Yearly Traffic Safety Analysis

767 CRASHES IN
IOWA, IA
2015

In 2015, Lee County recorded 767 traffic crashes, resulting in 11 fatalities and 246 injuries. The most significant contributing factor identified in these incidents was collisions with animals, accounting for 221 crashes, or nearly 29% of the total.

767

Total Crash Events

11

Persons Killed

246

Persons Injured

10

Fatal Crash Events

Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

Vulnerable Road User Casualties

In 2015, 11 motorists were killed and 237 were injured in crashes. Among vulnerable road users, there were no pedestrian or cyclist fatalities reported. However, 5 pedestrians and 4 cyclists sustained injuries in traffic incidents.

0

Pedestrians Killed

0

Cyclists Killed

11

Motorists Killed

5

Pedestrians Injured

4

Cyclists Injured

237

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in Lee County occurred most frequently on Mondays and Fridays, with each day recording 121 incidents. The evening commute hour of 5 p.m. was the peak time for crashes, with 62 incidents. While the majority of crashes (369) happened during daylight, a notable number of crashes, 154 in total, occurred in dark conditions, whether the roadway was lighted or not.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 767 total crashes, 10 (1.3%) were fatal crashes, and an additional 192 crashes (25%) resulted in some level of injury. The majority of incidents, 565 crashes or 73.7%, resulted in no injuries. The 10 fatal crashes led to a total of 11 fatalities, indicating at least one crash involved multiple deaths.

Severity is per crash event (most severe injury). 10 fatal crash events resulted in 11 persons killed.

Outcome by Severity (Crash Events)

Fatal10fatal crashes1.3%
Serious Injury11serious injury crashes1.4%
Minor Injury69minor injury crashes9%
Possible Injury112possible injury crashes14.6%
No Injury565no injury crashes73.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals were the leading contributing factor, cited in 221 crashes (28.8%). Following this, driver-related factors such as losing control (57 crashes), following too closely (53 crashes), and running off the road (41 crashes) were the next most common causes. Failures to yield right-of-way from a stop sign were also significant, contributing to 34 crashes.

Officer-Reported Primary Contributing Cause

Animal221 (28.8%)
Lost Control57 (7.4%)
Followed too close53 (6.9%)
Ran off road - left41 (5.3%)
Driving too fast for conditions35 (4.6%)
Other (explain in narrative): Other35 (4.6%)
FTYROW: From stop sign34 (4.4%)
Ran off road - straight29 (3.8%)
FTYROW: Making left turn23 (3%)
Ran Stop Sign19 (2.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred under ideal conditions, with 364 (47.5%) happening in clear weather and 400 (52.2%) on dry road surfaces. Similarly, 369 crashes (48.1%) took place during daylight hours. Adverse weather conditions like rain (43 crashes) and snow (28 crashes) were less frequent, as were wet (60 crashes) and snowy/icy road surfaces (74 crashes combined).

Weather

Clear364 (66.7%)
Cloudy89 (16.3%)
Rain43 (7.9%)
Snow28 (5.1%)
Freezing rain/drizzle13 (2.4%)
Sleet, hail5 (0.9%)
Fog, smoke, smog2 (0.4%)
Blowing Snow2 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight369 (67.3%)
Dark - roadway not lighted85 (15.5%)
Dark - roadway lighted57 (10.4%)
Dawn16 (2.9%)
Dark - unknown roadway lighting12 (2.2%)
Dusk9 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry400 (72.2%)
Wet60 (10.8%)
Snow46 (8.3%)
Ice/frost28 (5.1%)
Gravel13 (2.3%)
Slush3 (0.5%)
Other (explain in narrative)2 (0.4%)
Water (standing or moving)1 (0.2%)
Mud, dirt1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Drivers aged 26-34 were the most frequently involved group in crashes, accounting for 227 of the individuals where age was recorded. Among vehicle makes, Ford (203) and Chevrolet (197) were the most common, followed by Dodge (70) and GMC (54). These figures represent the vehicles involved in crashes and do not reflect overall vehicle population or market share.

