 

presence of AES fields which reflect larger increases in unknown values from 2015 to 2016.
Incomplete Loss Reporting 11

Table 10. Percent of unknown values by specific data element for residential 

building fires reported to the NFIRS (2015-2017)

Data element

2015 2016 2017

Percent unknown Percent unknown Percent unknown

Area of Fire Origin 12.9 13.1 14.2

Heat Source 37.6 38.1 39.5

Item First Ignited 37.9 38.3 40.1

Factors 

Contributing to 

Ignition

28.9 30.1 31.6

Presence of 

Detectors 29.7 31.6 31.3

Presence of AES 8.4 10.2 9.5

Fire Cause 16.6 17.3 18.2

Source: NFIRS.

Table 11. Percent of unknown values by specific data element for nonresidential 

building fires reported to the NFIRS (2015-2017)

Data element

2015 2016 2017

Percent unknown Percent unknown Percent unknown

Area of Fire Origin 18.0 18.7 18.8

Heat Source 42.8 43.6 43.5

Item First Ignited 43.9 45.0 45.2

Factors 

Contributing to 

Ignition

31.5 32.6 33.6

Presence of 

Detectors 19.7 20.7 20.2

Presence of AES 10.3 10.7 10.8

Fire Cause 34.7 35.6 36.9

Source: NFIRS.

Incomplete Loss Reporting

Although it is troublesome that insufficient data for the various NFIRS data elements 

can mask the true picture of the fire problem and impact the credibility of the data, the 

apparent nonreporting of injuries and property loss associated with many fire incidents 

is equally challenging. For example, there are many reported fires where the flame 

spread indicates damage, but property loss is not reported. It is notoriously difficult to 

estimate dollar loss, but an approximation is more useful than leaving the data element 

blank. Analysts need to be aware that this apparent lack of property-loss data affects the 

understanding of those fires that cause substantial loss.
12 Data Sources and National Estimates Methodology Overview

Identifying Large Outliers

If the incident record clearly contains outliers, it is generally recommended to exclude the 

record from the analysis. However, before excluding such records, it is suggested that a 

quick internet search be conducted to see if some unusual fire did occur. Additionally, if 

time permits, following up with the fire department that submitted the incident record 

may be the best method to use for data verification.

National Fire Incident Reporting 

System Analytic Resources

Several resources that provide more detailed documentation on using the NFIRS and the 

NFIRS data are available. The “National Fire Incident Reporting System Complete Reference 

Guide” provides instructions for reporting data to the NFIRS and an understanding of the 

data elements collected by the system. It also serves as a reference for coding the data.

The document “National Fire Incident Reporting System Version 5.0 Fire Data Analysis 

Guidelines and Issues” discusses analytic considerations and methods of analyzing 

fire-incident data using NFIRS data. Topics include the NFIRS 5.0 data structure, general 

quality assurance issues, and definitions and parameters of common fire analyses (e.g., 

residential building fires or casualties), including the methodology for determining 

structure fire causes. The methods, techniques and considerations discussed are those 

used by the USFA analysts, and they do not necessarily reflect methods, techniques and 

considerations used by fire data analysts from other agencies and organizations. NFIRS 

data partners may (and do) employ their own methods for analyzing the data and may 

make differing assumptions when encountering data issues.

The “Review and Assessment of Data Quality in the National Fire Incident Reporting 

System” covers a review of the system, the many robust data quality checks and 

mechanisms which are an integral part of the NFIRS, and an assessment of the data 

quality both at the state level and at the data element level. The data element assessment 

focuses on the most common data elements used in NFIRS data analyses.

“The National Estimates Approach to U.S. Fire Statistics” is the original methodology 

for creating estimates of the U.S. fire problem using the NFPA’s annual Survey of Fire 

Departments for U.S. Fire Experience and the NFIRS data. The authors present a detailed 

consensus procedure for such calculations, as well as the supporting rationale. “National 

Estimates Methodology for Building Fires and Losses” is the USFA’s application of the 

national estimates approach to building fires and fire losses. It details the USFA’s current 

fire data estimation methodology for all building fires (i.e., residential and nonresidential) 

and associated losses.

The USFA’s “Fire in the United States 2006-2015” is a statistical portrait of the national fire 

problem and provides an in-depth discussion of the data sources and the methodologies 

used to incorporate these data into fire analyses. Lastly, the “Fire Data Analysis Handbook” 

is a resource for those unfamiliar with basic data analysis techniques and their applicability 

to fire-data based analyses.
Resources 13

Resources

Hall, J. & Harwood, B. (1989, May). The national estimates approach to U.S. fire statistics. 

Fire Technology, 25(2), 99–113. Retrieved from https://www.nfpa.org/-/media/Files/

News-and-Research/Fire-statistics-and-reports/NFPA-estimates-and-methodology/

NationalEstimatesApproach.pdf

USFA. (2004). Fire data analysis handbook (2nd ed.). Retrieved from http://www.usfa.fema.

gov/downloads/pdf/publications/fa-266.pdf

USFA. (2011). National fire incident reporting system version 5.0 fire data analysis guidelines 

and issues. Retrieved from https://www.usfa.fema.gov/downloads/pdf/nfirs/nfirs_

data_analysis_guidelines_issues.pdf

USFA. (2012). National estimates methodology for building fires and losses. Retrieved from 

https://www.usfa.fema.gov/downloads/pdf/statistics/national_estimate_methodology.

pdf

USFA. (2015). National Fire Incident Reporting System complete reference guide. Retrieved 

from https://www.usfa.fema.gov/downloads/pdf/nfirs/NFIRS_Complete_Reference_

Guide_2015.pdf

USFA. (2017). Fire in the United States 2006-2015 (19th ed.). Retrieved from https://www.

usfa.fema.gov/downloads/pdf/publications/fius19th.pdf

USFA. (2017). Review and assessment of data quality in the national fire incident reporting 

system. Retrieved from https://www.usfa.fema.gov/downloads/pdf/publications/

nfirs_data_quality_report.pdf