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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
230 CRASHES IN
IOWA, IA
2015
In 2015, Appanoose County recorded 230 traffic crashes, which resulted in 2 fatalities and 109 injuries. A significant portion of these incidents involved a single vehicle, with collisions involving animals being the most frequently cited contributing factor, accounting for 26.5% of all crashes.
230
Total Crash Events
2
Persons Killed
109
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 Appanoose County crashes. A total of 2 motorists were killed and 106 were injured. Among vulnerable road users, there were no fatalities; however, 2 pedestrians and 1 cyclist sustained injuries.
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
106
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 Appanoose County occurred most frequently on Fridays, which saw 61 incidents in 2015. The peak time for crashes was the 6 p.m. hour with 16 events, a count also matched by the noon hour. Overall, more crashes happened during daylight hours (112) than in dark or low-light conditions (72).
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
The majority of crashes, 63.5% (146 incidents), resulted in no injuries. Collisions involving an injury of any severity—from possible to fatal—accounted for 36.5% of incidents. There were 2 fatal crashes recorded, which resulted in a total of 2 fatalities.
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 most common contributing factor cited in crashes was an animal, which was involved in 61 incidents, or 26.5% of the total. Following this, 'Lost Control' was a factor in 24 crashes (10.4%). Other significant factors included running off the road, which collectively accounted for 28 crashes between running off to the left, right, or straight.
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 ideal driving conditions, with 61.3% (141 crashes) happening on dry roads and 55.7% (128 crashes) in clear weather. Crashes during daylight hours accounted for 48.7% (112) of all incidents. Adverse weather conditions such as rain or snow were present in a smaller number of crashes, with rain being the most frequent among them at 12 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
Analysis of persons involved in crashes shows the 16-20 age group was the most represented, with 83 individuals, followed by the 26-34 age group with 78 individuals. Among the 327 vehicles involved, Chevrolet was the most frequent make with 70 vehicles, followed by Ford with 60 and Dodge with 40.
Top Vehicle Makes (327 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (291 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 leading major cause of crashes was interaction with an animal, cited in 61 incidents (26.5% of total). 'Lost Control' was the second most frequent cause, contributing to 24 crashes (10.4%). Other notable causes included running off the road (28 incidents combined) and driver distraction from an interior source (11 incidents).
Major Cause
Showing top 9 of 34 reported. 25 additional (70 total) not shown: Other (explain in narrative): Other, Driving too fast for conditions, FTYROW: Making left turn, Driver Distraction: Exterior distraction, Swerving/Evasive Action, Driver Distraction: Inattentive/lost in thought, Driver Distraction: Passenger, Operating vehicle in an reckless, erratic, careless, negligent manner, Followed too close, FTYROW: From driveway, FTYROW: Other (explain in narrative), Made improper turn, Ran Traffic Signal, Equipment failure, FTYROW: At uncontrolled intersection, Passing: On wrong side, Passing: Other passing (explain in narrative), Passing: Through/around barrier, Ran off road - right, Failed to yield to emergency vehicle, Aggressive driving/road rage, Driver Distraction: Other electronic device activity, Operator inexperience, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed.
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 76 crashes. The second most frequent event was a collision with an animal, which initiated 60 crashes. Collisions with fixed objects, such as a ditch (19 crashes), tree (6 crashes), or utility pole (6 crashes), were also a significant category of initial impacts.
First Harmful Event
Showing top 9 of 28 reported. 19 additional (28 total) not shown: Collision with fixed object: Curb/island/raised median, Other (explain in narrative), Collision with fixed object: Fence, Non-collision events: Vehicle went airborne, Collision with: Non-motorist (see non-motorist section - NOT a unit), Non-collision events: Other non-collision (explain in narrative), Collision with: Thrown or falling object, Miscellaneous events: Hit and run, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Guardrail - face, Collision with fixed object: Mailbox, Collision with fixed object: Other fixed object (explain in narrative), 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 - end, Collision with: Struck/struck by object/cargo/person from other vehicle.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Junction / Feature
The majority of crashes occurred at non-intersection locations, with 105 incidents recorded on road segments with no special feature. Crashes at intersections were less common, with four-way intersections being the most frequent type, accounting for 26 incidents, followed by T-intersections with 19 incidents. Driveway-related crashes accounted for another 20 incidents.
Roadway Junction / Feature
Showing top 9 of 11 reported. 2 additional (2 total) not shown: Non-intersection: Railroad grade crossing, Non-intersection: Crossover-related.
