Yearly Traffic Safety Analysis

82 CRASHES IN
IOWA, IA
2015

In 2015, Van Buren County recorded 82 traffic crashes, resulting in 0 fatalities and 39 injuries. A significant portion of these incidents, approximately 26.8%, were attributed to collisions with animals, which was the single most common contributing factor.

82

Total Crash Events

0

Persons Killed

39

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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, there were no fatalities among any road users in Van Buren County. A total of 36 motorists were injured in crashes. Additionally, one pedestrian and one cyclist sustained injuries in separate incidents.

0

Pedestrians Killed

0

Cyclists Killed

0

Motorists Killed

0

Other Killed

1

Pedestrians Injured

1

Cyclists Injured

36

Motorists Injured

1

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 Van Buren County during 2015 peaked on Saturdays, which saw 20 incidents. The busiest times of day were the 10 a.m. and 3 p.m. hours, each recording 7 crashes. Overall, 42 crashes occurred during daylight, while 33 took place in dark, dusk, or dawn conditions.

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, 54 out of 82 (65.9%), resulted in no injuries. Injury-related crashes accounted for the remaining 34.1% of incidents, with 8 classified as serious injury, 10 as minor injury, and 10 as possible injury. There were no fatal crashes recorded in 2015, and consequently, no persons were killed.

Outcome by Severity (Crash Events)

Serious Injury8serious injury crashes9.8%
Minor Injury10minor injury crashes12.2%
Possible Injury10possible injury crashes12.2%
No Injury54no injury crashes65.9%

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 for crashes was animals, cited in 22 incidents (26.8%). The second most common factor was losing control of the vehicle, which accounted for 17 crashes (20.7%). Other notable factors included running off the road while driving straight (7 crashes) and failure to yield the right-of-way from a stop sign (4 crashes).

Officer-Reported Primary Contributing Cause

Animal22 (26.8%)
Lost Control17 (20.7%)
Ran off road - straight7 (8.5%)
FTYROW: From stop sign4 (4.9%)
Driving too fast for conditions3 (3.7%)
Operating vehicle in an reckless, erratic, careless, negligent manner3 (3.7%)
Ran Stop Sign2 (2.4%)
FTYROW: Making left turn2 (2.4%)
Driver Distraction: Other interior distraction2 (2.4%)
Driver Distraction: Talking on a hand-held device1 (1.2%)

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 incidents happening in clear weather and 56 on dry road surfaces. Daylight conditions were present for 42 crashes. Adverse conditions were less frequent, with 10 crashes occurring on cloudy days and 4 on wet or rainy roads, while crashes on snow, ice, or slush-covered roads accounted for a combined 9 incidents.

Weather

Clear58 (79.5%)
Cloudy10 (13.7%)
Rain2 (2.7%)
Snow2 (2.7%)
Sleet, hail1 (1.4%)

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

Lighting

Daylight42 (56.0%)
Dark - roadway not lighted20 (26.7%)
Dusk8 (10.7%)
Dark - roadway lighted3 (4.0%)
Dawn2 (2.7%)

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

Road Surface

Dry56 (74.7%)
Snow6 (8.0%)
Gravel5 (6.7%)
Wet4 (5.3%)
Ice/frost2 (2.7%)
Slush1 (1.3%)
Sand1 (1.3%)

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 55-64 age group was the most represented, with 30 individuals, followed by the 65+ age group with 26 individuals. Among the 106 vehicles involved, Ford was the most frequent make with 23 vehicles. Chevrolet vehicles accounted for 20, and Toyota for 10.

