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CRASH INTELLIGENCE REPORT · IOWA, IA · 2015
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2015-annual-report
Yearly Traffic Safety Analysis
172 CRASHES IN
IOWA, IA
2015
In 2015, Louisa County recorded 172 traffic crashes, resulting in 1 fatality and 43 injuries. A significant majority of these incidents, 59.3%, were attributed to collisions with animals, which was the leading contributing factor by a large margin.
172
Total Crash Events
1
Persons Killed
43
Persons Injured
1
Fatal Crash Events
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, all recorded fatalities and injuries in Louisa County involved motorists. One motorist was killed and 43 were injured in traffic crashes. There were no reported fatalities or injuries involving pedestrians or cyclists during this period.
1
Motorists Killed
43
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 Louisa County peaked on Thursdays, with 31 incidents reported. The most frequent time for crashes was the 6 a.m. hour, which saw 19 events. Significant crash activity also occurred during the evening hours between 5 p.m. and 9 p.m.
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 172 crashes, a large majority (77.9%) resulted in no injuries. Injury-related crashes accounted for approximately 22.1% of the total, including 7 serious injury and 14 minor injury incidents. One fatal crash occurred, resulting in one fatality.
Outcome by Severity (Crash Events)
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 primary contributing factor to crashes was encounters with animals, cited in 102 incidents, accounting for 59.3% of all crashes. Far less frequent factors included losing control of the vehicle, which was noted in 15 crashes (8.7%), and driving too fast for conditions, which was a factor in 7 crashes (4.1%).
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A majority of crashes occurred in favorable conditions, with 59% of incidents with available data happening in clear weather and 74% on dry road surfaces. Daylight conditions were present for 58% of the crashes. Crashes in darkness on unlighted roadways accounted for 28 incidents.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field
Vehicles & Demographics
The age group most frequently involved in crashes was 26-34 years old, with 46 individuals recorded, followed by the 16-20 age group with 40 individuals. The most common vehicle makes involved were Ford (31 vehicles) and Chevrolet (37 vehicles, combining 'CHEVROLET' and 'CHEV'), followed by Dodge (26 vehicles, combining 'DODGE' and 'DODG').
Top Vehicle Makes (201 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (188 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events
Major Cause
The predominant major cause of crashes was an animal in the roadway, accounting for 102 incidents. Other significant causes included losing control of the vehicle, which was cited in 15 crashes, and driving too fast for conditions, which contributed to 7 crashes. Running off a straight road was also listed as the cause for 7 incidents.
Major Cause
Showing top 9 of 24 reported. 15 additional (22 total) not shown: FTYROW: Making left turn, Driver Distraction: Reaching for object(s)/fallen object(s), Ran off road - right, Exceeded authorized speed, Swerving/Evasive Action, Made improper turn, Driver Distraction: Exterior distraction, Driver Distraction: Talking on a hand-held device, Followed too close, FTYROW: From driveway, Driver Distraction: Adjusting devices (radio, climate), Operating vehicle in an reckless, erratic, careless, negligent manner, Passing: Where prohibited by signs/markings, Crossed centerline (undivided), Driver Distraction: Inattentive/lost in thought.
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 an animal, which occurred in 102 crashes. Collisions with another vehicle in traffic were the second most frequent event, with 24 occurrences. Crashes involving a fixed object, such as a ditch, accounted for 20 incidents, while overturns or rollovers were the first harmful event in 11 cases.
First Harmful Event
Showing top 9 of 15 reported. 6 additional (6 total) not shown: Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Embankment, Collision with fixed object: Fence, Collision with fixed object: Ground, Collision with fixed object: Guardrail - end, 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
The majority of crashes, 75 out of 95 with available data, occurred at non-intersection locations. This includes 68 crashes on straight or curved road segments without a special feature. Intersections accounted for 20 crashes, with T-intersections being the most common type, site of 10 incidents.
Roadway Junction / Feature
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 90 recorded. Sport utility vehicles (39) and light trucks or pickups (35) were also frequently involved. Tractor/semi-trailers were involved in 11 crashes, while one motorcycle was recorded.
Vehicle Type
"Other" combines 3 smaller categories (3 records): Farm equipment (explain in narrative) (1), All-terrain vehicle (ATV) (1), Motorcycle (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, 96 out of 122 with this data, occurred where no traffic controls were present. Stop signs were the most common form of traffic control at crash locations, present in 12 incidents. Ten crashes occurred in marked no-passing zones.
Traffic Control Device
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Most Damaged Area
The most frequently damaged area on vehicles was the front, which was the primary point of impact in 30 cases. Combined with front-corner impacts, frontal damage was noted in 62 vehicles. Damage to the top of the vehicle, often associated with rollovers, was the second most common category, recorded for 20 vehicles.
Most Damaged Area
"Other" combines 7 smaller categories (22 records): Driver side - middle (5), Driver side - front (4), Passenger side - middle (4), Rear - driver side corner (3), Undercarriage (3), Rear (2), Passenger side - rear (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Crashes by City
Within Louisa County, crash distribution was highest in Columbus Junction, which recorded 9 incidents. Wapello had the second-highest volume with 3 crashes. A number of crashes occurred outside of any specific city limits and are not included in this breakdown.
Crashes by City
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Paved vs Unpaved Road
Crashes predominantly occurred on paved roads, which accounted for 150 incidents. Unpaved surfaces, such as gravel or dirt roads, were the site of 19 crashes, making up 11.2% of the total where 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 a minority of crashes, a roadway factor was identified as a contributor. The most common factor was the surface condition, such as wet or icy roads, cited in 9 incidents. One crash was noted as occurring in a work zone.
Roadway Contributing Factor
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
The estimated property damage for the vast majority of crashes (149 incidents) fell within the $1,500 to $7,500 range. Twenty crashes resulted in damages estimated between $7,500 and $25,000. Three crashes were categorized as having high damage costs, 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
The most common type of crash was a non-collision event involving a single vehicle, such as running off the road or an overturn, which accounted for 118 incidents or 68.6% of all crashes. Among multi-vehicle crashes, the most frequent manners were same-direction sideswipes (9 crashes) and broadside collisions (7 crashes).
Manner of Collision
"Other" combines 1 smaller categories (1 records): Head-on (front to front) (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Pre-Crash Driver Action
Prior to the crash, the most common driver action was moving essentially straight, which was the case in 108 incidents. Turning left was the pre-crash action in 13 cases, and negotiating a curve was the action in 9 cases. These actions represent the driver's intended maneuver immediately before the incident.
Pre-Crash Driver Action
Showing top 9 of 12 reported. 3 additional (3 total) not shown: Legally Parked, Making U-turn, Accelerating in road.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 246 individuals involved in crashes, the vast majority (242 people, or 98.4%) were drivers. Passengers accounted for the remaining 4 individuals. No pedestrians or other non-occupant types were recorded in these incidents.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Across all 246 people involved in crashes, there was 1 fatality and 43 injuries. The injuries consisted of 8 serious injuries, 16 minor injuries, and 19 possible injuries. The remaining individuals were not reported as injured.
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 37 individuals for whom safety equipment use was specified, 32 were using a shoulder and lap belt. Four individuals were recorded as not using any safety equipment. One child was secured in a forward-facing child safety 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 were single-vehicle incidents, which accounted for 143 of the 172 total crashes, or 83.1%. The remaining 29 crashes involved two vehicles. No crashes involving three or more vehicles were 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: 172
- Total persons involved: 246
- Total vehicles involved: 201
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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2015-01-01 – 2015-12-31
Generated: September 9, 2026 · All rights reserved