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 137 of the 327 vehicles. Light trucks and pickups were the second most common with 72 vehicles, followed by sport utility vehicles with 65. Commercial tractor-trailers were involved in 8 incidents, and motorcycles were involved in 5.
Vehicle Type
"Other" combines 8 smaller categories (13 records): Passenger van (seats 9-15) (3), All-terrain vehicle (ATV) (2), Cargo/panel van (2), Single-unit truck (>= 3 axles) (2), Golf cart (1), Farm tractor (1), Farm equipment (explain in narrative) (1), Other light truck (<=10000 lbs) (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Traffic Control Device
The vast majority of crashes, 210 incidents, occurred where no traffic controls were present. Stop signs were the most common form of traffic control at crash locations where a device was present, noted in 33 incidents. Traffic signals were a factor in 19 crashes.
Traffic Control Device
"Other" combines 2 smaller categories (3 records): Work zone sign (2), Railway crossing device (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 damage, recorded on 69 vehicles, with an additional 53 vehicles damaged on a front corner. Side impacts were also frequent, while damage to the rear of the vehicle was noted in 19 instances, suggesting a notable share of rear-end collisions.
Most Damaged Area
"Other" combines 9 smaller categories (79 records): Rear - passenger side corner (14), Driver side - front (14), Passenger side - front (11), Rear - driver side corner (11), Top (11), Other (explain in narrative) (8), Passenger side - rear (6), Non-collision/no damage (3), Undercarriage (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Crashes by City
Within Appanoose County, the city of Centerville accounted for the largest number of crashes with 90 incidents. The town of Moulton recorded the next highest volume with 8 crashes. Following them were Moravia and Mystic, each with 4 reported crashes.
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 on paved roads were far more common, accounting for 193 incidents. However, a notable 36 crashes, or approximately 15.7% of the total where surface type was recorded, occurred on unpaved surfaces such as gravel or dirt roads.
Paved vs Unpaved Road
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Roadway Contributing Factor
Roadway factors were cited as contributors in a minority of crashes. The most common factor was the road surface condition, such as being wet or icy, noted in 9 incidents. Work zones were a contributing factor in 6 crashes, and a slippery or loose surface was noted in 4 crashes.
Roadway Contributing Factor
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Driver Condition
In cases where a driver's condition was recorded as something other than 'apparently normal,' being under the influence of alcohol was the most frequent, noted for 11 drivers. Emotional state, such as anger or depression, was cited for 6 drivers, and fatigue or falling asleep was a factor for 3 drivers.
Driver Condition
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Property Damage
The estimated property damage was most commonly in the $1,500 to $7,500 range, which applied to 188 crashes, or 81.7% of the total. A smaller number of crashes resulted in higher damage, with 29 incidents falling in the $7,500 to $25,000 range and 2 crashes exceeding $25,000 in estimated damage.
Property Damage
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Manner of Collision
Nearly half of all crashes, 107 incidents or 46.5%, were non-collision events involving a single vehicle, such as running off the road or overturning. Among multi-vehicle crashes, rear-end collisions were the most frequent type, accounting for 36 incidents (15.7%). Broadside collisions were the next most common, with 18 reported cases.
Manner of Collision
"Other" combines 3 smaller categories (12 records): Rear to side (5), Head-on (front to front) (5), 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 was moving essentially straight, which was the case for 180 vehicles. Turning left was the second most frequent action, recorded for 26 vehicles. Backing was also a notable pre-crash maneuver, involved in 23 instances.
Pre-Crash Driver Action
Showing top 9 of 13 reported. 4 additional (11 total) not shown: Slowing/stopping (deceleration), Accelerating in road, Entering traffic lane (merging), Changing lanes.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 440 individuals involved in crashes, the vast majority were drivers, accounting for 407 people. Passengers made up the next largest group with 30 individuals. A small number of non-motorists were also involved, including 2 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
Among all persons for whom an injury status was recorded, 2 individuals sustained fatal injuries. An additional 109 people were injured, with 16 classified as serious, 42 as minor, and 51 as possible injuries. Only 2 individuals in this group were explicitly recorded as having 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 limited data available for safety equipment usage, 70 individuals were recorded as using a shoulder and lap belt. A notable 17 individuals were documented as using no safety equipment at all. This represents 18.9% of the occupants for whom restraint use was specified.
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 of incident, accounting for 135 crashes or 58.7% of the total. Crashes involving two vehicles were also frequent, with 93 incidents. There were only two crashes recorded that involved three 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: 230
- Total persons involved: 440
- Total vehicles involved: 327
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