Yearly Traffic Safety Analysis

317 CRASHES IN
IOWA, IA
2015

In 2015, Clayton County recorded 317 traffic crashes, resulting in 3 fatalities and 97 injuries. A significant finding from the data is that collisions with animals were the primary contributing factor, accounting for 45.4% of all reported incidents. The majority of crashes, 77.9%, resulted in no injuries.

317

Total Crash Events

3

Persons Killed

97

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 3 fatalities and 95 of the 97 total injuries involved motor vehicle occupants. One pedestrian was injured, and no cyclists were killed or injured in reported crashes. An additional injury was recorded for a person classified as 'other non-motorist'.

0

Pedestrians Killed

3

Motorists Killed

0

Other Killed

1

Pedestrians Injured

95

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 frequency in Clayton County peaked on Saturdays, which saw 58 incidents, closely followed by Fridays with 56. The most common time for crashes was the 6 p.m. hour, when 31 incidents occurred. While more crashes happened during daylight hours (108), a notable number of incidents, 73, occurred in dark conditions, with 62 of those on unlighted roadways.

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 317 crashes, the majority (77.9% or 247 incidents) were property-damage-only. Injury-involved crashes accounted for 22.1% of the total, comprising 6 serious injury, 29 minor injury, and 32 possible injury crashes. There were 3 fatal crashes during this period, which resulted in a total of 3 fatalities.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
Serious Injury6serious injury crashes1.9%
Minor Injury29minor injury crashes9.1%
Possible Injury32possible injury crashes10.1%
No Injury247no injury crashes77.9%

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 most prominent contributing factor cited in crashes was 'Animal,' which was involved in 144 incidents, representing 45.4% of the total. Other leading factors included 'Lost Control' at 10.4% (33 crashes), 'Ran off road - straight' at 5.7% (18 crashes), and 'Driving too fast for conditions' at 5.4% (17 crashes). Together, these top four factors account for over two-thirds of all crashes with a determined cause.

Officer-Reported Primary Contributing Cause

Animal144 (45.4%)
Lost Control33 (10.4%)
Ran off road - straight18 (5.7%)
Driving too fast for conditions17 (5.4%)
Other (explain in narrative): Other10 (3.2%)
Ran off road - left9 (2.8%)
Driver Distraction: Exterior distraction9 (2.8%)
Driver Distraction: Other interior distraction8 (2.5%)
FTYROW: From stop sign7 (2.2%)
Exceeded authorized speed6 (1.9%)

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

Road & Environmental Conditions

A majority of crashes occurred in favorable conditions, with 116 incidents (36.6%) happening in clear weather and 118 (37.2%) on dry road surfaces. Crashes in daylight accounted for 108 incidents (34.1%). Adverse conditions played a role in a subset of crashes, with snow noted in 23 incidents and icy or frosty roads in 12 incidents. Crashes in darkness on unlighted roads were also significant, with 62 such events.

Weather

Clear116 (61.7%)
Cloudy35 (18.6%)
Snow23 (12.2%)
Blowing Snow5 (2.7%)
Fog, smoke, smog5 (2.7%)
Rain4 (2.1%)

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

Lighting

Daylight108 (56.5%)
Dark - roadway not lighted62 (32.5%)
Dark - roadway lighted11 (5.8%)
Dusk6 (3.1%)
Dawn4 (2.1%)

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

Road Surface

Dry118 (62.4%)
Snow25 (13.2%)
Gravel24 (12.7%)
Ice/frost12 (6.3%)
Wet8 (4.2%)
Slush2 (1.1%)

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

Vehicles & Demographics

Among the 498 people involved in crashes with a recorded age, the 55-64 age group was most represented with 78 individuals, followed by the 26-34 group (76 individuals) and the 16-20 group (75 individuals). An analysis of the 396 vehicles involved shows that Chevrolet (including 'CHEV') was the most frequent make with 106 vehicles, followed by Ford with 72 vehicles, and Dodge (including 'DODG') with 45 vehicles.

Top Vehicle Makes (396 vehicles)

1
FORD72 (18.2%)
2
CHEVROLET69 (17.4%)
3
CHEV37 (9.3%)
4
DODGE31 (7.8%)
5
PONTIAC16 (4%)
6
TOYOTA15 (3.8%)
7
DODG14 (3.5%)
8
CHRYSLER13 (3.3%)
9
JEEP9 (2.3%)
10
GMC9 (2.3%)

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

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

Sex Distribution (354 persons with recorded sex)

Male206 (58.2%)
Female148 (41.8%)

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

Major Cause

Collisions with an animal was the most frequently cited major cause, contributing to 144 crashes. The next most common causes were drivers losing control (33 crashes), running off a straight road (18 crashes), and driving too fast for conditions (17 crashes). These four causes represent the circumstances for a significant majority of incidents.

