Yearly Traffic Safety Analysis

69 CRASHES IN
IOWA, IA
2015

In 2015, Butler County recorded 69 traffic crashes, resulting in 1 fatality and 27 injuries. A notable finding from the data is the high proportion of single-vehicle incidents, which accounted for 29 of the total crashes, representing 42% of all collisions.

69

Total Crash Events

1

Persons Killed

27

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 Butler County involved motorists. There was one motorist killed and a total of 27 motorists injured in crashes. No fatalities or injuries were reported for pedestrians or cyclists during this period.

1

Motorists Killed

27

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 in Butler County showed distinct temporal patterns in 2015. Fridays were the most frequent day for crashes, with 16 incidents, followed by Saturday with 14. The single busiest hour for crashes was 3 PM, which saw 14 collisions, while 43 of the 69 total incidents (62.3%) happened during daylight hours.

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 69 crashes in Butler County, a majority (68.1%, or 47 crashes) resulted in no injuries. Crashes involving injuries accounted for 31.9% of the total, distributed among serious (1 crash), minor (7 crashes), and possible injuries (13 crashes). There was one fatal crash recorded during this period, which resulted in one fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.4%
Serious Injury1serious injury crashes1.4%
Minor Injury7minor injury crashes10.1%
Possible Injury13possible injury crashes18.8%
No Injury47no injury crashes68.1%

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

Analysis of contributing factors indicates that 'Driving too fast for conditions' was the most cited cause, attributed to 9 of the 69 crashes (13%). Other significant factors included 'Ran off road - straight' and 'Lost Control', each accounting for 6 crashes (8.7%). Collisions involving an animal and reckless or erratic operation were each noted in 5 crashes.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions9 (13%)
Ran off road - straight6 (8.7%)
Lost Control6 (8.7%)
Animal5 (7.2%)
Operating vehicle in an reckless, erratic, careless, negligent manner5 (7.2%)
Ran Stop Sign4 (5.8%)
FTYROW: From parked position3 (4.3%)
FTYROW: Making left turn3 (4.3%)
FTYROW: Other (explain in narrative)3 (4.3%)
Driver Distraction: Exterior distraction2 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in 2015 occurred under ideal environmental conditions. Specifically, 48 crashes (69.6%) happened in clear weather, 45 (65.2%) on dry road surfaces, and 43 (62.3%) during daylight hours. Adverse conditions were less frequent, with snow being a factor in 6 crashes and wet roads in 5.

Weather

Clear48 (72.7%)
Snow6 (9.1%)
Cloudy6 (9.1%)
Rain3 (4.5%)
Freezing rain/drizzle1 (1.5%)
Blowing Snow1 (1.5%)
Blowing sand, soil, dirt1 (1.5%)

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

Lighting

Daylight43 (64.2%)
Dark - roadway not lighted16 (23.9%)
Dark - roadway lighted5 (7.5%)
Dusk2 (3.0%)
Dawn1 (1.5%)

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

Road Surface

Dry45 (67.2%)
Gravel7 (10.4%)
Wet5 (7.5%)
Snow4 (6.0%)
Ice/frost4 (6.0%)
Slush1 (1.5%)
Water (standing or moving)1 (1.5%)

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

Vehicles & Demographics

Demographically, individuals aged 16-20 and 21-25 were the most frequently involved in crashes, with 24 persons from each group recorded among the 136 total people. An analysis of the 108 vehicles involved shows that Chevrolet was the most common make with 27 vehicles, followed by Ford with 18 and Dodge with 12.

Top Vehicle Makes (108 vehicles)

1
CHEVROLET27 (25%)
2
FORD18 (16.7%)
3
DODGE12 (11.1%)
4
CHEV5 (4.6%)
5
FREIGHTLINER4 (3.7%)
6
BUICK3 (2.8%)
7
CHRYSLER3 (2.8%)
8
OLDSMOBILE3 (2.8%)
9
OLDS2 (1.9%)
10
JEEP2 (1.9%)

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 (102 persons with recorded sex)

Male72 (70.6%)
Female30 (29.4%)

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

Major Cause

According to Iowa DOT coding, the leading major cause of crashes was 'Driving too fast for conditions,' cited in 9 incidents. This was followed by 'Ran off road - straight' and 'Lost Control,' each contributing to 6 crashes. Encounters with animals and reckless vehicle operation were each listed as the major cause for 5 crashes.

