Yearly Traffic Safety Analysis

920 CRASHES IN
IOWA, IA
2015

In 2015, Des Moines County recorded 920 traffic crashes, resulting in 4 fatalities and 278 injuries. These incidents involved 1,922 people and 1,621 vehicles. Analysis of contributing factors reveals that collisions involving animals were the most frequently cited cause, accounting for 102 incidents or 11.1% of crashes.

920

Total Crash Events

4

Persons Killed

278

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 constituted the largest group of individuals killed or injured, with 3 fatalities and 260 injuries. Vulnerable road users were also impacted; one pedestrian was killed and 10 were injured. Additionally, 6 cyclists were injured in traffic collisions, though no cyclist fatalities were recorded.

1

Pedestrians Killed

0

Cyclists Killed

3

Motorists Killed

0

Other Killed

10

Pedestrians Injured

6

Cyclists Injured

260

Motorists Injured

2

Other 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

Crash occurrences in Des Moines County peaked on Fridays, with 156 incidents reported, and on Thursdays with 141 incidents. The most frequent time for crashes was the 3 p.m. hour, which saw 88 collisions, followed by the 4 p.m. and 5 p.m. hours. A significant majority of crashes, 587 in total (63.8%), occurred 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 920 total crashes, approximately 75.1% (691 crashes) resulted in no injuries and were limited to property damage. The remaining incidents involved some level of injury, including 16 serious injury crashes and 65 minor injury crashes. There were 4 fatal crashes recorded, which resulted in a total of 4 fatalities.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.4%
Serious Injury16serious injury crashes1.7%
Minor Injury65minor injury crashes7.1%
Possible Injury144possible injury crashes15.7%
No Injury691no injury crashes75.1%

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 the presence of an animal, cited in 102 incidents (11.1%). Failure to yield the right-of-way from a stop sign was the next most common specific driver action, contributing to 63 crashes (6.8%). Following too closely was also a significant factor, involved in 62 crashes (6.7%).

Officer-Reported Primary Contributing Cause

Animal102 (11.1%)
Other (explain in narrative): Other84 (9.1%)
FTYROW: From stop sign63 (6.8%)
Followed too close62 (6.7%)
Ran off road - left56 (6.1%)
FTYROW: Making left turn46 (5%)
Lost Control38 (4.1%)
Driving too fast for conditions35 (3.8%)
Ran Stop Sign33 (3.6%)
Ran off road - straight28 (3%)

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 in favorable conditions, with 63.8% (587 crashes) happening in daylight and 66.6% (613 crashes) on dry road surfaces. Clear weather was reported for 54.8% of crashes (504 incidents). Adverse conditions were less frequent, with rain noted in 57 crashes and wet roads in 103 crashes.

Weather

Clear504 (60.2%)
Cloudy225 (26.9%)
Rain57 (6.8%)
Snow29 (3.5%)
Freezing rain/drizzle12 (1.4%)
Fog, smoke, smog5 (0.6%)
Severe Winds2 (0.2%)
Sleet, hail2 (0.2%)
Blowing Snow1 (0.1%)

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

Lighting

Daylight587 (69.5%)
Dark - roadway lighted128 (15.2%)
Dark - roadway not lighted88 (10.4%)
Dusk19 (2.3%)
Dawn12 (1.4%)
Dark - unknown roadway lighting10 (1.2%)

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

Road Surface

Dry613 (72.9%)
Wet103 (12.2%)
Snow55 (6.5%)
Ice/frost38 (4.5%)
Gravel19 (2.3%)
Slush12 (1.4%)
Sand1 (0.1%)

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 the most represented, with 304 individuals, followed by the 16-20 age group with 255 individuals. Among the 1,621 vehicles involved, Ford was the most frequent make listed (283 vehicles). Vehicles from Chevrolet (315 total, combining 'CHEV' and 'CHEVROLET' entries) and Dodge (150 total, combining 'DODG' and 'DODGE') were also commonly involved in crashes.

Top Vehicle Makes (1,621 vehicles)

1
FORD283 (17.5%)
2
CHEV173 (10.7%)
3
CHEVROLET142 (8.8%)
4
DODG105 (6.5%)
5
NR61 (3.8%)
6
JEEP60 (3.7%)
7
KIA55 (3.4%)
8
DODGE45 (2.8%)
9
BUIC44 (2.7%)
10
GMC43 (2.7%)

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

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

Sex Distribution (1,325 persons with recorded sex)

Male731 (55.2%)
Female594 (44.8%)

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 recorded major cause of crashes was an animal in the roadway, accounting for 102 incidents. Driver-related actions followed, with failure to yield right-of-way from a stop sign cited in 63 crashes and following too closely in 62 crashes. Running off the road to the left was also a common cause, contributing to 56 crashes.