Major Cause

1
Animal144 (46.6%)
2
Lost Control33 (10.7%)
3
Ran off road - straight18 (5.8%)
4
Driving too fast for conditions17 (5.5%)
5
Other (explain in narrative): Other10 (3.2%)
6
Ran off road - left9 (2.9%)
7
Driver Distraction: Exterior distraction9 (2.9%)
8
Driver Distraction: Other interior distraction8 (2.6%)
9
FTYROW: From stop sign7 (2.3%)

Showing top 9 of 34 reported. 25 additional (54 total) not shown: Exceeded authorized speed, Other (explain in narrative): No improper action, Swerving/Evasive Action, Driver Distraction: Adjusting devices (radio, climate), Operating vehicle in an reckless, erratic, careless, negligent manner, FTYROW: Other (explain in narrative), FTYROW: Making left turn, Followed too close, Driver Distraction: Other electronic device activity, Other (explain in narrative): Vision obstructed, Ran Stop Sign, FTYROW: From parked position, FTYROW: At uncontrolled intersection, Operator inexperience, Failed to yield to emergency vehicle, Driver Distraction: Unrestrained animal, Passing: Other passing (explain in narrative), Passing: Where prohibited by signs/markings, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Inattentive/lost in thought, Traveling wrong way or on wrong side of road, Aggressive driving/road rage, Crossed centerline (undivided), FTYROW: To pedestrian, Improper Backing.

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 144 crashes. Collisions with another vehicle in traffic was the second most frequent event, occurring 47 times. Run-off-road events were also prevalent, with 31 crashes involving a ditch and 26 involving an overturn or rollover.

First Harmful Event

1
Collision with: Animal144 (47.2%)
2
Collision with: Vehicle in traffic47 (15.4%)
3
Collision with fixed object: Ditch31 (10.2%)
4
Non-collision events: Overturn/rollover26 (8.5%)
5
Other (explain in narrative)9 (3%)
6
Collision with: Parked motor vehicle8 (2.6%)
7
Collision with fixed object: Guardrail - face5 (1.6%)
8
Collision with fixed object: Embankment5 (1.6%)
9
Non-collision events: Other non-collision (explain in narrative)4 (1.3%)

Showing top 9 of 25 reported. 16 additional (26 total) not shown: Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Tree, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Re-entering roadway, Miscellaneous events: Hit and run, Collision with fixed object: Guardrail - end, Collision with fixed object: Utility pole/light support, Collision with: Work zone maintenance equipment, Non-collision events: Vehicle went airborne, Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Snow bank, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Curb/island/raised median, Collision with fixed object: Wall.

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

Roadway Junction / Feature

The vast majority of incidents occurred at non-junction locations, with 133 taking place on straight or curved road segments without special features. In contrast, 36 incidents were recorded at intersections, with T-intersections being the most common type (21 incidents), followed by four-way intersections (10 incidents). Driveway-related incidents accounted for another 14 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature133 (69.6%)
2
Intersection: T-intersection21 (11%)
3
Intersection: Four-way intersection10 (5.2%)
4
Non-intersection: Driveway access (related, not in)9 (4.7%)
5
Non-intersection: Driveway access (within)5 (2.6%)
6
Intersection: Other intersection (explain in narrative)3 (1.6%)
7
Interchange-related: Off-ramp2 (1%)
8
Intersection: Y-intersection2 (1%)
9
Non-intersection: Alley2 (1%)

Showing top 9 of 12 reported. 3 additional (4 total) not shown: Non-intersection: Other non-intersection (explain in narrative), Non-intersection: Railroad grade crossing, Non-intersection: Crossover-related.

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 176 units recorded. Light trucks and SUVs were also frequently involved, with 87 four-tire light trucks and 69 sport utility vehicles. Six motorcycles and six tractor/semi-trailers were also involved in crashes during this period.

Vehicle Type

"Other" combines 8 smaller categories (13 records): Farm tractor (3), Cargo/panel van (2), Maintenance/construction vehicle (2), All-terrain vehicle (ATV) (2), Single-unit truck (>= 3 axles) (1), Other (explain in narrative) (1), Farm equipment (explain in narrative) (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

A large majority of vehicles involved in crashes were in areas with no traffic controls present, accounting for 202 vehicles. For crashes where traffic controls were present, stop signs were the most common device, noted for 32 vehicles. A 'No Passing Zone' was the relevant traffic control for 12 vehicles.

Traffic Control Device

"Other" combines 1 smaller categories (2 records): Railway crossing device (2).

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 vehicle damage, with the direct front being the most damaged area on 69 vehicles. When including front corners, frontal impacts account for 118 vehicles. The top of the vehicle was the most damaged area in 25 cases, suggesting rollovers, while rear impacts were noted as the primary damage area for 18 vehicles.

Most Damaged Area

"Other" combines 10 smaller categories (59 records): Driver side - middle (12), Driver side - front (12), Passenger side - rear (11), Passenger side - front (9), Driver side - rear (6), Rear - passenger side corner (4), Other (explain in narrative) (2), Cargo loss (1), Undercarriage (1), Non-collision/no damage (1).

