Yearly Traffic Safety Analysis

299 CRASHES IN
IOWA, IA
2015

In 2015, Mahaska County recorded 299 total traffic crashes, resulting in 7 fatalities and 117 injuries. These incidents involved 517 vehicles and 643 individuals. The majority of crashes, approximately 67.6%, resulted in no injuries, while 4 crashes were fatal.

299

Total Crash Events

7

Persons Killed

117

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 7 fatalities and the vast majority of injuries, with 113 reported. No pedestrians or cyclists were killed. However, there was 1 pedestrian injury and 2 cyclist injuries recorded during this period.

0

Pedestrians Killed

0

Cyclists Killed

7

Motorists Killed

0

Other Killed

1

Pedestrians Injured

2

Cyclists Injured

113

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 patterns in Mahaska County show a concentration during the latter part of the week, with Friday being the peak day for incidents with 55 crashes. Crashes peaked during the midday and afternoon hours, with both the 12 p.m. and 4 p.m. hours recording the highest frequency at 30 crashes each. The majority of collisions, 212 out of 299, occurred 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 299 crashes in 2015, the majority (67.6%) were property-damage-only incidents with no reported injuries. Injury-involved crashes, ranging from possible to serious, accounted for 93 incidents. There were 4 fatal crashes, which resulted in a total of 7 fatalities, highlighting that a single crash event can involve multiple deaths.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.3%
Serious Injury13serious injury crashes4.3%
Minor Injury31minor injury crashes10.4%
Possible Injury49possible injury crashes16.4%
No Injury202no injury crashes67.6%

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 factors cited in Mahaska County crashes include failure to yield the right of way from a stop sign, which was noted in 27 incidents (9.0%). This was closely followed by drivers losing control of their vehicle in 26 incidents (8.7%) and driving too fast for conditions in 21 incidents (7.0%). Other significant factors included following too closely (19 crashes) and various forms of driver distraction.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign27 (9%)
Lost Control26 (8.7%)
Driving too fast for conditions21 (7%)
Followed too close19 (6.4%)
Other (explain in narrative): Other17 (5.7%)
Animal16 (5.4%)
Driver Distraction: Other interior distraction14 (4.7%)
FTYROW: Making left turn14 (4.7%)
Ran Traffic Signal12 (4%)
Ran off road - straight12 (4%)

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 occurred in ideal driving conditions. In 2015, 197 crashes (65.9%) happened in clear weather, 212 (70.9%) in daylight, and 204 (68.2%) on dry road surfaces. Crashes during adverse weather included 18 in rain and 10 in snow, while 70 incidents occurred in dark conditions.

Weather

Clear197 (68.2%)
Cloudy53 (18.3%)
Rain18 (6.2%)
Snow10 (3.5%)
Freezing rain/drizzle5 (1.7%)
Fog, smoke, smog3 (1.0%)
Blowing Snow3 (1.0%)

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

Lighting

Daylight212 (72.6%)
Dark - roadway not lighted38 (13.0%)
Dark - roadway lighted32 (11.0%)
Dawn6 (2.1%)
Dusk4 (1.4%)

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

Road Surface

Dry204 (70.3%)
Wet39 (13.4%)
Snow19 (6.6%)
Gravel14 (4.8%)
Ice/frost11 (3.8%)
Mud, dirt2 (0.7%)
Slush1 (0.3%)

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

Vehicles & Demographics

Analysis of individuals involved in crashes shows the 16-20 age group was the most represented, with 98 persons. Among the 517 vehicles involved, Ford was the most frequent make with 94 vehicles, followed by Chevrolet with 77 vehicles and Dodge with 42 vehicles. These figures represent the makes of vehicles involved in collisions and do not reflect market share.

Top Vehicle Makes (517 vehicles)

1
FORD94 (18.2%)
2
CHEV77 (14.9%)
3
DODG42 (8.1%)
4
CHEVROLET27 (5.2%)
5
DODGE22 (4.3%)
6
BUIC22 (4.3%)
7
GMC19 (3.7%)
8
PONT17 (3.3%)
9
JEEP17 (3.3%)
10
TOYT16 (3.1%)

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

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

Sex Distribution (444 persons with recorded sex)

Male269 (60.6%)
Female175 (39.4%)

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

Major Cause

The primary causes of crashes in Mahaska County were led by 'Failure to yield right of way from a stop sign,' cited in 27 incidents. 'Lost Control' was the second-most common cause, contributing to 26 crashes. 'Driving too fast for conditions' was documented as the major cause in 21 crashes.

