Yearly Traffic Safety Analysis

55 CRASHES IN
IOWA, IA
2015

In 2015, Adams County recorded 55 traffic crashes, resulting in one fatality and 18 injuries. A significant finding from the data is the high frequency of collisions involving animals, which were cited as a contributing factor in 29.1% of all crashes. The single fatal crash occurred in August.

55

Total Crash Events

1

Persons Killed

18

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

All crash casualties involved motor vehicle occupants, as there were no recorded fatalities or injuries involving pedestrians or cyclists. In total, one motorist was killed and 18 motorists were injured during this period.

1

Motorists Killed

18

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 occurrences peaked on Thursdays, with 11 incidents recorded on this day of the week. The evening hour of 9 PM was the single most frequent time for crashes, accounting for 9 events. August saw the highest monthly crash total with 9 incidents, including the year's only fatality.

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

Out of 55 total crashes, 18 incidents resulted in an injury or fatality, while the majority, 67.3% (37 crashes), involved no injuries. One crash was classified as fatal, leading to one death. An additional 17 crashes resulted in either minor or possible injuries.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.8%
Minor Injury3minor injury crashes5.5%
Possible Injury14possible injury crashes25.5%
No Injury37no injury crashes67.3%

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

Encounters with animals were the leading contributing factor, cited in 16 crashes, which constitutes 29.1% of all incidents. Speed-related issues were also prominent, with 'Exceeded authorized speed' noted in 6 crashes (10.9%) and 'Driving too fast for conditions' in another 3 crashes (5.5%).

Officer-Reported Primary Contributing Cause

Animal16 (29.1%)
Exceeded authorized speed6 (10.9%)
Ran off road - straight3 (5.5%)
Ran off road - left3 (5.5%)
Driving too fast for conditions3 (5.5%)
FTYROW: At uncontrolled intersection2 (3.6%)
Lost Control2 (3.6%)
Other (explain in narrative): Other2 (3.6%)
Followed too close2 (3.6%)
Ran Stop Sign2 (3.6%)

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 58.2% happening in daylight and 63.6% on dry road surfaces. Clear weather was reported for 26 of the 55 crashes. Adverse conditions were less frequent, with rain present in 5 crashes and snow or ice contributing to 3 incidents.

Weather

Clear26 (55.3%)
Cloudy14 (29.8%)
Rain5 (10.6%)
Freezing rain/drizzle1 (2.1%)
Fog, smoke, smog1 (2.1%)

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

Lighting

Daylight32 (68.1%)
Dark - roadway not lighted10 (21.3%)
Dusk4 (8.5%)
Dark - roadway lighted1 (2.1%)

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

Road Surface

Dry35 (74.5%)
Wet5 (10.6%)
Gravel3 (6.4%)
Snow2 (4.3%)
Ice/frost1 (2.1%)
Mud, dirt1 (2.1%)

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

Vehicles & Demographics

The most frequently involved vehicle makes were Ford (17 vehicles), Chevrolet (14 vehicles), and Dodge (9 vehicles). Among the 96 individuals involved in crashes, the 65+ age group was the largest demographic with 18 people, followed closely by the 16-20 age group with 16 people.

Top Vehicle Makes (74 vehicles)

1
FORD17 (23%)
2
DODG7 (9.5%)
3
CHEV7 (9.5%)
4
CHEVROLET7 (9.5%)
5
PONT5 (6.8%)
6
BUIC3 (4.1%)
7
OLDS2 (2.7%)
8
PONTIAC2 (2.7%)
9
PETERBILT2 (2.7%)
10
HONDA2 (2.7%)

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

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

Sex Distribution (68 persons with recorded sex)

Male37 (54.4%)
Female31 (45.6%)

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 attributed to crashes was an animal in the roadway, accounting for 16 incidents. 'Exceeded authorized speed' was the second-leading cause with 6 crashes. Other significant causes included running off the road and driving too fast for conditions, each cited in 3 crashes.

Major Cause

1
Animal16 (29.6%)
2
Exceeded authorized speed6 (11.1%)
3
Ran off road - straight3 (5.6%)
4
Ran off road - left3 (5.6%)
5
Driving too fast for conditions3 (5.6%)
6
FTYROW: At uncontrolled intersection2 (3.7%)
7
Lost Control2 (3.7%)
8
Other (explain in narrative): Other2 (3.7%)
9
Followed too close2 (3.7%)

Showing top 9 of 23 reported. 14 additional (15 total) not shown: Ran Stop Sign, Passing: Other passing (explain in narrative), Ran off road - right, Separation of units, Swerving/Evasive Action, Driver Distraction: Other electronic device activity, Driver Distraction: Other interior distraction, Driver Distraction: Reaching for object(s)/fallen object(s), Failed to keep in proper lane, FTYROW: From parked position, FTYROW: From stop sign, FTYROW: Making left turn, FTYROW: Other (explain in narrative), Other (explain in narrative): No improper action.

