Yearly Traffic Safety Analysis

82 CRASHES IN
IOWA, IA
2015

In 2015, Mitchell County recorded 82 traffic crashes, resulting in 1 fatality and 55 injuries. Analysis of the data reveals that single-vehicle crashes were the most common collision type, accounting for 45.1% of all incidents. The leading contributing factor cited in these crashes was failure to yield at an uncontrolled intersection.

82

Total Crash Events

1

Persons Killed

55

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

Motor vehicle occupants accounted for the vast majority of casualties, with 53 motorists injured in crashes during this period. The data also includes one cyclist fatality, one cyclist injury, and one pedestrian injury. No motorist fatalities were recorded.

0

Pedestrians Killed

1

Cyclists Killed

0

Motorists Killed

1

Pedestrians Injured

1

Cyclists Injured

53

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

Crashes in Mitchell County during 2015 occurred most frequently on Tuesdays, with 17 incidents, and during the 3 p.m. hour, which saw 8 crashes. The data shows a strong daytime pattern, with 62 of the 82 total crashes (75.6%) occurring in daylight conditions. Crashes were most common in January (11), September (10), and December (10).

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

Just over half of all crashes (51.2%) resulted in no injuries, involving only property damage. The remaining 48.8% of crashes involved at least one reported injury or a fatality. There was 1 fatal crash recorded, which resulted in 1 fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.2%
Serious Injury4serious injury crashes4.9%
Minor Injury12minor injury crashes14.6%
Possible Injury23possible injury crashes28%
No Injury42no injury crashes51.2%

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 identified in crashes was 'Failure to yield right-of-way at an uncontrolled intersection,' cited in 10 incidents (12.2%). Other frequently cited factors include 'Lost Control' (8 crashes), 'Driver Distraction: Other interior distraction' (7 crashes), and both 'Driving too fast for conditions' and 'Failure to yield from a stop sign' (5 crashes each).

Officer-Reported Primary Contributing Cause

FTYROW: At uncontrolled intersection10 (12.2%)
Lost Control8 (9.8%)
Driver Distraction: Other interior distraction7 (8.5%)
FTYROW: From stop sign5 (6.1%)
Driving too fast for conditions5 (6.1%)
FTYROW: Making left turn4 (4.9%)
Ran off road - straight4 (4.9%)
Made improper turn3 (3.7%)
Ran off road - left3 (3.7%)
Ran off road - right2 (2.4%)

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, with 69.5% happening in clear weather and 75.6% during daylight hours. Similarly, 64.6% of crashes took place on dry road surfaces. Adverse conditions were less frequent, with 12 crashes on icy or frosty roads and 5 crashes during snowfall.

Weather

Clear57 (71.3%)
Cloudy12 (15.0%)
Snow5 (6.3%)
Freezing rain/drizzle3 (3.8%)
Rain2 (2.5%)
Blowing Snow1 (1.3%)

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

Lighting

Daylight62 (76.5%)
Dark - roadway not lighted13 (16.0%)
Dark - roadway lighted2 (2.5%)
Dawn2 (2.5%)
Dusk2 (2.5%)

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

Road Surface

Dry53 (65.4%)
Ice/frost12 (14.8%)
Snow7 (8.6%)
Gravel5 (6.2%)
Wet3 (3.7%)
Other (explain in narrative)1 (1.2%)

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 16-20 age group was the most represented, with 36 individuals, followed by the 55-64 age group with 28 individuals. The most common vehicle makes involved were Chevrolet (32 vehicles), Ford (21 vehicles), and Dodge (14 vehicles), based on combined data entries.