Major Cause

1
Animal102 (12.1%)
2
Other (explain in narrative): Other84 (10%)
3
FTYROW: From stop sign63 (7.5%)
4
Followed too close62 (7.4%)
5
Ran off road - left56 (6.7%)
6
FTYROW: Making left turn46 (5.5%)
7
Lost Control38 (4.5%)
8
Driving too fast for conditions35 (4.2%)
9
Ran Stop Sign33 (3.9%)

Showing top 9 of 49 reported. 40 additional (321 total) not shown: Ran off road - straight, Ran Traffic Signal, Driver Distraction: Other interior distraction, FTYROW: Other (explain in narrative), Operating vehicle in an reckless, erratic, careless, negligent manner, Other (explain in narrative): No improper action, FTYROW: From driveway, Driver Distraction: Exterior distraction, Driver Distraction: Inattentive/lost in thought, FTYROW: From parked position, Improper Backing, Exceeded authorized speed, Failed to keep in proper lane, Made improper turn, FTYROW: From yield sign, FTYROW: At uncontrolled intersection, Swerving/Evasive Action, Improper or erratic lane changing, Ran off road - right, Driver Distraction: Passenger, Traveling wrong way or on wrong side of road, Driver Distraction: Talking on a hand-held device, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Reaching for object(s)/fallen object(s), Aggressive driving/road rage, FTYROW: Making right turn on red signal, Other (explain in narrative): Vision obstructed, Over correcting/over steering, Passing: Other passing (explain in narrative), Passing: Through/around barrier, Driver Distraction: Other electronic device activity, Crossed centerline (undivided), Driver Distraction: Unrestrained animal, Drove around RR grade crossing gates, Other (explain in narrative): Getting off/out of vehicle, Cargo/equipment loss or shift, Oversized Load/Vehicle, Equipment failure, Failed to yield to emergency vehicle, Passing: With insufficient distance/inadequate visibility.

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, which occurred in 580 crashes, representing 63% of all incidents. Collisions with animals were the second most frequent event, recorded in 89 crashes. Collisions with fixed objects, such as ditches (22 events), utility poles (21 events), and curbs (16 events), were also notable.

First Harmful Event

1
Collision with: Vehicle in traffic580 (63.4%)
2
Collision with: Animal89 (9.7%)
3
Collision with: Parked motor vehicle50 (5.5%)
4
Collision with fixed object: Ditch22 (2.4%)
5
Collision with fixed object: Utility pole/light support21 (2.3%)
6
Collision with: Non-motorist (see non-motorist section - NOT a unit)18 (2%)
7
Non-collision events: Other non-collision (explain in narrative)17 (1.9%)
8
Non-collision events: Overturn/rollover17 (1.9%)
9
Collision with fixed object: Curb/island/raised median16 (1.7%)

Showing top 9 of 38 reported. 29 additional (85 total) not shown: Miscellaneous events: Hit and run, Collision with fixed object: Traffic sign support, Collision with fixed object: Tree, Collision with fixed object: Embankment, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with: Re-entering roadway, Other (explain in narrative), Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Mailbox, Collision with fixed object: Guardrail - end, Collision with: Other non-fixed object (explain in narrative), Non-collision events: Vehicle went airborne, Collision with fixed object: Fence, Non-collision events: Jackknife, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Cable barrier, Collision with fixed object: Bridge pier or support, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Snow bank, Collision with fixed object: Guardrail - face, Collision with fixed object: Ground, Collision with fixed object: Wall, Collision with fixed object: Fire hydrant, Collision with: Railway vehicle/train, Miscellaneous events: Vehicle out of gear/rolled, 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 on non-intersection road segments, which accounted for 445 incidents, or 48.4% of the total. Four-way intersections were the most common type of junction for crashes, with 238 incidents reported. T-intersections were the location for another 58 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature445 (52.5%)
2
Intersection: Four-way intersection238 (28.1%)
3
Intersection: T-intersection58 (6.8%)
4
Non-intersection: Driveway access (related, not in)33 (3.9%)
5
Intersection: Intersection with ramp16 (1.9%)
6
Non-intersection: Driveway access (within)11 (1.3%)
7
Intersection: Other intersection (explain in narrative)8 (0.9%)
8
Non-intersection: Crossover-related7 (0.8%)
9
Non-intersection: Other non-intersection (explain in narrative)7 (0.8%)