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

First Harmful Event

The most frequent initial event in a crash sequence was a collision with an animal, which occurred in 16 incidents. The second most common event was a collision with another vehicle in traffic, documented in 13 crashes. Run-off-road events also occurred, leading to collisions with a ditch (5 crashes) or an overturn (4 crashes).

First Harmful Event

1
Collision with: Animal16 (30.2%)
2
Collision with: Vehicle in traffic13 (24.5%)
3
Collision with fixed object: Ditch5 (9.4%)
4
Non-collision events: Overturn/rollover4 (7.5%)
5
Other (explain in narrative)3 (5.7%)
6
Collision with: Parked motor vehicle2 (3.8%)
7
Non-collision events: Other non-collision (explain in narrative)2 (3.8%)
8
Collision with: Other non-fixed object (explain in narrative)2 (3.8%)
9
Collision with fixed object: Tree1 (1.9%)

Showing top 9 of 14 reported. 5 additional (5 total) not shown: Collision with fixed object: Ground, Non-collision events: Vehicle went airborne, Collision with fixed object: Building, Collision with: Re-entering roadway, 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, 35 out of 55, occurred at non-intersection locations. Intersections accounted for 13 crashes, with 8 of those taking place at four-way intersections and 5 at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature33 (68.8%)
2
Intersection: Four-way intersection8 (16.7%)
3
Intersection: T-intersection5 (10.4%)
4
Non-intersection: Alley1 (2.1%)
5
Non-intersection: Other non-intersection (explain in narrative)1 (2.1%)

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 collisions, accounting for 34 of the 74 vehicles documented. Four-tire light trucks and pickups were the second most prevalent with 18 vehicles, followed by sport utility vehicles with 8. Three tractor-trailers and one motorcycle were also involved in crashes.

Vehicle Type

"Other" combines 3 smaller categories (3 records): Passenger van (seats 9-15) (1), Single unit truck (2-axle, 6-tire) (1), Single-unit truck (>= 3 axles) (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 occurred in areas where no traffic controls were present, a situation noted in 52 instances. For crashes where traffic controls were a factor, stop signs were the most common device, present in 11 instances.

Traffic Control Device

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, recorded for 14 vehicles. Rear impacts, often indicative of rear-end collisions, were the second most frequent with 7 instances, followed by impacts to the front-passenger side corner, also with 7 instances.

Most Damaged Area

"Other" combines 8 smaller categories (17 records): Other (explain in narrative) (3), Driver side - middle (3), Driver side - front (3), Passenger side - middle (2), Passenger side - front (2), Driver side - rear (2), Non-collision/no damage (1), Rear - passenger side corner (1).

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

Crashes by City

Crashes were most concentrated in Corning, which saw 18 incidents, followed by Prescott with 6 and Nodaway with 2. A significant portion of crashes, 29 out of the total 55, occurred in unincorporated areas outside of these listed municipalities.

Crashes by City

1
CORNING18 (69.2%)
2
PRESCOTT6 (23.1%)
3
NODAWAY2 (7.7%)

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 48 of the 55 total incidents. Seven crashes, representing 12.7% of the total, took place 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

Property Damage

The most common estimated property damage cost fell within the $1,500 to $7,500 range, which was assigned to 36 crashes. Sixteen crashes resulted in damages estimated between $7,500 and $25,000, while only one crash was 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 were the dominant crash type, accounting for 34 incidents, or 61.8% of the total. Among multi-vehicle crashes, the most common type was a rear-end collision, which occurred in 7 incidents (12.7%).

Manner of Collision

"Other" combines 2 smaller categories (2 records): Sideswipe, opposite direction (1), 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 most common action for vehicles immediately before a crash was moving straight ahead, which was the case for 47 of the 74 vehicles involved. Turning left was the next most frequent pre-crash action, recorded for 6 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight47 (68.1%)
2
Turning left6 (8.7%)
3
Legally Parked4 (5.8%)
4
Overtaking/passing3 (4.3%)
5
Backing2 (2.9%)
6
Slowing/stopping (deceleration)2 (2.9%)
7
Stopped in traffic2 (2.9%)
8
Turning right2 (2.9%)
9
Other (explain in narrative)1 (1.4%)

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

Person Type

Of the 96 individuals involved in crashes, the vast majority were drivers, accounting for 91 people. The remaining 5 individuals were passengers. No other person types, such as pedestrians or cyclists, were recorded in any crash.

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 19 people sustained injuries or were killed in crashes during this period. This included one fatality, 4 individuals with minor injuries, and 14 with possible injuries. The remaining individuals involved were not 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 small subset of 15 vehicle occupants for whom safety equipment use was recorded, 10 were noted as using a shoulder and lap belt. However, 5 individuals in this group were recorded as using no safety equipment at all.

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 frequent type, accounting for 37 of the 55 incidents (67.3%). Crashes involving two vehicles occurred 17 times, and there was one reported crash 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: 55
  • Total persons involved: 96
  • Total vehicles involved: 74

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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