Top Vehicle Makes (1,166 vehicles)

1
FORD203 (17.4%)
2
CHEVROLET197 (16.9%)
3
CHEV70 (6%)
4
DODGE70 (6%)
5
GMC54 (4.6%)
6
DODG46 (3.9%)
7
TOYOTA43 (3.7%)
8
CHRYSLER41 (3.5%)
9
BUICK31 (2.7%)
10
PONTIAC27 (2.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

159 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (928 persons with recorded sex)

Male548 (59.1%)
Female380 (40.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Major Cause

The most frequently cited major cause for crashes was an animal in the roadway, accounting for 221 incidents. Other leading causes included losing control (57 crashes), following too closely (53 crashes), and running off the road to the left (41 crashes). Driving too fast for conditions was a factor in 35 crashes.

Major Cause

1
Animal221 (30.6%)
2
Lost Control57 (7.9%)
3
Followed too close53 (7.3%)
4
Ran off road - left41 (5.7%)
5
Driving too fast for conditions35 (4.8%)
6
Other (explain in narrative): Other35 (4.8%)
7
FTYROW: From stop sign34 (4.7%)
8
Ran off road - straight29 (4%)
9
FTYROW: Making left turn23 (3.2%)

Showing top 9 of 49 reported. 40 additional (195 total) not shown: Ran Stop Sign, Driver Distraction: Other interior distraction, Operating vehicle in an reckless, erratic, careless, negligent manner, Swerving/Evasive Action, Driver Distraction: Exterior distraction, Improper or erratic lane changing, FTYROW: From yield sign, Driver Distraction: Inattentive/lost in thought, Exceeded authorized speed, Failed to keep in proper lane, Made improper turn, Other (explain in narrative): No improper action, FTYROW: From driveway, FTYROW: Other (explain in narrative), Improper Backing, Ran Traffic Signal, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Other electronic device activity, Driver Distraction: Reaching for object(s)/fallen object(s), FTYROW: To pedestrian, FTYROW: At uncontrolled intersection, Other (explain in narrative): Vision obstructed, Crossed centerline (undivided), Separation of units, Traveling wrong way or on wrong side of road, Failure to signal intentions, Driver Distraction: Unrestrained animal, Ran off road - right, Passing: Other passing (explain in narrative), Passing: Through/around barrier, Passing: With insufficient distance/inadequate visibility, Driver Distraction: Adjusting devices (radio, climate), Disregarded RR Signal, FTYROW: From parked position, Cargo/equipment loss or shift, Towing Improperly, Driver Distraction: Passenger, Illegally Parked/Unattended, Operator inexperience, Equipment failure.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

First Harmful Event

The most common first harmful event was a collision with another vehicle in traffic, occurring in 276 crashes. The second most frequent event was a collision with an animal, noted in 218 incidents. Collisions with fixed objects were also prevalent, with ditches being the most common fixed object struck (45 crashes), followed by trees (10 crashes).

First Harmful Event

1
Collision with: Vehicle in traffic276 (36.9%)
2
Collision with: Animal218 (29.2%)
3
Collision with: Parked motor vehicle49 (6.6%)
4
Collision with fixed object: Ditch45 (6%)
5
Non-collision events: Overturn/rollover35 (4.7%)
6
Other (explain in narrative)15 (2%)
7
Collision with fixed object: Tree10 (1.3%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)9 (1.2%)
9
Collision with fixed object: Curb/island/raised median9 (1.2%)

Showing top 9 of 31 reported. 22 additional (81 total) not shown: Collision with fixed object: Utility pole/light support, Collision with: Struck/struck by object/cargo/person from other vehicle, Miscellaneous events: Hit and run, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Traffic sign support, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Guardrail - face, Collision with: Re-entering roadway, Non-collision events: Vehicle went airborne, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Mailbox, Collision with fixed object: Embankment, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Guardrail - end, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fence, Non-collision events: Non-contact vehicle (phantom), Collision with: Railway vehicle/train, Collision with fixed object: Culvert/pipe opening, Miscellaneous events: Eluding law enforcement, Miscellaneous events: Immersion, Non-collision events: Fell/jumped from vehicle.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Junction / Feature

