Yearly Traffic Safety Analysis

541 CRASHES IN
IOWA, IA
2015

In 2015, Wapello County recorded 541 traffic crashes, resulting in 2 fatalities and 220 injuries. A significant finding from the data is that collisions with animals were the most frequently cited contributing factor, accounting for 77 incidents, or 14.2% of all crashes.

541

Total Crash Events

2

Persons Killed

220

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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, motorists accounted for all fatalities and the vast majority of injuries in Wapello County, with 2 motorists killed and 215 injured. Vulnerable road users were also impacted, though to a lesser extent, with 4 pedestrians and 1 cyclist sustaining injuries. No fatalities were recorded for pedestrians or cyclists during this period.

0

Pedestrians Killed

0

Cyclists Killed

2

Motorists Killed

4

Pedestrians Injured

1

Cyclists Injured

215

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 Wapello County occurred most frequently on Tuesdays, which saw 89 incidents in 2015. The data reveals distinct peaks during commute hours, with the most crashes happening in the 3 p.m. hour (53 crashes) and the 7 a.m. hour (33 crashes). A majority of collisions, 341 out of 541, took place during daylight hours.

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 541 total crashes, 68.2% (369 incidents) resulted in no injuries, being property-damage-only events. The remaining crashes involved injuries of varying severity, including 98 with possible injuries, 61 with minor injuries, and 11 with serious injuries. There were 2 fatal crashes recorded, resulting in 2 total fatalities.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.4%
Serious Injury11serious injury crashes2%
Minor Injury61minor injury crashes11.3%
Possible Injury98possible injury crashes18.1%
No Injury369no injury crashes68.2%

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

The leading contributing factor identified in crashes was 'Animal,' cited in 77 incidents (14.2%). This was followed by drivers losing control (62 crashes, 11.5%) and failure to yield the right-of-way from a stop sign (59 crashes, 10.9%). Following too closely was also a significant factor, contributing to 49 crashes.

Officer-Reported Primary Contributing Cause

Animal77 (14.2%)
Lost Control62 (11.5%)
FTYROW: From stop sign59 (10.9%)
Followed too close49 (9.1%)
Driving too fast for conditions32 (5.9%)
FTYROW: Making left turn30 (5.5%)
Ran off road - left27 (5%)
Ran off road - straight19 (3.5%)
Other (explain in narrative): Other18 (3.3%)
Ran Stop Sign15 (2.8%)

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 data indicates that most crashes occurred in ideal driving conditions, with 61.7% happening in clear weather and 67.3% on dry road surfaces. Similarly, 341 of the 541 total crashes (63.0%) occurred during daylight. Adverse conditions were less frequent, with 23 crashes reported in rain and 23 in snow, while 48 crashes occurred on wet roads and 32 on snowy roads.

Weather

Clear334 (70.5%)
Cloudy79 (16.7%)
Rain23 (4.9%)
Snow23 (4.9%)
Freezing rain/drizzle11 (2.3%)
Fog, smoke, smog4 (0.8%)

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

Lighting

Daylight341 (71.9%)
Dark - roadway lighted57 (12.0%)
Dark - roadway not lighted54 (11.4%)
Dusk9 (1.9%)
Dawn8 (1.7%)
Dark - unknown roadway lighting5 (1.1%)

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

Road Surface

Dry364 (76.8%)
Wet48 (10.1%)
Snow32 (6.8%)
Ice/frost22 (4.6%)
Gravel6 (1.3%)
Slush2 (0.4%)

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

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was most represented with 192 individuals, followed closely by the 16-20 age group with 184 individuals. Among the 897 vehicles involved, Chevrolet was the most frequent make with 196 vehicles, followed by Ford with 137 and Dodge with 99. Toyota (70) and Jeep (34) were also commonly involved.