Showing top 9 of 17 reported. 8 additional (25 total) not shown: Non-intersection: Alley, Interchange-related: Off-ramp, diverge area, Interchange-related: Off-ramp, Interchange-related: On-ramp merge area, Intersection: Y-intersection, Intersection: L-intersection, Non-intersection: Railroad grade crossing, Interchange-related: On-ramp.

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 761 of the 1,621 vehicles (47%). Light trucks and sport utility vehicles were also frequently involved, with 320 and 309 vehicles respectively. Tractor/semi-trailers were involved in crashes 30 times, while motorcycles were involved 21 times.

Vehicle Type

"Other" combines 14 smaller categories (28 records): Single unit truck (2-axle, 6-tire) (7), Cargo/panel van (5), Other bus (seats > 15) (2), Passenger van (seats 9-15) (2), Maintenance/construction vehicle (2), Farm equipment (explain in narrative) (2), Other light truck (<=10000 lbs) (1), Tractor/doubles (1), Farm tractor (1), Train (1), Motor home/recreational vehicle (1), Other small bus (seats 9-15) (1), Other heavy truck (> 10000 lbs) (cannot classify) (1), Other (explain in narrative) (1).

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

Traffic Control Device

Analysis of traffic controls indicates that the majority of crashes, 925 incidents, occurred where no traffic controls were present. For crashes at controlled locations, traffic signals were the most common device, present at 330 crashes. Stop signs were present at 202 crash locations.

Traffic Control Device

"Other" combines 4 smaller categories (8 records): No Passing Zone (marked) (3), Traffic director (person) (2), Work zone sign (2), School zone signs (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 401 vehicles sustaining damage primarily to the front. An additional 299 vehicles had damage concentrated in the front corners. Rear-end collisions were indicated by 180 vehicles with primary damage to the rear, while side impacts were noted for a combined 228 vehicles damaged on the driver or passenger side.

Most Damaged Area

"Other" combines 9 smaller categories (364 records): Passenger side - front (72), Passenger side - rear (68), Driver side - rear (66), Rear - driver side corner (65), Rear - passenger side corner (35), Other (explain in narrative) (25), Top (15), Undercarriage (12), Non-collision/no damage (6).

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

Impairment (Alcohol / Drugs)

A total of 37 crashes, representing 4% of all incidents, were recorded as involving an impaired driver. Among these crashes where impairment type was specified, alcohol was a factor in 33 cases and drugs were a factor in 2 cases. These figures represent a minimum count, as impairment may not be determined in all applicable instances.

Crashes by City

The highest concentration of crashes within the county occurred in Burlington, which recorded 618 incidents. West Burlington had the second-highest volume with 100 crashes. Other municipalities, including Mediapolis (20 crashes), Danville (10 crashes), and Middletown (8 crashes), reported significantly fewer incidents.

Crashes by City

1
BURLINGTON618 (81.7%)
2
WEST BURLINGTON100 (13.2%)
3
MEDIAPOLIS20 (2.6%)
4
DANVILLE10 (1.3%)
5
MIDDLETOWN8 (1.1%)

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, 875 incidents, occurred on paved roadways. Crashes on unpaved surfaces like gravel or dirt roads accounted for 41 incidents, or approximately 4.5% of crashes where the surface type was recorded.

Paved vs Unpaved Road

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

Roadway Contributing Factor

In cases where a roadway factor was noted as a contributor, adverse surface conditions such as wet or icy roads were the most common, cited in 84 crashes. Work zones were a contributing factor in 17 crashes. Other noted factors included slippery or loose surfaces (8 crashes) and obstructions in the roadway (2 crashes).

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)84 (73%)
2
Work Zone (roadway-related)17 (14.8%)
3
Slippery, loose or worn surface8 (7%)
4
Obstruction in roadway2 (1.7%)
5
Shoulders (none, low, soft, high)1 (0.9%)
6
Debris1 (0.9%)
7
Traffic backup, regular congestion1 (0.9%)
8
Disabled vehicle1 (0.9%)

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, driving under the influence of alcohol was the most frequent, noted for 48 drivers. Driver fatigue or falling asleep was documented for 8 drivers. Other conditions included an emotional state (7 drivers) and influence of drugs or medication (5 drivers).

