Yearly Traffic Safety Analysis

120 CRASHES IN
IOWA, IA
2015

In 2015, Guthrie County recorded 120 total traffic crashes, resulting in 2 fatalities and 35 injuries. The data indicates that single-vehicle incidents were the predominant crash type. A significant finding from the analysis is the primary contributing factor to crashes: collisions with animals, which accounted for 44 of the 120 total incidents, representing 36.7% of all crashes in the county for the year.

120

Total Crash Events

2

Persons Killed

35

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 2 fatalities and 35 injuries recorded in Guthrie County in 2015 involved motorists. There were no pedestrians or cyclists killed or injured in any of the reported crashes during this period. The two individuals who lost their lives were vehicle occupants, as were the 35 people who sustained injuries.

2

Motorists Killed

35

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 analysis reveals that incidents were most frequent on Thursdays and Fridays, with each day recording 21 crashes. The evening commute hour from 5:00 PM to 5:59 PM was the single most common time for crashes, with 15 incidents. A notable pattern is the high number of crashes occurring in darkness on unlit roadways, which accounted for 31 incidents, compared to 46 crashes that 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 120 crashes in Guthrie County, 90 incidents (75%) resulted in no injuries, being classified as property-damage-only. The remaining 25% of crashes involved some level of injury or a fatality. Specifically, there were 2 fatal crashes (1.7%), 3 crashes with serious injuries (2.5%), 11 with minor injuries (9.2%), and 14 with possible injuries (11.7%). These 2 fatal crashes resulted in a total of 2 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.7%
Serious Injury3serious injury crashes2.5%
Minor Injury11minor injury crashes9.2%
Possible Injury14possible injury crashes11.7%
No Injury90no injury crashes75%

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 cited in crashes was overwhelmingly animals, involved in 44 incidents (36.7%). Following distantly were factors such as drivers losing control (11 crashes, 9.2%), driving too fast for conditions (9 crashes, 7.5%), and running off a straight road (6 crashes, 5.0%). Failure to yield the right-of-way from a stop sign was also a factor in 6 crashes.

Officer-Reported Primary Contributing Cause

Animal44 (36.7%)
Lost Control11 (9.2%)
Driving too fast for conditions9 (7.5%)
Ran off road - straight6 (5%)
FTYROW: From stop sign6 (5%)
Ran off road - left5 (4.2%)
Followed too close5 (4.2%)
Other (explain in narrative): Other4 (3.3%)
Swerving/Evasive Action4 (3.3%)
Driver Distraction: Other interior distraction3 (2.5%)

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 favorable conditions. Specifically, 64 crashes happened in clear weather and 61 took place on dry road surfaces. Regarding lighting, 46 crashes occurred during daylight. However, a significant number of incidents, 31, happened on dark roadways that were not lighted. Adverse weather was less common, with 5 crashes occurring in snow and 2 in rain.

Weather

Clear64 (73.6%)
Cloudy12 (13.8%)
Snow5 (5.7%)
Rain2 (2.3%)
Fog, smoke, smog2 (2.3%)
Sleet, hail1 (1.1%)
Freezing rain/drizzle1 (1.1%)

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

Lighting

Daylight46 (52.3%)
Dark - roadway not lighted31 (35.2%)
Dusk6 (6.8%)
Dawn3 (3.4%)
Dark - roadway lighted1 (1.1%)
Dark - unknown roadway lighting1 (1.1%)

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

Road Surface

Dry61 (69.3%)
Gravel13 (14.8%)
Snow4 (4.5%)
Ice/frost4 (4.5%)
Wet3 (3.4%)
Other (explain in narrative)2 (2.3%)
Oil1 (1.1%)

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

Vehicles & Demographics

Among the 193 people involved in crashes, the 16-20 age group was the most represented, with 46 individuals. Analysis of the 155 vehicles involved shows that Ford was the most frequent make, with 41 vehicles recorded in crashes. Chevrolet vehicles were also common, with 15 listed as 'CHEVROLET' and another 11 as 'CHEV', for a combined total of 26.