Top Vehicle Makes (897 vehicles)

1
FORD137 (15.3%)
2
CHEV131 (14.6%)
3
CHEVROLET65 (7.2%)
4
DODG63 (7%)
5
DODGE36 (4%)
6
TOYT36 (4%)
7
JEEP34 (3.8%)
8
TOYOTA34 (3.8%)
9
GMC28 (3.1%)
10
CHRY22 (2.5%)

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

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

Sex Distribution (811 persons with recorded sex)

Male455 (56.1%)
Female356 (43.9%)

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 common major cause of crashes was interaction with an animal, which was cited in 77 incidents. This was followed by drivers losing control (62 crashes) and failure to yield the right-of-way from a stop sign (59 crashes). Following too closely (49 crashes) and driving too fast for conditions (32 crashes) were also primary causes.

Major Cause

1
Animal77 (14.8%)
2
Lost Control62 (11.9%)
3
FTYROW: From stop sign59 (11.3%)
4
Followed too close49 (9.4%)
5
Driving too fast for conditions32 (6.1%)
6
FTYROW: Making left turn30 (5.7%)
7
Ran off road - left27 (5.2%)
8
Ran off road - straight19 (3.6%)
9
Other (explain in narrative): Other18 (3.4%)

Showing top 9 of 44 reported. 35 additional (149 total) not shown: Ran Stop Sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Other (explain in narrative): No improper action, FTYROW: From driveway, Made improper turn, Ran Traffic Signal, Ran off road - right, Exceeded authorized speed, Driver Distraction: Other interior distraction, FTYROW: From yield sign, Failed to keep in proper lane, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Exterior distraction, Driver Distraction: Reaching for object(s)/fallen object(s), Improper Backing, FTYROW: Other (explain in narrative), Improper or erratic lane changing, Passing: On wrong side, Swerving/Evasive Action, Passing: Other passing (explain in narrative), Driver Distraction: Passenger, FTYROW: From parked position, Downhill runaway, FTYROW: At uncontrolled intersection, Illegally Parked/Unattended, Operator inexperience, Traveling wrong way or on wrong side of road, Crossed centerline (undivided), Other (explain in narrative): Vision obstructed, Cargo/equipment loss or shift, Driver Distraction: Talking on a hand-held device, FTYROW: To pedestrian, Failed to yield to emergency vehicle, Equipment failure, Over correcting/over steering.

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

First Harmful Event

The most frequent first harmful event was a collision with another vehicle in traffic, accounting for 290 crashes, or 53.6% of the total. Collisions with animals were the second most common event, with 76 incidents. Single-vehicle run-off-road events were also prevalent, including 32 crashes where the first harmful event was hitting a ditch and 32 involving an overturn or rollover.

First Harmful Event

1
Collision with: Vehicle in traffic290 (54%)
2
Collision with: Animal76 (14.2%)
3
Collision with fixed object: Ditch32 (6%)
4
Non-collision events: Overturn/rollover32 (6%)
5
Collision with: Parked motor vehicle22 (4.1%)
6
Collision with fixed object: Utility pole/light support15 (2.8%)
7
Collision with fixed object: Tree8 (1.5%)
8
Other (explain in narrative)7 (1.3%)
9
Collision with: Re-entering roadway4 (0.7%)

Showing top 9 of 34 reported. 25 additional (51 total) not shown: Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with fixed object: Fence, Non-collision events: Vehicle went airborne, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Embankment, Collision with fixed object: Guardrail - face, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Ground, Miscellaneous events: Hit and run, Collision with fixed object: Building, Collision with fixed object: Other fixed object (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Non-collision events: Other non-collision (explain in narrative), Collision with: Thrown or falling object, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Traffic sign support, Miscellaneous events: Eluding law enforcement, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Bridge overhead structure, Collision with fixed object: Snow bank, Miscellaneous events: Immersion, Non-collision events: Fell/jumped from vehicle, Non-collision events: Jackknife, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Mailbox.