Major Cause

1
Driving too fast for conditions9 (13.6%)
2
Ran off road - straight6 (9.1%)
3
Lost Control6 (9.1%)
4
Animal5 (7.6%)
5
Operating vehicle in an reckless, erratic, careless, negligent manner5 (7.6%)
6
Ran Stop Sign4 (6.1%)
7
FTYROW: From parked position3 (4.5%)
8
FTYROW: Making left turn3 (4.5%)
9
FTYROW: Other (explain in narrative)3 (4.5%)

Showing top 9 of 25 reported. 16 additional (22 total) not shown: Driver Distraction: Exterior distraction, Made improper turn, Ran off road - left, Other (explain in narrative): Vision obstructed, Followed too close, FTYROW: At uncontrolled intersection, Crossed centerline (undivided), Passing: Other passing (explain in narrative), Passing: Where prohibited by signs/markings, Driver Distraction: Passenger, Other (explain in narrative): Other, FTYROW: From stop sign, Cargo/equipment loss or shift, Aggressive driving/road rage, Improper Backing, Driver Distraction: Adjusting devices (radio, climate).

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: Vehicle in traffic,' which initiated 29 crashes. Collisions with fixed objects, such as bridges and ditches, collectively accounted for 11 crashes. Additionally, collisions with animals were the first harmful event in 5 incidents, and overturns or rollovers were recorded in 3 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic29 (53.7%)
2
Collision with: Animal5 (9.3%)
3
Collision with fixed object: Bridge/bridge rail parapet4 (7.4%)
4
Non-collision events: Overturn/rollover3 (5.6%)
5
Collision with fixed object: Ditch3 (5.6%)
6
Collision with: Parked motor vehicle2 (3.7%)
7
Collision with fixed object: Utility pole/light support1 (1.9%)
8
Collision with: Other non-fixed object (explain in narrative)1 (1.9%)
9
Collision with: Railway vehicle/train1 (1.9%)

Showing top 9 of 14 reported. 5 additional (5 total) not shown: Collision with fixed object: Fire hydrant, Miscellaneous events: Immersion, Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Tree, Collision with fixed object: Fence.

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

Roadway Junction / Feature

A majority of crashes, 37 out of 69, occurred in non-junction locations along a road segment. Intersections were the site of 22 crashes, with four-way intersections being the most common type, accounting for 13 of these incidents. Crashes related to driveways accounted for another 4 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature37 (55.2%)
2
Intersection: Four-way intersection13 (19.4%)
3
Intersection: T-intersection7 (10.4%)
4
Non-intersection: Driveway access (related, not in)4 (6%)
5
Non-intersection: Other non-intersection (explain in narrative)2 (3%)
6
Non-intersection: Crossover-related1 (1.5%)
7
Intersection: Y-intersection1 (1.5%)
8
Intersection: Other intersection (explain in narrative)1 (1.5%)
9
Non-intersection: Railroad grade crossing1 (1.5%)

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 42 of the 108 vehicles. Light trucks and SUVs collectively represented a significant portion as well, with 26 pickups and 17 SUVs involved. Notably, 6 tractor/semi-trailers and 4 motorcycles were also involved in crashes during this period.

Vehicle Type

"Other" combines 4 smaller categories (4 records): Single-unit truck (>= 3 axles) (1), Maintenance/construction vehicle (1), Train (1), Motor home/recreational vehicle (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 where traffic control was documented, the vast majority (85 vehicles) were at locations with 'No controls present.' Stop signs were the most common form of traffic control noted, being present for 10 vehicles involved in collisions. Other controls like warning signs and railway crossing devices were present for a small number of vehicles.

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 22 vehicles reporting damage to the 'Front' and an additional 26 vehicles sustaining damage to a front corner. Side impacts were also notable, with 11 vehicles damaged in the middle of the driver's side. Rear damage was recorded for 5 vehicles.

Most Damaged Area

"Other" combines 7 smaller categories (22 records): Passenger side - front (4), Driver side - rear (4), Rear - passenger side corner (4), Passenger side - middle (3), Other (explain in narrative) (3), Rear - driver side corner (2), Passenger side - rear (2).