Crashes were more likely to occur away from intersections, with 334 incidents (43.5%) happening on non-junction road segments. Four-way intersections were the most common crash site among junction types, accounting for 98 crashes. T-intersections were the site of another 37 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature334 (61.1%)
2
Intersection: Four-way intersection98 (17.9%)
3
Intersection: T-intersection37 (6.8%)
4
Non-intersection: Driveway access (related, not in)16 (2.9%)
5
Intersection: Other intersection (explain in narrative)14 (2.6%)
6
Non-intersection: Crossover-related11 (2%)
7
Non-intersection: Other non-intersection (explain in narrative)10 (1.8%)
8
Non-intersection: Driveway access (within)5 (0.9%)
9
Intersection: Intersection with ramp4 (0.7%)

Showing top 9 of 17 reported. 8 additional (18 total) not shown: Non-intersection: Railroad grade crossing, Non-intersection: Alley, Intersection: L-intersection, Intersection: Y-intersection, Interchange-related: Off-ramp, Non-intersection: Bike lanes, Interchange-related: Other interchange (explain in narrative), Interchange-related: On-ramp merge area.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, with 511 units recorded. Light trucks and SUVs were also frequently involved, with 261 four-tire light trucks and 203 sport utility vehicles documented. Tractor/semi-trailers were involved in 29 crashes, while motorcycles were involved in 10.

Vehicle Type

"Other" combines 14 smaller categories (31 records): Cargo/panel van (9), Single-unit truck (>= 3 axles) (4), All-terrain vehicle (ATV) (3), Farm tractor (3), Maintenance/construction vehicle (2), Other (explain in narrative) (2), Motor home/recreational vehicle (1), Golf cart (1), Train (1), Truck tractor (bobtail) (1), Truck/trailer (1), Other light truck (<=10000 lbs) (1), Farm equipment (explain in narrative) (1), School bus (seats > 15) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

A significant majority of crashes, 674 out of 767, occurred where no traffic controls were present. In locations with traffic controls, stop signs were the most common, present at the scene of 138 crashes. Traffic signals were present for 93 crashes.

Traffic Control Device

"Other" combines 3 smaller categories (6 records): Work zone sign (3), Warning sign (2), No Passing Zone (marked) (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Most Damaged Area

The front of the vehicle was the most common area of damage, recorded in 229 incidents. Rear-end collisions were also significant, with the rear being the most damaged area in 103 crashes. Damage to the front-driver side corner (90 incidents) and front-passenger side corner (84 incidents) suggests a high number of angle or turning-related impacts.

Most Damaged Area

"Other" combines 10 smaller categories (246 records): Passenger side - front (51), Passenger side - rear (50), Rear - driver side corner (39), Driver side - rear (35), Top (28), Rear - passenger side corner (17), Other (explain in narrative) (14), Undercarriage (6), Non-collision/no damage (5), Cargo loss (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Impairment (Alcohol / Drugs)

Impairment was suspected in 32 crashes, representing approximately 4.2% of total incidents. Alcohol was the suspected impairment in 31 of these cases, while drugs were suspected in one case. These figures represent a minimum, as impairment is often difficult to determine at the scene.

Crashes by City

The highest volume of crashes within Lee County occurred in Keokuk, with 203 incidents, and Fort Madison, with 193 incidents. Smaller municipalities like Montrose (20 crashes), Donnellson (16 crashes), and West Point (7 crashes) recorded significantly fewer events. A large number of crashes occurred in unincorporated areas and are not included in these city-specific totals.

Crashes by City

1
KEOKUK203 (45.6%)
2
FORT MADISON193 (43.4%)
3
MONTROSE20 (4.5%)
4
DONNELLSON16 (3.6%)
5
WEST POINT7 (1.6%)
6
HOUGHTON3 (0.7%)
7
FRANKLIN2 (0.4%)
8
SAINT PAUL1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Paved vs Unpaved Road

The vast majority of crashes, 710 out of 762 with specified road surface types, occurred on paved roadways. Crashes on unpaved surfaces, such as gravel or dirt roads, accounted for 52 incidents, representing approximately 6.8% of the total where surface type was known.