Top Vehicle Makes (106 vehicles)

1
FORD23 (21.7%)
2
CHEV10 (9.4%)
3
CHEVROLET10 (9.4%)
4
TOYOTA5 (4.7%)
5
JEEP5 (4.7%)
6
DODGE5 (4.7%)
7
TOYT5 (4.7%)
8
MERCURY4 (3.8%)
9
BUICK4 (3.8%)
10
GMC4 (3.8%)

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

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

Sex Distribution (94 persons with recorded sex)

Male66 (70.2%)
Female28 (29.8%)

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 cited major cause of crashes was an animal on the roadway, contributing to 22 incidents. The second leading cause was a driver losing control of their vehicle, which was a factor in 17 crashes. Other significant causes included running off a straight road (7 crashes) and failure to yield the right-of-way from a stop sign (4 crashes).

Major Cause

1
Animal22 (29.3%)
2
Lost Control17 (22.7%)
3
Ran off road - straight7 (9.3%)
4
FTYROW: From stop sign4 (5.3%)
5
Driving too fast for conditions3 (4%)
6
Operating vehicle in an reckless, erratic, careless, negligent manner3 (4%)
7
Ran Stop Sign2 (2.7%)
8
FTYROW: Making left turn2 (2.7%)
9
Driver Distraction: Other interior distraction2 (2.7%)

Showing top 9 of 22 reported. 13 additional (13 total) not shown: Driver Distraction: Talking on a hand-held device, Operator inexperience, Other (explain in narrative): Other, Passing: Other passing (explain in narrative), Ran off road - left, Driver Distraction: Adjusting devices (radio, climate), Swerving/Evasive Action, Made improper turn, Exceeded authorized speed, FTYROW: From parked position, FTYROW: To pedestrian, Improper Backing, 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, recorded in 22 crashes. This was followed by collisions with another vehicle in traffic, which occurred in 17 incidents. Run-off-road events were also prominent, with 13 crashes involving a ditch as the first harmful event and 8 resulting in an overturn or rollover.

First Harmful Event

1
Collision with: Animal22 (27.2%)
2
Collision with: Vehicle in traffic17 (21%)
3
Collision with fixed object: Ditch13 (16%)
4
Non-collision events: Overturn/rollover8 (9.9%)
5
Collision with: Non-motorist (see non-motorist section - NOT a unit)3 (3.7%)
6
Non-collision events: Other non-collision (explain in narrative)2 (2.5%)
7
Collision with: Parked motor vehicle2 (2.5%)
8
Non-collision events: Non-contact vehicle (phantom)2 (2.5%)
9
Collision with fixed object: Embankment2 (2.5%)

Showing top 9 of 19 reported. 10 additional (10 total) not shown: Collision with fixed object: Cable barrier, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Building, Miscellaneous events: Hit and run, Collision with fixed object: Bridge/bridge rail parapet, Non-collision events: Vehicle went airborne, Other (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Traffic sign support, Collision with fixed object: Utility pole/light support.

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

Roadway Junction / Feature

The vast majority of crashes, 58 out of 82, occurred at non-intersection locations, with 50 of these happening on a standard road segment. In contrast, 18 crashes took place at intersections, including 10 at four-way intersections and 7 at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature50 (65.8%)
2
Intersection: Four-way intersection10 (13.2%)
3
Intersection: T-intersection7 (9.2%)
4
Non-intersection: Driveway access (related, not in)4 (5.3%)
5
Non-intersection: Driveway access (within)3 (3.9%)
6
Non-intersection: Other non-intersection (explain in narrative)1 (1.3%)
7
Intersection: Y-intersection1 (1.3%)

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 48 of the vehicles. Light trucks and pickups were the second most frequent with 24 vehicles, followed by sport utility vehicles with 15. Motorcycles were involved in 4 crashes, and tractor/semi-trailers were involved in 3.

Vehicle Type

"Other" combines 3 smaller categories (3 records): Passenger van (seats 9-15) (1), School bus (seats > 15) (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

For the vehicles involved in crashes, the vast majority (84) were in areas with no traffic controls present. Stop signs were the traffic control device in place for 12 vehicles. Only one vehicle was noted in an area with a marked no-passing zone.

