Yearly Traffic Safety Analysis

304 CRASHES IN
IOWA, IA
2015

In 2015, Clay County recorded 304 traffic crashes, resulting in 1 fatality and 93 injuries. The single most notable statistical finding from the data is that collisions with animals were the leading contributing factor, accounting for 57 incidents, or nearly 19% of all crashes.

304

Total Crash Events

1

Persons Killed

93

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

Of the 94 people killed or injured in crashes, the single fatality was a pedestrian. An additional 5 pedestrians and 5 cyclists were injured. The vast majority of injuries were sustained by motor vehicle occupants, with 82 motorists injured and none killed.

1

Pedestrians Killed

0

Cyclists Killed

0

Motorists Killed

0

Other Killed

5

Pedestrians Injured

5

Cyclists Injured

82

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 occurrences in Clay County peaked on Wednesdays, which saw 62 incidents, and during the 3 p.m. hour, with 34 crashes recorded. The majority of crashes, 193 out of 304, occurred during daylight hours. Weekdays saw higher crash volumes, with Wednesday (62), Friday (59), and Monday (48) being the most frequent days for incidents.

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

The majority of crashes, 73.4% (223 incidents), resulted in no injuries. Crashes involving an injury accounted for 80 of the total 304 incidents, with severities ranging from possible (43 crashes) to serious (5 crashes). There was one fatal crash recorded in 2015, which resulted in one fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury5serious injury crashes1.6%
Minor Injury32minor injury crashes10.5%
Possible Injury43possible injury crashes14.1%
No Injury223no injury crashes73.4%

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

Collisions involving animals were the leading contributing factor, accounting for 57 crashes, or 18.8% of the total. Failure to yield the right-of-way was also a prominent factor, cited in 22 crashes at stop signs and 14 at uncontrolled intersections. Other significant factors included drivers losing control (21 crashes) and driving too fast for conditions (17 crashes).

Officer-Reported Primary Contributing Cause

Animal57 (18.8%)
Other (explain in narrative): Other27 (8.9%)
FTYROW: From stop sign22 (7.2%)
Lost Control21 (6.9%)
Driving too fast for conditions17 (5.6%)
Ran off road - straight14 (4.6%)
FTYROW: At uncontrolled intersection14 (4.6%)
FTYROW: Making left turn10 (3.3%)
Ran off road - left10 (3.3%)
Followed too close10 (3.3%)

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 happened in favorable conditions, with 63.5% (193) occurring in daylight, 55.6% (169) in clear weather, and 57.2% (174) on dry road surfaces. However, adverse road surface conditions were present in a notable number of incidents, including 35 crashes on snow, 26 on wet roads, and 11 on ice or frost. Snow was falling in 15 crashes and rain in 14.

Weather

Clear169 (66.5%)
Cloudy49 (19.3%)
Snow15 (5.9%)
Rain14 (5.5%)
Blowing Snow3 (1.2%)
Fog, smoke, smog2 (0.8%)
Freezing rain/drizzle2 (0.8%)

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

Lighting

Daylight193 (75.1%)
Dark - roadway not lighted28 (10.9%)
Dark - roadway lighted22 (8.6%)
Dusk8 (3.1%)
Dawn5 (1.9%)
Dark - unknown roadway lighting1 (0.4%)

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

Road Surface

Dry174 (67.7%)
Snow35 (13.6%)
Wet26 (10.1%)
Ice/frost11 (4.3%)
Gravel8 (3.1%)
Sand1 (0.4%)
Mud, dirt1 (0.4%)
Slush1 (0.4%)

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

Vehicles & Demographics

Among the 582 people involved in crashes, the most represented age groups were 26-34 years old (96 individuals) and 16-20 years old (87 individuals). Of the 486 vehicles involved, the most frequent makes were Chevrolet (126 vehicles), Ford (77 vehicles), and Dodge (38 vehicles).

Top Vehicle Makes (486 vehicles)

1
FORD77 (15.8%)
2
CHEV72 (14.8%)
3
CHEVROLET54 (11.1%)
4
PONT24 (4.9%)
5
DODG24 (4.9%)
6
BUIC20 (4.1%)
7
GMC18 (3.7%)
8
CHRY16 (3.3%)
9
DODGE14 (2.9%)
10
TOYT11 (2.3%)

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

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

Sex Distribution (439 persons with recorded sex)

Male236 (53.8%)
Female203 (46.2%)

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 of crashes was an animal in the roadway, contributing to 57 incidents. Failure to yield the right-of-way was also a prominent cause, with 22 crashes resulting from failing to yield at a stop sign and 14 at an uncontrolled intersection. Losing control of the vehicle was cited in 21 crashes, and driving too fast for conditions contributed to another 17.

