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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
91 CRASHES IN
IOWA, IA
2015
In 2015, Keokuk County recorded 91 traffic crashes, resulting in 2 fatalities and 32 injuries. A significant statistical finding is that collisions with animals were the primary contributing factor, cited in 37 crashes, or 40.7% of the total. These incidents were predominantly single-vehicle, non-collision events.
91
Total Crash Events
2
Persons Killed
32
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, all traffic fatalities in Keokuk County were motorists, with 2 killed and 30 injured in crashes. No cyclists were killed or injured. While no pedestrians were killed, two pedestrians sustained injuries in traffic incidents during this period.
0
Pedestrians Killed
2
Motorists Killed
2
Pedestrians Injured
30
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
Crash analysis for Keokuk County in 2015 shows that Mondays were the most frequent day for incidents, with 22 of the 91 total crashes. The evening commute and post-dusk hours were peak times, with the hours of 5 p.m. and 7 p.m. each recording 10 crashes. While 34 crashes occurred during daylight, a combined 18 crashes happened in dark conditions, either on unlighted or lighted roadways.
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 91 crashes in Keokuk County, the majority (70.3%, or 64 crashes) resulted in no injuries. Crashes involving some level of injury—possible, minor, or serious—accounted for 27.5% of the total (25 crashes). Two fatal crashes occurred, representing 2.2% of all incidents and resulting in two 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 prevalent contributing factor in Keokuk County crashes was animals, which were cited in 37 incidents, accounting for 40.7% of all crashes. The second most common factor was losing control of the vehicle, noted in 10 crashes (11%). Other notable factors included driving too fast for conditions and running off the road, each contributing to 5 crashes.
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 substantial number of crashes in Keokuk County occurred in what appeared to be clear conditions. Specifically, 36 crashes (39.6%) happened in clear weather and on dry road surfaces. Daylight was the lighting condition for 34 crashes. Conversely, snow was a factor in 10 crashes, and 18 crashes took place in dark conditions.
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
Among the 154 individuals involved in crashes, the 16-20 age group was the most represented, with 38 people. The most frequently involved vehicle makes were Ford, with 25 vehicles, followed by Chevrolet (including 'CHEV' and 'CHEVROLET') with 20 vehicles, and GMC with 11 vehicles. Dodge vehicles were involved in 12 crashes.
Top Vehicle Makes (117 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 (111 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 in Keokuk County was interaction with an animal, cited in 37 incidents. Losing control of the vehicle was the second-most common cause, with 10 incidents. Driving too fast for conditions and running off a straight road were each listed as the major cause for 5 crashes.
Major Cause
Showing top 9 of 26 reported. 17 additional (21 total) not shown: Driver Distraction: Exterior distraction, Driver Distraction: Other interior distraction, FTYROW: Making left turn, Ran off road - left, Aggressive driving/road rage, FTYROW: From parked position, FTYROW: From stop sign, Equipment failure, Failed to keep in proper lane, Made improper turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Exceeded authorized speed, Other (explain in narrative): Vision obstructed, Passing: Where prohibited by signs/markings, Driver Distraction: Unrestrained animal, Followed too close, FTYROW: At uncontrolled intersection.
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 in Keokuk County crashes was a collision with an animal, which occurred in 37 incidents. The second most frequent event was a collision with another vehicle in traffic, recorded in 19 crashes. Run-off-road events were also notable, including 9 collisions with a ditch and 8 overturns or rollovers.
First Harmful Event
Showing top 9 of 14 reported. 5 additional (5 total) not shown: Collision with fixed object: Mailbox, Collision with fixed object: Snow bank, Collision with fixed object: Ground, Collision with: Other non-fixed object (explain in narrative), Collision with: Parked motor 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 in Keokuk County, 44 incidents, occurred at non-intersection locations. In contrast, 12 crashes took place at intersections, including 7 at four-way intersections and 3 at T-intersections. An additional 3 crashes occurred at driveway access points.