Driver Condition

1
Under the influence of alcohol48 (62.3%)
2
Asleep/fatigued8 (10.4%)
3
Emotional (e.g. depressed, angry)7 (9.1%)
4
Under the influence of drugs/meds5 (6.5%)
5
Illness/fainted4 (5.2%)
6
Medical condition (seizure, reaction)2 (2.6%)
7
Walks with a cane/crutches1 (1.3%)
8
Physical impairment1 (1.3%)
9
Visually impaired1 (1.3%)

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

Property Damage

Officer-estimated property damage was most commonly in the $1,500 to $7,500 range, which applied to 744 crashes, or 80.9% of the total. A smaller number of crashes resulted in more significant damage, with 136 incidents estimated between $7,500 and $25,000. Eight crashes were estimated to have 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 such as running off the road were the most frequent crash type, accounting for 234 incidents or 25.4% of the total. Rear-end collisions were the next most common manner of collision with 210 crashes (22.8%). Broadside collisions also occurred frequently, representing 187 crashes or 20.3% of all incidents.

Manner of Collision

"Other" combines 3 smaller categories (46 records): Rear to side (23), Other (explain in narrative) (15), Rear to rear (8).

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 was moving essentially straight, which was the case for 889 vehicles, or 54.8% of all vehicles with a recorded action. Turning left was the next most frequent maneuver, recorded for 155 vehicles. A notable 134 vehicles were legally parked when they were struck.

Pre-Crash Driver Action

1
Movement essentially straight889 (58.2%)
2
Turning left155 (10.1%)
3
Legally Parked134 (8.8%)
4
Stopped in traffic80 (5.2%)
5
Turning right67 (4.4%)
6
Slowing/stopping (deceleration)60 (3.9%)
7
Backing60 (3.9%)
8
Other (explain in narrative)22 (1.4%)
9
Negotiating a curve15 (1%)

Showing top 9 of 17 reported. 8 additional (46 total) not shown: Changing lanes, Overtaking/passing, Making U-turn, Leaving traffic lane, Entering traffic lane (merging), Illegally Parked/Unattended, Accelerating in road, Starting in road.

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

Pedestrian/Cyclist Action

Among the 19 non-motorists involved in crashes, the most common recorded action was entering or crossing a roadway, documented for 5 individuals. Three non-motorists were moving along the roadway with traffic at the time of their collision. The action for 6 individuals was recorded as 'Other'.

Pedestrian/Cyclist Action

1
Other6 (31.6%)
2
Entering or crossing roadway5 (26.3%)
3
Movement: Along roadway with traffic3 (15.8%)
4
Playing on or working on vehicle1 (5.3%)
5
Approaching or leaving vehicle1 (5.3%)
6
Waiting to cross roadway1 (5.3%)
7
Disabled vehicle-related/pushing vehicle1 (5.3%)
8
Movement: On shoulder/median1 (5.3%)

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

Person Type

Drivers constituted the vast majority of individuals involved in crashes, accounting for 1,835 of the 1,922 people recorded (95.5%). Passengers made up another 68 individuals (3.5%). The remaining persons involved included 11 pedestrians, 6 bicyclists, and 2 other non-motorists.

Person Type

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

Person Injury Severity

A total of 282 individuals sustained injuries or were killed in traffic crashes. This includes 4 fatalities, 22 serious injuries, 85 minor injuries, and 171 possible injuries. These individuals represent 14.7% of the 1,922 total persons involved in crashes during this period.

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 209 vehicle occupants for whom safety equipment use was specified, 185 were reported as using a shoulder and lap belt. Fifteen occupants were recorded as using no safety equipment at all. Additionally, 5 occupants were secured in a forward-facing child safety seat and 1 was in a booster seat.

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

The majority of crashes, 610 incidents or 66.3%, involved two vehicles. Single-vehicle crashes accounted for 272 incidents, representing 29.6% of the total. Multi-vehicle collisions involving three or more vehicles were less common, with 29 crashes involving three vehicles and 9 crashes involving four or more.

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: 920
  • Total persons involved: 1,922
  • Total vehicles involved: 1,621

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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