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

Impairment (Alcohol / Drugs)

Impairment was a factor in 14 crashes, representing 4.4% of all incidents. Of these, 12 crashes involved alcohol, while 2 involved a combination of alcohol and drugs. These figures represent the minimum number of crashes where impairment was officially recorded.

Crashes by City

Crash distribution across municipalities in Clayton County was led by Marquette, which recorded 28 incidents. Elkader had the second-highest volume with 15 crashes, followed by Guttenberg with 13 crashes and Monona with 12. Several other towns, including McGregor, Edgewood, and Clayton, recorded smaller numbers of incidents.

Crashes by City

1
MARQUETTE28 (28%)
2
ELKADER15 (15%)
3
GUTTENBERG13 (13%)
4
MONONA12 (12%)
5
MCGREGOR11 (11%)
6
EDGEWOOD4 (4%)
7
CLAYTON3 (3%)
8
POSTVILLE3 (3%)
9
STRAWBERRY POINT3 (3%)

Showing top 9 of 15 reported. 6 additional (8 total) not shown: FARMERSBURG, SAINT OLAF, ELKPORT, VOLGA CITY, GARNAVILLO, GARBER.

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, with 275 incidents occurring on such surfaces. However, a notable 39 crashes, or 12.4% of the total where surface type was specified, occurred on unpaved gravel or dirt roads, reflecting the county's rural road network.

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 a minority of crashes, a roadway factor was cited as a contributor. The most common was 'Surface condition (e.g. wet, icy),' which was noted in 38 incidents. Other factors such as debris or ruts were cited infrequently, each contributing to fewer than five crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)38 (80.9%)
2
Slippery, loose or worn surface3 (6.4%)
3
Debris2 (4.3%)
4
Ruts/holes/bumps1 (2.1%)
5
Traffic backup, prior crash1 (2.1%)
6
Traffic backup, prior non-recurring incident1 (2.1%)
7
Work Zone (roadway-related)1 (2.1%)

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,' impairment and fatigue were the leading alternative driver conditions noted. Fourteen drivers were identified as being under the influence of alcohol. Additionally, 7 drivers were noted as being asleep or fatigued, and 4 were recorded as being in an emotional state.

Driver Condition

1
Under the influence of alcohol14 (48.3%)
2
Asleep/fatigued7 (24.1%)
3
Emotional (e.g. depressed, angry)4 (13.8%)
4
Medical condition (seizure, reaction)2 (6.9%)
5
Under the influence of drugs/meds1 (3.4%)
6
Walks with a cane/crutches1 (3.4%)

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 included 248 incidents. A smaller number of crashes resulted in more significant damage, with 54 incidents estimated between $7,500 and $25,000, and 6 crashes causing 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, categorized as 'Non-collision,' were the dominant manner of collision, accounting for 195 incidents or 61.5% of the total. The next most frequent type was a rear-end collision, which occurred in 30 crashes (9.5%). Head-on collisions were reported in 6 incidents.

Manner of Collision

"Other" combines 3 smaller categories (7 records): Angle, oncoming left turn (4), Rear to rear (2), Rear to side (1).

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

Pre-Crash Driver Action

Among vehicles involved in crashes, the most common pre-crash action was 'Movement essentially straight,' recorded for 197 vehicles. Turning left was the action for 22 vehicles, while 12 vehicles were slowing or stopping and another 12 were negotiating a curve just before their respective incidents.

Pre-Crash Driver Action

1
Movement essentially straight197 (64%)
2
Turning left22 (7.1%)
3
Legally Parked13 (4.2%)
4
Slowing/stopping (deceleration)12 (3.9%)
5
Backing12 (3.9%)
6
Negotiating a curve12 (3.9%)
7
Turning right11 (3.6%)
8
Stopped in traffic10 (3.2%)
9
Other (explain in narrative)6 (1.9%)

Showing top 9 of 16 reported. 7 additional (13 total) not shown: Overtaking/passing, Illegally Parked/Unattended, Entering a parked position, Accelerating in road, Making U-turn, Leaving a parked position, Changing lanes.

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

Person Type

Of the 498 individuals involved in crashes, the vast majority were drivers, accounting for 468 people (94.0%). Passengers comprised 28 of the individuals involved. The data also includes one pedestrian and one person classified as an '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 498 people involved in crashes, 3 individuals sustained fatal injuries. A total of 97 people were injured, with 7 classified as serious injuries, 40 as minor injuries, and 50 as possible injuries. The remaining individuals were either not injured or had an unknown injury status.

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 84 vehicle occupants for whom safety equipment use was recorded, 66 (78.6%) were using a shoulder and lap belt. Conversely, 14 individuals, or 16.7% of this subset, were recorded as using no restraints at the time of the crash.

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, accounting for 243 of the 317 total incidents (76.6%). Crashes involving two vehicles numbered 69, while multi-vehicle pileups were rare, with only 5 crashes involving 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: 317
  • Total persons involved: 498
  • Total vehicles involved: 396

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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