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 damage, with 18 vehicles sustaining damage to the front center and another 16 to the front corners. Damage to the side of the vehicle was also significant, recorded for 24 vehicles. Rollovers likely account for the 9 vehicles with 'Top' as the most damaged area.

Most Damaged Area

"Other" combines 9 smaller categories (19 records): Driver side - front (4), Driver side - rear (3), Non-collision/no damage (2), Passenger side - rear (2), Rear (2), Rear - passenger side corner (2), Other (explain in narrative) (2), Undercarriage (1), Rear - driver side corner (1).

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

Crashes by City

Within Van Buren County, Keosauqua had the highest number of reported crashes with 7. Bonaparte followed with 4 crashes, and Farmington recorded 3. Other municipalities with crashes included Cantril with 2, and both Calmar and Milton with 1 each.

Crashes by City

1
KEOSAUQUA7 (38.9%)
2
BONAPARTE4 (22.2%)
3
FARMINGTON3 (16.7%)
4
CANTRIL2 (11.1%)
5
CALMAR1 (5.6%)
6
MILTON1 (5.6%)

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

Paved vs Unpaved Road

Crashes were predominantly on paved roads, which accounted for 68 incidents. However, a notable portion, 14 crashes or approximately 17.1%, occurred on unpaved surfaces such as gravel or dirt roads, reflecting the county's secondary road network.

Paved vs Unpaved Road

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

Driver Condition

While most drivers were recorded as 'apparently normal,' a specific condition was noted for 14 drivers involved in crashes. Ten drivers were suspected of being under the influence of alcohol. An additional 3 drivers were noted as being asleep or fatigued, and one was suspected of being under the influence of drugs or medication.

Driver Condition

1
Under the influence of alcohol10 (71.4%)
2
Asleep/fatigued3 (21.4%)
3
Under the influence of drugs/meds1 (7.1%)

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 frequently in the $1,500 to $7,500 range, which applied to 57 crashes. A further 21 crashes resulted in damage estimated between $7,500 and $25,000. 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

The vast majority of incidents, 58 out of 82 (70.7%), were single-vehicle, non-collision events, such as running off the road or overturning. Among multi-vehicle crashes, the most common type was a broadside collision, which occurred 6 times. Rear-end and same-direction sideswipe collisions each accounted for 5 crashes.

Manner of Collision

"Other" combines 1 smaller categories (1 records): Other (explain in narrative) (1).

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

Pre-Crash Driver Action

The predominant pre-crash action for vehicles was moving essentially straight, which was the case for 71 vehicles. Turning left was the action for 12 vehicles prior to impact. Other actions such as overtaking, backing, and negotiating a curve were each recorded for 4 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight71 (69.6%)
2
Turning left12 (11.8%)
3
Overtaking/passing4 (3.9%)
4
Backing4 (3.9%)
5
Negotiating a curve4 (3.9%)
6
Legally Parked4 (3.9%)
7
Turning right2 (2%)
8
Other (explain in narrative)1 (1%)

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

Person Type

Of the 145 people involved in crashes, the overwhelming majority, 131, were drivers. There were 11 passengers involved in these incidents. The remaining individuals included one pedestrian, one bicyclist, and one other non-motorist.

Person Type

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

Person Injury Severity

Across all 145 individuals involved in crashes, a total of 39 people sustained injuries. Of those injured, 12 suffered serious injuries, 14 had minor injuries, and 13 had possible injuries. No fatalities were recorded among any persons involved.

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 individuals for whom safety equipment use was recorded, 17 were using both a shoulder and lap belt. Six individuals were recorded as using no safety equipment at all. Additionally, two people were using a DOT-compliant helmet.

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

A significant majority of crashes, 59 out of 82 (72%), involved only a single vehicle. Two-vehicle collisions accounted for 22 incidents. There was one crash reported 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: 82
  • Total persons involved: 145
  • Total vehicles involved: 106

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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