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, accounting for 41 vehicles. Light trucks and SUVs were also frequently involved, with 30 pickups and 24 sport utility vehicles recorded. Tractor/semi-trailers were involved in 6 crashes, and one motorcycle was involved in an incident.
Vehicle Type
"Other" combines 3 smaller categories (3 records): Passenger van (seats 9-15) (1), Farm equipment (explain in narrative) (1), Cargo/panel van (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, 69 incidents, occurred on roadway segments where no traffic controls were present. In 13 cases, a stop sign was the active traffic control device. A marked no-passing zone was the relevant control in 2 incidents.
Traffic Control Device
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 impact, recorded as the most damaged area on 24 vehicles. Side impacts were also frequent, with damage to the passenger side noted on 16 vehicles and the driver side on 8 vehicles. Rear damage was the primary point of impact for 7 vehicles.
Most Damaged Area
"Other" combines 8 smaller categories (17 records): Driver side - front (5), Driver side - middle (3), Passenger side - rear (3), Rear - passenger side corner (2), Undercarriage (1), Rear - driver side corner (1), Non-collision/no damage (1), Other (explain in narrative) (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Crashes by City
Crash distribution within Keokuk County shows that Sigourney had the highest volume with 10 crashes. Hedrick followed with 6 crashes, and Delta had 3. The towns of What Cheer, Martinsburg, Keota, and South English each recorded one crash.
Crashes by City
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Paved vs Unpaved Road
In Keokuk County, 80 crashes occurred on paved roads. A notable portion, 11 crashes or 12.1% of the total, took place on unpaved surfaces such as gravel or dirt roads, reflecting the area's rural 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
Among roadway-related contributing factors, adverse surface conditions such as wet or icy roads were cited in 14 crashes. An additional crash was attributed to a slippery, loose, or worn surface. For the majority of crashes, no roadway factor was cited.
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 noted as something other than 'apparently normal,' the most frequent issues were being asleep/fatigued or under the influence of alcohol, each recorded for 4 drivers. Illness or fainting was noted as a condition for 2 drivers involved in crashes.
Driver Condition
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 - $7,500' range, which applied to 55 crashes. Twenty-six crashes resulted in damages between $7,500 and $25,000, while 5 crashes involved severe damages 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 incidents, categorized as 'Non-collision,' were the dominant crash type, accounting for 54 of the 91 total crashes (59.3%). The most common multi-vehicle crash type was a broadside collision, which occurred 12 times (13.2%). Rear-end collisions were recorded in 6 incidents.
Manner of Collision
"Other" combines 1 smaller categories (1 records): Angle, oncoming left turn (1).
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Pre-Crash Driver Action
The vast majority of vehicles involved in crashes, 68 in total, were moving straight ahead just prior to the incident. The next most frequent pre-crash action was turning left, which was recorded for 6 vehicles. All other documented actions, such as turning right or backing, were noted in three or fewer instances each.
Pre-Crash Driver Action
Showing top 9 of 13 reported. 4 additional (4 total) not shown: Slowing/stopping (deceleration), Stopped in traffic, Entering traffic lane (merging), Making U-turn.
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records
Person Type
Of the 154 people involved in crashes, the great majority, 144, were drivers of vehicles. Passengers accounted for 8 of the individuals involved. Additionally, 2 pedestrians were involved in crashes during this period.
Person Type
Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Crash-level records
Person Injury Severity
Across all 154 individuals involved in crashes, 34 people sustained some level of injury or were killed. This includes 2 fatalities, 4 serious injuries, 15 minor injuries, and 13 possible injuries. The majority of people involved did not sustain a documented injury.
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 available data for vehicle occupants, at least 6 individuals were not using any safety equipment at the time of their crash. In contrast, 19 occupants were recorded as having used both a shoulder and lap belt. Data on safety equipment use was not available for all participants.
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 in Keokuk County, with 67 such events recorded. Crashes involving two vehicles occurred 22 times. There were also 2 crashes 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: 91
- Total persons involved: 154
- Total vehicles involved: 117
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