Top Vehicle Makes (127 vehicles)

1
CHEV26 (20.5%)
2
FORD21 (16.5%)
3
DODG9 (7.1%)
4
PONT7 (5.5%)
5
CHRY7 (5.5%)
6
CHEVROLET6 (4.7%)
7
BUIC6 (4.7%)
8
DODGE5 (3.9%)
9
INTERNATIONA4 (3.1%)
10
PONTIAC3 (2.4%)

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 (119 persons with recorded sex)

Female60 (50.4%)
Male59 (49.6%)

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 frequently recorded major cause of crashes was 'Failure to yield right-of-way at an uncontrolled intersection,' which was attributed to 10 incidents. Other leading causes included 'Lost Control' (8 crashes), 'Driver Distraction' from an interior source (7 crashes), and both 'Driving too fast for conditions' and 'Failure to yield from a stop sign' (5 crashes each).

Major Cause

1
FTYROW: At uncontrolled intersection10 (12.8%)
2
Lost Control8 (10.3%)
3
Driver Distraction: Other interior distraction7 (9%)
4
FTYROW: From stop sign5 (6.4%)
5
Driving too fast for conditions5 (6.4%)
6
FTYROW: Making left turn4 (5.1%)
7
Ran off road - straight4 (5.1%)
8
Made improper turn3 (3.8%)
9
Ran off road - left3 (3.8%)

Showing top 9 of 31 reported. 22 additional (29 total) not shown: Ran off road - right, Animal, FTYROW: From yield sign, Swerving/Evasive Action, Driver Distraction: Inattentive/lost in thought, Other (explain in narrative): Other, Followed too close, Other (explain in narrative): No improper action, Passing: Other passing (explain in narrative), Passing: With insufficient distance/inadequate visibility, Ran Traffic Signal, Driver Distraction: Talking on a hand-held device, Exceeded authorized speed, Driver Distraction: Manual operation of an electronic communication device, Failed to keep in proper lane, Driver Distraction: Exterior distraction, Traveling wrong way or on wrong side of road, FTYROW: To pedestrian, Crossed centerline (undivided), Operating vehicle in an reckless, erratic, careless, negligent manner, Operator inexperience, Other (explain in narrative): Disregarded signs/road markings.

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 a vehicle in traffic,' which occurred in 42 of the 82 crashes (51.2%). Run-off-road incidents were also significant, with 15 crashes involving a collision with a ditch and 8 resulting in an overturn or rollover.

First Harmful Event

1
Collision with: Vehicle in traffic42 (51.9%)
2
Collision with fixed object: Ditch15 (18.5%)
3
Non-collision events: Overturn/rollover8 (9.9%)
4
Collision with: Non-motorist (see non-motorist section - NOT a unit)3 (3.7%)
5
Collision with: Animal2 (2.5%)
6
Collision with fixed object: Utility pole/light support2 (2.5%)
7
Other (explain in narrative)2 (2.5%)
8
Collision with: Parked motor vehicle1 (1.2%)
9
Collision with: Thrown or falling object1 (1.2%)

Showing top 9 of 14 reported. 5 additional (5 total) not shown: Collision with fixed object: Snow bank, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Mailbox, Collision with: Other non-fixed object (explain in narrative).

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

Roadway Junction / Feature

A majority of crashes, 57 out of 82 (69.5%), occurred at non-intersection locations rather than at junctions. Four-way intersections were the most common junction type for crashes, accounting for 23 incidents. An additional 2 crashes were related to driveway access points.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature52 (64.2%)
2
Intersection: Four-way intersection23 (28.4%)
3
Non-intersection: Other non-intersection (explain in narrative)2 (2.5%)
4
Non-intersection: Driveway access (related, not in)2 (2.5%)
5
Non-intersection: Driveway access (within)1 (1.2%)
6
Intersection: T-intersection1 (1.2%)

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 54 of the 127 vehicles, followed by sport utility vehicles (28) and four-tire light trucks (19). The data also includes the involvement of 5 tractor/semi-trailers and 2 motorcycles in these incidents.

Vehicle Type

"Other" combines 6 smaller categories (6 records): Other light truck (<=10000 lbs) (1), Golf cart (1), Maintenance/construction vehicle (1), Motor home/recreational vehicle (1), Farm tractor (1), School bus (seats > 15) (1).