Paved vs Unpaved Road

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Roadway Contributing Factor

Among crashes where a roadway factor was noted, surface conditions such as wet or icy roads were the leading contributor, cited in 64 incidents. Other factors were cited infrequently, with slippery or loose surfaces contributing to 3 crashes and shoulder defects contributing to 2. In most crashes, no roadway factor was identified as a contributor.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)64 (87.7%)
2
Slippery, loose or worn surface3 (4.1%)
3
Shoulders (none, low, soft, high)2 (2.7%)
4
Debris1 (1.4%)
5
Ruts/holes/bumps1 (1.4%)
6
Disabled vehicle1 (1.4%)
7
Work Zone (roadway-related)1 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Driver Condition

While most drivers were recorded as 'apparently normal,' a driver condition was noted in a subset of crashes. Among these, driving under the influence of alcohol was the most frequent, recorded for 38 drivers. Driver fatigue or being asleep was noted for 14 drivers, and an emotional state was recorded for 10 drivers.

Driver Condition

1
Under the influence of alcohol38 (53.5%)
2
Asleep/fatigued14 (19.7%)
3
Emotional (e.g. depressed, angry)10 (14.1%)
4
Under the influence of drugs/meds4 (5.6%)
5
Medical condition (seizure, reaction)3 (4.2%)
6
Illness/fainted2 (2.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Property Damage

The most common estimated property damage cost was in the $1,500 to $7,500 range, which applied to 619 crashes. A smaller but significant number of crashes, 101, resulted in damages between $7,500 and $25,000. Ten crashes were estimated to have caused damage exceeding $25,000.

Property Damage

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Manner of Collision

Single-vehicle, non-collision events, which often involve running off the road, were the most common crash type, accounting for 310 incidents (40.4%). Among multi-vehicle crashes, rear-end collisions were the most frequent, with 124 incidents (16.2%), followed by broadside collisions with 97 incidents (12.6%).

Manner of Collision

"Other" combines 3 smaller categories (25 records): Head-on (front to front) (13), Other (explain in narrative) (11), Rear to rear (1).

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Pre-Crash Driver Action

The majority of vehicles involved in crashes, 625 in total, were moving straight ahead immediately prior to the incident. The next most common pre-crash action was being legally parked, with 99 vehicles involved. Vehicles turning left (78) or stopped in traffic (43) were also frequently involved in collisions.

Pre-Crash Driver Action

1
Movement essentially straight625 (62.1%)
2
Legally Parked99 (9.8%)
3
Turning left78 (7.8%)
4
Stopped in traffic43 (4.3%)
5
Other (explain in narrative)43 (4.3%)
6
Turning right27 (2.7%)
7
Changing lanes18 (1.8%)
8
Backing17 (1.7%)
9
Slowing/stopping (deceleration)14 (1.4%)

Showing top 9 of 18 reported. 9 additional (42 total) not shown: Negotiating a curve, Overtaking/passing, Accelerating in road, Illegally Parked/Unattended, Entering traffic lane (merging), Leaving traffic lane, Starting in road, Making U-turn, Entering a parked position.

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Person Type

Of the 1,429 individuals involved in crashes, the vast majority, 1,361, were drivers. Passengers accounted for 59 individuals, while vulnerable road users included 5 pedestrians and 4 bicyclists. This highlights that most incidents involved vehicle occupants.

Person Type

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 1,429 people involved in crashes, 11 individuals sustained fatal injuries. An additional 13 people suffered serious injuries, 87 had minor injuries, and 146 had possible injuries. A small number of non-drivers, 6 in total, were recorded with no injuries.

Person Injury Severity

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Based on the available data for safety equipment use, 137 occupants were recorded as using both a shoulder and lap belt. Conversely, 22 individuals were recorded as using no safety equipment at all. The data on this topic is limited and does not cover all occupants.

Occupant Safety Equipment

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

Single-vehicle crashes were the most common type, with 399 incidents, representing 52% of all crashes. Two-vehicle collisions were also frequent, accounting for 332 crashes. Multi-vehicle pile-ups were rare, with only one crash involving 4 vehicles and one involving 6 vehicles.

Vehicles Per Crash

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2015-01-01 through 2015-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 767
  • Total persons involved: 1,429
  • Total vehicles involved: 1,166

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2015." Published September 9, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2015-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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