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

Crashes by City

The crash data for Butler County shows a concentration of incidents in specific municipalities. Parkersburg had the highest volume with 10 crashes, followed by Shell Rock with 8, and Clarksville with 6. Aplington recorded 4 crashes, while New Hartford and Dumont each had 3.

Crashes by City

1
PARKERSBURG10 (27%)
2
SHELL ROCK8 (21.6%)
3
CLARKSVILLE6 (16.2%)
4
APLINGTON4 (10.8%)
5
NEW HARTFORD3 (8.1%)
6
DUMONT3 (8.1%)
7
GREENE2 (5.4%)
8
LAKE CITY1 (2.7%)

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

Paved vs Unpaved Road

The data distinguishes between crashes on paved and unpaved road surfaces. A significant minority of incidents, 10 out of 69 crashes (14.5%), occurred on unpaved roads such as gravel or dirt. The majority, 59 crashes, took place on paved surfaces.

Paved vs Unpaved Road

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

Roadway Contributing Factor

While most crashes did not have an explicit roadway factor cited, 'Surface condition' was the most noted contributor, playing a role in 12 incidents. Other factors such as roadway obstructions, ruts or holes, and work zones were each cited in one crash, indicating they were less common contributors.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)12 (80%)
2
Obstruction in roadway1 (6.7%)
3
Ruts/holes/bumps1 (6.7%)
4
Work Zone (roadway-related)1 (6.7%)

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

Driver Condition

In a minority of cases, a specific driver condition other than 'apparently normal' was noted. Three drivers were recorded as being under the influence of alcohol. Additionally, fatigue or falling asleep was a condition for two drivers, and a medical condition was noted for another two drivers.

Driver Condition

1
Under the influence of alcohol3 (30%)
2
Asleep/fatigued2 (20%)
3
Medical condition (seizure, reaction)2 (20%)
4
Emotional (e.g. depressed, angry)1 (10%)
5
Under the influence of drugs/meds1 (10%)
6
Visually impaired1 (10%)

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

Property Damage

Officer-estimated property damage was recorded for all 69 crashes. The most common damage range was '$1,500 - $7,500,' which applied to 40 crashes. Twenty crashes fell into the '$7,500 - $25,000' category, while 4 crashes (5.8%) involved high-cost damages estimated at over $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 frequent type of crash was a 'Non-collision (single vehicle)' event, such as running off the road or overturning, which accounted for 29 of the 69 incidents (42%). Among multi-vehicle crashes, broadside collisions were most common, with 11 occurrences (15.9%), followed by rear-end collisions with 7 occurrences (10.1%).

Manner of Collision

"Other" combines 1 smaller categories (3 records): Sideswipe, opposite direction (3).

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

Pre-Crash Driver Action

An analysis of pre-crash actions for the vehicles involved shows that the majority, 65 vehicles, were engaged in 'Movement essentially straight.' Turning left was the next most common maneuver, recorded for 10 vehicles, while slowing/stopping and backing were each the pre-crash action for 6 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight65 (62.5%)
2
Turning left10 (9.6%)
3
Slowing/stopping (deceleration)6 (5.8%)
4
Backing6 (5.8%)
5
Turning right5 (4.8%)
6
Legally Parked4 (3.8%)
7
Overtaking/passing3 (2.9%)
8
Other (explain in narrative)2 (1.9%)
9
Entering a parked position1 (1%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Negotiating a curve, Leaving traffic lane.

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

Person Type

Of the 136 individuals involved in crashes, the vast majority were drivers, accounting for 129 people (94.9%). Passengers made up the remainder, with 7 individuals recorded in this role. No other person types, such as pedestrians or cyclists, were involved 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 136 people involved in crashes, 28 individuals sustained some level of injury or were killed. This includes 1 fatality, 2 serious injuries, 9 minor injuries, and 16 possible injuries. The remaining 108 individuals 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 subset of 26 vehicle occupants for whom safety equipment use was recorded, 9 individuals were noted as having used 'None used'. This represents 34.6% of the occupants with recorded data. Conversely, 17 occupants were recorded as having used a shoulder and lap belt.

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 data shows a mix of single and multi-vehicle crashes. Two-vehicle collisions were the most common scenario, accounting for 37 of the 69 crashes. Single-vehicle crashes were also very frequent, with 31 incidents recorded, while only one crash 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: 69
  • Total persons involved: 136
  • Total vehicles involved: 108

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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