Top Vehicle Makes (155 vehicles)

1
FORD41 (26.5%)
2
CHEVROLET15 (9.7%)
3
CHEV11 (7.1%)
4
DODGE8 (5.2%)
5
DODG7 (4.5%)
6
BUIC7 (4.5%)
7
KIA4 (2.6%)
8
GMC4 (2.6%)
9
CHRY4 (2.6%)
10
CHRYSLER4 (2.6%)

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 (147 persons with recorded sex)

Male81 (55.1%)
Female66 (44.9%)

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 for crashes was 'Animal', accounting for 44 of the 120 incidents. 'Lost Control' was the second leading cause, attributed to 11 crashes, followed by 'Driving too fast for conditions' with 9 crashes. Failure to yield from a stop sign and running off a straight portion of the road were each listed as the major cause for 6 crashes.

Major Cause

1
Animal44 (37.3%)
2
Lost Control11 (9.3%)
3
Driving too fast for conditions9 (7.6%)
4
Ran off road - straight6 (5.1%)
5
FTYROW: From stop sign6 (5.1%)
6
Ran off road - left5 (4.2%)
7
Followed too close5 (4.2%)
8
Other (explain in narrative): Other4 (3.4%)
9
Swerving/Evasive Action4 (3.4%)

Showing top 9 of 23 reported. 14 additional (24 total) not shown: Driver Distraction: Other interior distraction, Other (explain in narrative): No improper action, Exceeded authorized speed, FTYROW: From driveway, Improper Backing, Made improper turn, Ran off road - right, Ran Stop Sign, Crossed centerline (undivided), Downhill runaway, Aggressive driving/road rage, Ran Traffic Signal, FTYROW: Making left turn, FTYROW: From yield sign.

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: Animal', which initiated 44 crashes. The second most frequent event was a 'Collision with: Vehicle in traffic', occurring in 27 incidents. Non-collision events, primarily 'Overturn/rollover', were the first harmful event in 13 crashes, while collisions with a ditch occurred in 8 incidents.

First Harmful Event

1
Collision with: Animal44 (37%)
2
Collision with: Vehicle in traffic27 (22.7%)
3
Non-collision events: Overturn/rollover13 (10.9%)
4
Collision with fixed object: Ditch8 (6.7%)
5
Collision with: Parked motor vehicle3 (2.5%)
6
Collision with fixed object: Traffic sign support3 (2.5%)
7
Collision with fixed object: Tree3 (2.5%)
8
Non-collision events: Non-contact vehicle (phantom)2 (1.7%)
9
Collision with: Struck/struck by object/cargo/person from other vehicle2 (1.7%)

Showing top 9 of 20 reported. 11 additional (14 total) not shown: Collision with fixed object: Culvert/pipe opening, Other (explain in narrative), Collision with: Re-entering roadway, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Non-collision events: Vehicle went airborne, Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Utility pole/light support, Collision with fixed object: Mailbox, Collision with fixed object: Landscape/shrubbery, Non-collision events: Fell/jumped from 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, 62 out of 120, occurred at non-intersection locations described as having no special feature. Intersections accounted for a smaller portion of incidents, with 13 crashes at four-way intersections and 2 at T-intersections. An additional 3 crashes were related to driveway access.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature62 (70.5%)
2
Intersection: Four-way intersection13 (14.8%)
3
Non-intersection: Driveway access (within)3 (3.4%)
4
Non-intersection: Driveway access (related, not in)2 (2.3%)
5
Intersection: T-intersection2 (2.3%)
6
Non-intersection: Other non-intersection (explain in narrative)2 (2.3%)
7
Intersection: Other intersection (explain in narrative)2 (2.3%)
8
Non-intersection: Bike lanes1 (1.1%)
9
Non-intersection: Alley1 (1.1%)

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

Vehicle Type

Of the 155 vehicles involved in crashes, passenger cars were the most common type, with 65 units. Sport utility vehicles (38 vehicles) and four-tire light trucks or pickups (31 vehicles) were also frequently involved. The data also includes 5 motorcycles and 4 tractor/semi-trailers among the vehicles in collisions.

Vehicle Type

"Other" combines 1 smaller categories (1 records): Farm tractor (1).

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

Traffic Control Device

A large majority of crashes, 82 out of 120, occurred on roadway segments where no traffic controls were present. For crashes at controlled locations, stop signs were the most common device, present at 16 incidents. Warning signs were noted at the scene of 15 crashes.

