Guide

NFIRS Data Explained: What the National Fire Incident Reporting System Tells Us

The National Fire Incident Reporting System (NFIRS) is the largest national database of fire incident information in the United States. Administered by the US Fire Administration (USFA), NFIRS collects detailed reports from participating fire departments on every type of incident they respond to — not just fires. Understanding NFIRS data helps contextualize the statistics on PlainFireData and reveals both the strengths and limitations of fire data nationally.

Leading causes of US home fires

Share of residential fires by cause

% of fires

What this shows Cooking is the leading cause, accounting for 49% of US home fires. Smoking materials cause a far larger share of deaths than fires — a reminder that the most common causes are not always the deadliest.

Source U.S. Fire Administration / NFPA residential fire cause estimates As of 2024

1. What Is NFIRS?

NFIRS is a voluntary reporting system where fire departments submit standardized incident reports to the USFA through their state fire marshal offices.

  • ▸ Established in 1975 to create a national picture of the US fire problem
  • ▸ Currently in version 5.0 — the standard incident reporting format since 1999
  • ▸ Participation is voluntary at the federal level, but many states mandate NFIRS reporting for departments that receive state or federal funding
  • ▸ Approximately 70-75% of US fire departments participate, representing about 85% of the US population
  • ▸ Data flows from individual departments → state fire marshals → USFA national database
  • ▸ The USFA publishes aggregated NFIRS data in annual reports, topical studies, and through the National Fire Data Center

2. What NFIRS Contains

NFIRS captures detailed information about every incident a participating department responds to, organized into standardized modules.

  • ▸ Basic Module — required for every incident: date, time, type of incident, actions taken, property use, casualties, and dollar loss
  • ▸ Fire Module — additional detail for fire incidents: heat source, item first ignited, area of origin, cause of ignition, factors contributing to ignition
  • ▸ Structure Fire Module — building-specific data: construction type, building status, number of stories, fire spread extent, detector and sprinkler performance
  • ▸ Civilian Fire Casualty Module — details on civilian injuries and deaths: age, gender, activity at time of injury, severity, cause of injury
  • ▸ Fire Service Casualty Module — same as civilian module but for firefighter injuries and deaths on duty
  • ▸ EMS Module — details on emergency medical service incidents (now 60-70% of all fire department responses)
  • ▸ HazMat Module — details on hazardous materials incidents: materials involved, release type, containment actions

3. How PlainFireData Uses This Data

PlainFireData integrates NFIRS-derived statistics with other federal data sources to present a comprehensive picture of fire protection.

  • ▸ State-level fire statistics on PlainFireData (annual fires, deaths, injuries, property loss) are derived from USFA's analysis of NFIRS data
  • ▸ Department-level data comes primarily from HIFLD (DHS/CISA) which catalogs department characteristics but not incident data
  • ▸ NFIRS incident-level records are not publicly available in raw form — USFA publishes them as aggregated statistics and topical reports
  • ▸ The fire statistics on state and county pages reflect NFIRS-reported data adjusted by USFA to account for non-participating departments
  • ▸ Cross-referencing NFIRS fire cause data with department characteristics helps identify where prevention programs are most needed

4. Limitations of NFIRS Data

NFIRS is the best national fire data source, but it has significant limitations that users should understand.

  • ▸ Voluntary participation means 25-30% of departments don't report — this creates geographic gaps, particularly in rural areas with small volunteer departments
  • ▸ Reporting quality varies widely — some departments submit detailed reports while others provide only minimal required fields
  • ▸ Data lags — NFIRS data is typically 1-2 years behind the current date due to the time needed for departments to submit, states to compile, and USFA to aggregate
  • ▸ Not all incident types are captured equally — fire incidents get the most detailed reporting; EMS and other calls may be less complete
  • ▸ Dollar loss estimates are self-reported by fire officers on scene and are known to be imprecise, particularly for large fires
  • ▸ No individual incident lookup — you cannot search for a specific fire at a specific address in NFIRS public data

5. Accessing NFIRS Data

There are several ways to access NFIRS-derived information, depending on your needs.

  • ▸ USFA Fire Statistics page (usfa.fema.gov) — annual reports, topical studies, and state fire profiles based on NFIRS data
  • ▸ National Fire Data Center — publishes research reports analyzing NFIRS trends (leading causes, demographics, seasonal patterns)
  • ▸ State fire marshal offices — many states publish their own NFIRS data with state-specific analysis
  • ▸ NFIRS Public Data — bulk data downloads available through the USFA for researchers (requires registration)
  • ▸ PlainFireData — integrates NFIRS-derived state statistics with HIFLD department data and FEMA grant information in an accessible format
  • ▸ For local incident data, contact your fire department directly — they have their own records and may share information upon request
Sources: USFA National Fire Statistics, NFPA Fire Statistics, HIFLD Fire Stations (DHS/CISA), IBHS Home Hardening Research, FEMA Assistance to Firefighters Grant program data.

Read our methodology — how this data is sourced, computed, and verified.

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Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainFireData Editorial

Understanding the Data

The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.

It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.

For readers who want to conduct their own research, we recommend going directly to the source whenever possible. federal and state government agencies provides detailed documentation on collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.

How We Analyze Data Records

Our analytical approach involves several steps designed to surface meaningful insights from large datasets. First, we clean and standardize the raw data, handling variations in naming conventions, date formats, and categorical labels. Then we compute summary statistics, distributions, and comparative benchmarks across relevant dimensions such as geography, time period, and category type.

Key metrics we examine include statistical records, geographic distributions, temporal trends. These indicators provide a multi-dimensional view of each entity in our database, allowing users to understand not just individual records but how they compare to peers, regional averages, and national benchmarks. We believe this contextual approach is far more valuable than presenting raw numbers in isolation.