Major Cause

1
FTYROW: From stop sign27 (9.7%)
2
Lost Control26 (9.4%)
3
Driving too fast for conditions21 (7.6%)
4
Followed too close19 (6.9%)
5
Other (explain in narrative): Other17 (6.1%)
6
Animal16 (5.8%)
7
Driver Distraction: Other interior distraction14 (5.1%)
8
FTYROW: Making left turn14 (5.1%)
9
Ran Traffic Signal12 (4.3%)

Showing top 9 of 39 reported. 30 additional (111 total) not shown: Ran off road - straight, Operating vehicle in an reckless, erratic, careless, negligent manner, Ran Stop Sign, Ran off road - left, Driver Distraction: Exterior distraction, Made improper turn, Improper Backing, FTYROW: From driveway, Exceeded authorized speed, Driver Distraction: Reaching for object(s)/fallen object(s), Swerving/Evasive Action, Failed to keep in proper lane, Passing: Other passing (explain in narrative), FTYROW: From parked position, FTYROW: Other (explain in narrative), Improper or erratic lane changing, Other (explain in narrative): No improper action, Traveling wrong way or on wrong side of road, Driver Distraction: Inattentive/lost in thought, Cargo/equipment loss or shift, Driver Distraction: Talking on a hand-held device, Equipment failure, Failure to signal intentions, Driver Distraction: Other electronic device activity, FTYROW: At uncontrolled intersection, Crossed centerline (undivided), Other (explain in narrative): Vision obstructed, Ran off road - right, Separation of units, Driver Distraction: Passenger.

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, accounting for 171 crashes (57.2%). Collisions with fixed objects were also frequent, including 19 crashes involving a ditch and 16 involving an animal. Single-vehicle non-collision events, such as an overturn or rollover, were the first harmful event in 13 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic171 (57.6%)
2
Collision with fixed object: Ditch19 (6.4%)
3
Collision with: Parked motor vehicle18 (6.1%)
4
Collision with: Animal16 (5.4%)
5
Non-collision events: Overturn/rollover13 (4.4%)
6
Other (explain in narrative)8 (2.7%)
7
Collision with fixed object: Embankment7 (2.4%)
8
Non-collision events: Other non-collision (explain in narrative)5 (1.7%)
9
Collision with fixed object: Building5 (1.7%)

Showing top 9 of 26 reported. 17 additional (35 total) not shown: Miscellaneous events: Hit and run, Collision with: Re-entering roadway, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Tree, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Culvert/pipe opening, 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, Collision with: Non-motorist (see non-motorist section - NOT a unit), Non-collision events: Fell/jumped from vehicle, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Vehicle went airborne, Collision with fixed object: Guardrail - face, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Fence, Collision with fixed object: Traffic signal support.

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

Roadway Junction / Feature

Crashes were more likely to occur away from intersections, with 149 incidents happening on non-junction road segments. Four-way intersections were the most common crash location among junction types, accounting for 88 incidents. T-intersections were the site of another 23 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature149 (51%)
2
Intersection: Four-way intersection88 (30.1%)
3
Intersection: T-intersection23 (7.9%)
4
Non-intersection: Driveway access (related, not in)13 (4.5%)
5
Non-intersection: Driveway access (within)6 (2.1%)
6
Non-intersection: Other non-intersection (explain in narrative)3 (1%)
7
Interchange-related: Off-ramp2 (0.7%)
8
Intersection: Other intersection (explain in narrative)2 (0.7%)
9
Intersection: Y-intersection2 (0.7%)

Showing top 9 of 13 reported. 4 additional (4 total) not shown: Non-intersection: Alley, Intersection: Intersection with ramp, Interchange-related: On-ramp merge area, Interchange-related: On-ramp.

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, with 207 units. Light trucks and pickups (117) and sport utility vehicles (97) were also frequently involved. Commercial vehicles like tractor/semi-trailers were involved in 18 crashes, while motorcycles were involved in 7 incidents.

Vehicle Type

"Other" combines 6 smaller categories (18 records): Motorcycle (7), Cargo/panel van (6), School bus (seats > 15) (2), Motor home/recreational vehicle (1), Farm equipment (explain in narrative) (1), Other bus (seats > 15) (1).

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

Traffic Control Device

Analysis of traffic controls present for the vehicles involved shows that a majority, 332, were in areas with no traffic controls present. For crashes at controlled locations, stop signs were the most common device, noted for 85 vehicles involved. Traffic signals were present for 74 vehicles involved in collisions.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): Yield signs (1).

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 point of impact, recorded as the most-damaged area for 132 vehicles. Combined with front-corner impacts (98 vehicles), frontal damage was a factor in a significant number of collisions. Rear impacts, indicative of rear-end collisions, were the primary damage area for 47 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (119 records): Driver side - rear (24), Passenger side - front (20), Rear - passenger side corner (20), Driver side - front (18), Passenger side - rear (14), Other (explain in narrative) (10), Top (9), Non-collision/no damage (2), Undercarriage (2).