Traffic Control Device

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

Most Damaged Area

Analysis of vehicle damage indicates that frontal impacts were most common. The primary point of impact was the 'Front' for 25 vehicles, the 'Front - passenger side corner' for 17 vehicles, and the 'Front - driver side corner' for 11 vehicles. Damage to the 'Top' of the vehicle, often associated with rollovers, was recorded for 13 vehicles.

Most Damaged Area

"Other" combines 7 smaller categories (27 records): Driver side - front (7), Driver side - rear (5), Passenger side - rear (4), Passenger side - front (4), Passenger side - middle (3), Driver side - middle (2), Non-collision/no damage (2).

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

Crashes by City

Crash distribution within Guthrie County shows the highest concentration in Guthrie Center, which recorded 13 crashes. Panora had the second-highest count with 9 crashes, followed by Stuart with 5. Other municipalities like Bayard, Yale, Coon Rapids, Dexter, and Menlo each recorded one or two crashes.

Crashes by City

1
GUTHRIE CENTER13 (39.4%)
2
PANORA9 (27.3%)
3
STUART5 (15.2%)
4
BAYARD2 (6.1%)
5
YALE1 (3%)
6
COON RAPIDS1 (3%)
7
DEXTER1 (3%)
8
MENLO1 (3%)

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

Paved vs Unpaved Road

Of the 120 total crashes, 93 occurred on paved road surfaces, while 27 crashes, or 22.5% of the total, took place on unpaved roads. This highlights the role of the county's gravel and dirt road network in local traffic safety.

Paved vs Unpaved Road

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, 7 were noted as being under the influence of alcohol. An additional 3 drivers were identified as being asleep or fatigued. One driver was recorded as being emotional and another had a medical condition.

Driver Condition

1
Under the influence of alcohol7 (58.3%)
2
Asleep/fatigued3 (25%)
3
Emotional (e.g. depressed, angry)1 (8.3%)
4
Medical condition (seizure, reaction)1 (8.3%)

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 fell into the '$1,500 - $7,500' category, which accounted for 91 of the 120 incidents. Higher-cost damages were less frequent, with 22 crashes estimated between $7,500 and $25,000, and only 2 crashes exceeding $25,000 in property 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 dominant crash type, accounting for 78 of the 120 incidents (65%). Among multi-vehicle crashes, 'Rear-end' collisions were the most frequent, with 14 incidents (11.7%), followed by 'Broadside' collisions with 6 incidents (5%).

Manner of Collision

"Other" combines 3 smaller categories (5 records): Angle, oncoming left turn (2), Sideswipe, opposite direction (2), Head-on (front to front) (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 pre-crash action for the 155 vehicles involved was 'Movement essentially straight', recorded for 88 vehicles. Other notable actions included 'Turning left' (11 vehicles) and 'Negotiating a curve' (7 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight88 (64.7%)
2
Turning left11 (8.1%)
3
Negotiating a curve7 (5.1%)
4
Slowing/stopping (deceleration)5 (3.7%)
5
Legally Parked5 (3.7%)
6
Other (explain in narrative)5 (3.7%)
7
Backing4 (2.9%)
8
Turning right3 (2.2%)
9
Overtaking/passing2 (1.5%)

Showing top 9 of 14 reported. 5 additional (6 total) not shown: Making U-turn, Leaving a parked position, Starting in road, Stopped in traffic, Accelerating in road.

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

Person Type

Of the 193 individuals involved in crashes, 186 were drivers, making up 96.4% of all persons. The remaining 7 individuals were vehicle passengers. No pedestrians, cyclists, or other non-occupant types were recorded in any of the crash reports for this period.

Person Type

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

Person Injury Severity

Among the 193 people involved in crashes, 2 sustained fatal injuries and 35 sustained non-fatal injuries. The injury breakdown includes 3 serious injuries, 13 minor injuries, and 19 possible injuries. The majority of individuals involved in crashes were not physically injured.

Person Injury Severity

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

Occupant Safety Equipment

Based on available data for 32 individuals, 22 were recorded as using a shoulder and lap belt. However, 6 individuals were noted as using no safety equipment at all. The data also shows 3 individuals used a child safety seat and 1 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

Single-vehicle crashes were the most common type, with 85 of the 120 total incidents (70.8%) involving only one vehicle. The remaining 35 crashes (29.2%) were two-vehicle collisions. No crashes involving three or more vehicles were reported during this period.

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: 120
  • Total persons involved: 193
  • Total vehicles involved: 155

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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