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

Traffic Control Device

For a significant majority of vehicles involved in crashes (104 of 127, or 81.9%), no traffic controls were present at the crash location. Where controls were present, 8 vehicles were at locations with traffic signals and 5 were at locations with stop signs.

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, with 32 vehicles sustaining primary damage there, and an additional 27 vehicles damaged on the front driver or passenger side corners. Side impacts were also frequent, with 10 vehicles damaged on the driver's side middle, while only 4 incidents were recorded with the most damage to the rear of the vehicle.

Most Damaged Area

"Other" combines 9 smaller categories (32 records): Passenger side - front (7), Passenger side - rear (5), Rear (4), Rear - driver side corner (4), Undercarriage (3), Other (explain in narrative) (3), Rear - passenger side corner (3), Driver side - rear (2), Cargo loss (1).

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

Crashes by City

Within Mitchell County, the city of Osage accounted for the largest number of crashes, with 31 recorded incidents. The towns of Mitchell, Riceville, and Saint Ansgar each reported 2 crashes, while Stacyville had 1. A significant portion of crashes occurred outside of any city's jurisdiction.

Crashes by City

1
OSAGE31 (81.6%)
2
MITCHELL2 (5.3%)
3
RICEVILLE2 (5.3%)
4
SAINT ANSGAR2 (5.3%)
5
STACYVILLE1 (2.6%)

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

Paved vs Unpaved Road

Crashes occurred predominantly on paved roads, which accounted for 69 of the 82 incidents. A notable portion, 13 crashes or 15.9% of the total, occurred 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

Roadway Contributing Factor

In cases where a roadway factor was noted as a contributor, 'Surface condition (e.g. wet, icy)' was the most common, cited in 11 crashes. Other roadway factors included 'Obstruction in roadway' and 'Slippery, loose or worn surface,' each contributing to 2 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)11 (68.8%)
2
Obstruction in roadway2 (12.5%)
3
Slippery, loose or worn surface2 (12.5%)
4
Work Zone (roadway-related)1 (6.3%)

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 per crash was in the $1,500 to $7,500 range, which applied to 52 of the 82 incidents (63.4%). A smaller number of crashes resulted in higher costs, with 5 crashes (6.1%) exceeding $25,000 in estimated damage.

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, categorized as 'Non-collision,' were the most frequent type of incident, accounting for 37 of the 82 crashes (45.1%). Among multi-vehicle crashes, broadside collisions were the most common, with 20 incidents, followed by rear-end (8) and head-on (7) collisions.

Manner of Collision

"Other" combines 1 smaller categories (1 records): Sideswipe, opposite direction (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 drivers involved in crashes, 98 out of 127 (77.2%), were moving essentially straight prior to the collision. Far less common pre-crash actions included turning left (9 vehicles) and negotiating a curve (6 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight98 (77.2%)
2
Turning left9 (7.1%)
3
Negotiating a curve6 (4.7%)
4
Legally Parked3 (2.4%)
5
Turning right3 (2.4%)
6
Stopped in traffic2 (1.6%)
7
Other (explain in narrative)1 (0.8%)
8
Changing lanes1 (0.8%)
9
Making U-turn1 (0.8%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Backing, Overtaking/passing, Slowing/stopping (deceleration).

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

Person Type

Drivers constituted the largest group of individuals involved in crashes, with 165 of the 184 people recorded (89.7%). Passengers accounted for 16 individuals (8.7%), while the remaining involved persons were two bicyclists and one 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 184 people involved in crashes, there was one fatality and five serious injuries recorded. An additional 50 individuals sustained minor or possible injuries, with 16 classified as minor and 34 as possible.

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 49 individuals for whom safety equipment usage was specified, 41 were reported as using a shoulder and lap belt. Four individuals were recorded as using no safety equipment, while two used only a lap belt and two used 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

Two-vehicle collisions were the most common scenario, accounting for 45 of the 82 crashes (54.9%). Single-vehicle crashes were also very frequent, making up the remaining 37 incidents, or 45.1% of the total.

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: 184
  • Total vehicles involved: 127

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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