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 on non-intersection road segments, with 244 incidents (45.1%) happening away from any junction. Four-way intersections were the most common crash location among junction types, accounting for 146 crashes (27.0%). T-intersections were the site of an additional 26 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature244 (51.5%)
2
Intersection: Four-way intersection146 (30.8%)
3
Intersection: T-intersection26 (5.5%)
4
Non-intersection: Driveway access (related, not in)11 (2.3%)
5
Non-intersection: Driveway access (within)8 (1.7%)
6
Intersection: Other intersection (explain in narrative)6 (1.3%)
7
Intersection: Intersection with ramp5 (1.1%)
8
Non-intersection: Other non-intersection (explain in narrative)4 (0.8%)
9
Non-intersection: Alley4 (0.8%)

Showing top 9 of 18 reported. 9 additional (20 total) not shown: Interchange-related: On-ramp merge area, Interchange-related: Off-ramp, Intersection: Roundabout, Non-intersection: Railroad grade crossing, Intersection: Y-intersection, Non-intersection: Crossover-related, Intersection: L-intersection, Interchange-related: On-ramp, Interchange-related: Off-ramp, diverge 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, accounting for 420 of the 897 vehicles (46.8%). Light trucks and pickups (187 vehicles) and sport utility vehicles (161 vehicles) were also frequently involved. Commercial trucks, including tractor-trailers, made up 2.7% of vehicles in crashes, while motorcycles accounted for 1.0%.

Vehicle Type

"Other" combines 11 smaller categories (25 records): Cargo/panel van (6), Single unit truck (2-axle, 6-tire) (6), Farm tractor (3), Other (explain in narrative) (2), Truck/trailer (2), Motor home/recreational vehicle (1), Tractor/doubles (1), Moped (1), Truck tractor (bobtail) (1), 3-wheeled, unenclosed (1), Other bus (seats > 15) (1).

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

Traffic Control Device

The data indicates that a majority of vehicles involved in crashes were on road segments with no traffic controls present, accounting for 548 instances. Where traffic controls were present, stop signs were the most common, noted in 140 instances, followed by traffic signals in 102 instances. Overall, 66.9% of vehicles in crashes were noted as having no controls present.

Traffic Control Device

"Other" combines 2 smaller categories (2 records): Work zone sign (1), 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

Frontal impacts were the most common area of vehicle damage, with 254 vehicles sustaining damage to the front. Including front corners, frontal impacts accounted for 44.6% of all vehicle damage points. Rear impacts, indicative of rear-end collisions, were the second most frequent, with 105 vehicles damaged at the rear.

Most Damaged Area

"Other" combines 9 smaller categories (172 records): Passenger side - rear (33), Top (27), Driver side - rear (27), Passenger side - front (26), Rear - driver side corner (22), Rear - passenger side corner (16), Other (explain in narrative) (8), Non-collision/no damage (8), Undercarriage (5).

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

Impairment (Alcohol / Drugs)

Impairment was a factor in at least 26 crashes, representing 4.8% of the total for the year. Of these, alcohol was the sole impairing substance in 21 cases, while drugs were involved in 3 cases and a combination of alcohol and drugs was noted in 2 cases. These figures represent a minimum, as impairment may be under-reported in crash data.

Crashes by City

The majority of crashes within the county were concentrated in Ottumwa, which recorded 346 incidents. Other municipalities saw significantly lower volumes, including Eddyville with 11 crashes, and both Agency and Eldon with 4 crashes each. Chillicothe (3 crashes), Blakesburg (2 crashes), and Kirkville (1 crash) also reported incidents.

Crashes by City

1
OTTUMWA346 (93.3%)
2
EDDYVILLE11 (3%)
3
AGENCY4 (1.1%)
4
ELDON4 (1.1%)
5
CHILLICOTHE3 (0.8%)
6
BLAKESBURG2 (0.5%)
7
KIRKVILLE1 (0.3%)

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, 510 out of 540 for which this data was recorded, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt roads accounted for 30 incidents, or 5.6% of the total. This reflects the prevalence of driving on the county's primary paved road network.