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

Impairment (Alcohol / Drugs)

Impairment was suspected in 10 crashes, representing 3.3% of all incidents in 2015. Of these, alcohol was the suspected substance in 9 crashes, and drugs were suspected in 1 crash. These figures should be considered a minimum, as impairment is often under-reported in crash data.

Crashes by City

The distribution of crashes across municipalities shows a heavy concentration in Oskaloosa, which accounted for 187 of the reported incidents. Other towns like New Sharon (3 crashes), Eddyville (2 crashes), and Fremont (2 crashes) saw significantly fewer events. A number of crashes occurred in unincorporated areas and are not included in this city-specific breakdown.

Crashes by City

1
OSKALOOSA187 (95.9%)
2
NEW SHARON3 (1.5%)
3
EDDYVILLE2 (1%)
4
FREMONT2 (1%)
5
UNIVERSITY PARK1 (0.5%)

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

Paved vs Unpaved Road

The vast majority of crashes, 266 out of 299, occurred on paved roadways. However, a notable 33 crashes, or 11.0% of the total, took place on unpaved surfaces such as gravel or dirt roads. This reflects the presence of an extensive secondary road network in the county.

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 a contributor in a minority of crashes. The most common factor was the road surface condition, such as being wet or icy, which was noted in 26 incidents. Other factors like ruts or traffic backups were cited in only one crash each.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)26 (92.9%)
2
Ruts/holes/bumps1 (3.6%)
3
Traffic backup, prior crash1 (3.6%)

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, being under the influence of alcohol was the most frequent, noted for 16 drivers. Driver fatigue or falling asleep was documented for 6 drivers, a factor often associated with rural driving. An emotional state was cited for 3 drivers.

Driver Condition

1
Under the influence of alcohol16 (51.6%)
2
Asleep/fatigued6 (19.4%)
3
Emotional (e.g. depressed, angry)3 (9.7%)
4
Impaired due to previous injury2 (6.5%)
5
Walks with a cane/crutches2 (6.5%)
6
Illness/fainted1 (3.2%)
7
Medical condition (seizure, reaction)1 (3.2%)

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

Property Damage

The estimated property damage for the majority of crashes (215 incidents) fell within the $1,500 to $7,500 range. A smaller number of crashes resulted in more significant damage, with 67 incidents estimated between $7,500 and $25,000. Twelve crashes, representing 4.0% of the total, involved severe property damage 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

Single-vehicle crashes, such as running off the road or overturning, were the most common type of incident, accounting for 93 crashes or 31.1% of the total. Among multi-vehicle collisions, rear-end crashes were the most frequent pattern with 69 incidents (23.1%), followed closely by broadside collisions with 65 incidents (21.7%).

Manner of Collision

"Other" combines 2 smaller categories (7 records): Sideswipe, opposite direction (5), Head-on (front to front) (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 'Movement essentially straight,' recorded for 287 vehicles. Turning left was the next most frequent action leading to a crash, documented for 48 vehicles. Other notable actions included slowing or stopping (20 vehicles) and backing (20 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight287 (57.6%)
2
Turning left48 (9.6%)
3
Legally Parked40 (8%)
4
Stopped in traffic22 (4.4%)
5
Backing20 (4%)
6
Slowing/stopping (deceleration)20 (4%)
7
Turning right19 (3.8%)
8
Other (explain in narrative)11 (2.2%)
9
Overtaking/passing8 (1.6%)

Showing top 9 of 17 reported. 8 additional (23 total) not shown: Negotiating a curve, Entering traffic lane (merging), Changing lanes, Starting in road, Leaving a parked position, Illegally Parked/Unattended, Making U-turn, Accelerating in road.

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

Person Type

Of the 643 people involved in crashes, the vast majority were drivers, accounting for 612 individuals. Passengers made up the next largest group with 26 people. A small number of non-motorists were involved, including 2 bicyclists and 1 pedestrian.

Person Type

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

Person Injury Severity

Across all 643 individuals involved in crashes, 7 people sustained fatal injuries and 117 sustained non-fatal injuries. The injuries included 15 serious, 37 minor, and 65 possible injuries. The data shows that while most crashes did not result in injury, a significant number of individuals were still affected.

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 vehicle occupants for whom safety equipment use was documented, 87 individuals were recorded as using a shoulder and lap belt. Conversely, 13 individuals were documented as using no safety equipment at the time of their crash. One person was secured in a forward-facing child safety seat.

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

Two-vehicle collisions were the most common scenario, accounting for 192 of the 299 crashes. Single-vehicle crashes were also frequent, with 95 incidents representing 31.8% of the total. Multi-vehicle crashes involving three or more vehicles were less common, with 10 three-vehicle and 2 four-vehicle incidents recorded.

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: 299
  • Total persons involved: 643
  • Total vehicles involved: 517

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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