Paved vs Unpaved Road

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

Roadway Contributing Factor

A specific roadway factor was identified as a contributor in 63 crashes. The most common factor was the surface condition, such as wet or icy roads, which was cited in 52 incidents. Work zones were a contributing factor in 3 crashes, while obstructions in the roadway and slippery surfaces each contributed to 2 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)52 (82.5%)
2
Work Zone (roadway-related)3 (4.8%)
3
Slippery, loose or worn surface2 (3.2%)
4
Obstruction in roadway2 (3.2%)
5
Shoulders (none, low, soft, high)1 (1.6%)
6
Ruts/holes/bumps1 (1.6%)
7
Traffic backup, regular congestion1 (1.6%)
8
Traffic control obscured1 (1.6%)

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,' the data indicates specific driver conditions in a subset of cases. Driving under the influence of alcohol was the most frequently noted condition, with 26 instances. Driver fatigue or falling asleep was cited in 9 cases, and driving under the influence of drugs or medication was noted in 3 cases.

Driver Condition

1
Under the influence of alcohol26 (63.4%)
2
Asleep/fatigued9 (22%)
3
Under the influence of drugs/meds3 (7.3%)
4
Emotional (e.g. depressed, angry)2 (4.9%)
5
Medical condition (seizure, reaction)1 (2.4%)

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

Property Damage

The estimated cost of property damage was most commonly in the $1,500 to $7,500 range, which applied to 418 crashes, or 77.3% of the total. A smaller number of incidents resulted in more significant damage, with 97 crashes estimated between $7,500 and $25,000, and 8 crashes (1.5%) exceeding $25,000 in property damage.

Property Damage

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

Manner of Collision

The most frequent type of crash was a non-collision event involving a single vehicle, such as a run-off-road or rollover, which accounted for 198 incidents or 36.6% of all crashes. Among multi-vehicle crashes, rear-end collisions were the most common, with 111 occurrences (20.5%), followed by broadside collisions with 99 occurrences (18.3%).

Manner of Collision

"Other" combines 3 smaller categories (17 records): Head-on (front to front) (9), Rear to side (6), Rear to rear (2).

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

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was moving essentially straight, which was the case for 530 of the 897 vehicles (59.1%). Turning left was the second most frequent action, recorded for 101 vehicles (11.3%). Other notable actions included slowing or stopping (36 vehicles) and being legally parked (33 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight530 (62.7%)
2
Turning left101 (12%)
3
Slowing/stopping (deceleration)36 (4.3%)
4
Legally Parked33 (3.9%)
5
Turning right31 (3.7%)
6
Stopped in traffic27 (3.2%)
7
Other (explain in narrative)23 (2.7%)
8
Negotiating a curve14 (1.7%)
9
Backing14 (1.7%)

Showing top 9 of 18 reported. 9 additional (36 total) not shown: Entering traffic lane (merging), Overtaking/passing, Illegally Parked/Unattended, Changing lanes, Leaving traffic lane, Leaving a parked position, Accelerating in road, Starting in road, Entering a parked position.

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

Person Type

The vast majority of individuals involved in crashes were drivers, accounting for 1,063 of the 1,126 people recorded (94.4%). Passengers made up 5.1% of the individuals involved, with 58 recorded. Vulnerable road users were a small fraction of the total, consisting of 4 pedestrians and 1 bicyclist.

Person Type

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

Person Injury Severity

Across all 1,126 individuals involved in crashes, there were 2 fatalities and 220 reported injuries. The injuries were categorized as 13 serious, 76 minor, and 131 possible. The data shows that the majority of people involved in crashes did not sustain a reported injury.

Person Injury Severity

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

Occupant Safety Equipment

Among the 172 individuals for whom safety equipment use was recorded, 145 were noted as using a shoulder and lap belt. However, 16 individuals, or 9.3% of this group, were recorded as using no safety equipment. The data also captured the use of child safety seats in 6 instances.

Occupant Safety Equipment

"Other" combines 1 smaller categories (1 records): Child safety seat (rear-facing) (1).

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

Vehicles Per Crash

The most common crash scenario involved two vehicles, which occurred in 296 out of 541 incidents (54.7%). Single-vehicle crashes were also frequent, accounting for 216 incidents, or 39.9% of the total. Crashes involving three or more vehicles were less common, with 27 three-vehicle crashes and 2 four-vehicle crashes recorded.

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: 541
  • Total persons involved: 1,126
  • Total vehicles involved: 897

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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