Major Cause

1
Animal57 (19.6%)
2
Other (explain in narrative): Other27 (9.3%)
3
FTYROW: From stop sign22 (7.6%)
4
Lost Control21 (7.2%)
5
Driving too fast for conditions17 (5.8%)
6
Ran off road - straight14 (4.8%)
7
FTYROW: At uncontrolled intersection14 (4.8%)
8
FTYROW: Making left turn10 (3.4%)
9
Ran off road - left10 (3.4%)

Showing top 9 of 38 reported. 29 additional (99 total) not shown: Followed too close, FTYROW: From yield sign, Driver Distraction: Other interior distraction, Other (explain in narrative): No improper action, Operating vehicle in an reckless, erratic, careless, negligent manner, Ran Stop Sign, Swerving/Evasive Action, Crossed centerline (undivided), Ran Traffic Signal, Improper or erratic lane changing, Made improper turn, Exceeded authorized speed, FTYROW: From driveway, FTYROW: From parked position, Driver Distraction: Inattentive/lost in thought, Improper Backing, FTYROW: Other (explain in narrative), Driver Distraction: Reaching for object(s)/fallen object(s), Driver Distraction: Exterior distraction, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Ran off road - right, FTYROW: Making right turn on red signal, Driver Distraction: Talking on a hand-held device, Driver Distraction: Adjusting devices (radio, climate), FTYROW: To pedestrian, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Other electronic device activity, Failed to keep in proper lane.

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, which occurred in 157 of the 304 crashes. Collisions with animals were the second most frequent initial event, accounting for 56 incidents. Single-vehicle events were also common, including 24 overturns or rollovers and 20 crashes where the first harmful event was colliding with a ditch.

First Harmful Event

1
Collision with: Vehicle in traffic157 (52.2%)
2
Collision with: Animal56 (18.6%)
3
Non-collision events: Overturn/rollover24 (8%)
4
Collision with fixed object: Ditch20 (6.6%)
5
Collision with: Non-motorist (see non-motorist section - NOT a unit)10 (3.3%)
6
Collision with: Parked motor vehicle6 (2%)
7
Other (explain in narrative)4 (1.3%)
8
Collision with fixed object: Utility pole/light support3 (1%)
9
Miscellaneous events: Hit and run3 (1%)

Showing top 9 of 23 reported. 14 additional (18 total) not shown: Non-collision events: Vehicle went airborne, Collision with fixed object: Other fixed object (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Non-collision events: Fell/jumped from vehicle, Non-collision events: Jackknife, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Embankment, Collision with fixed object: Snow bank, Collision with fixed object: Traffic signal support, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Other non-fixed object (explain in narrative), Collision with: Thrown or falling object, Collision with fixed object: Other traffic barrier (explain in narrative).

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

Roadway Junction / Feature

Crashes were slightly more common on non-intersection road segments, with 127 incidents occurring at non-junction locations. Intersections accounted for 109 crashes, the majority of which (98) happened at four-way intersections. An additional 11 crashes were related to driveway access.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature127 (49.6%)
2
Intersection: Four-way intersection98 (38.3%)
3
Intersection: T-intersection10 (3.9%)
4
Non-intersection: Driveway access (related, not in)8 (3.1%)
5
Non-intersection: Crossover-related4 (1.6%)
6
Non-intersection: Driveway access (within)3 (1.2%)
7
Non-intersection: Railroad grade crossing3 (1.2%)
8
Non-intersection: Other non-intersection (explain in narrative)1 (0.4%)
9
Intersection: Y-intersection1 (0.4%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Non-intersection: Alley.

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 200 of the 486 vehicles. Sport utility vehicles (107 vehicles) and light trucks or pickups (104 vehicles) were also frequently involved. Commercial vehicles and motorcycles represented a smaller share, with 13 tractor-trailers and 6 motorcycles involved in incidents.

Vehicle Type

"Other" combines 7 smaller categories (20 records): Single unit truck (2-axle, 6-tire) (4), Single-unit truck (>= 3 axles) (4), Moped (4), Farm tractor (3), School bus (seats > 15) (2), Truck/trailer (2), Other heavy truck (> 10000 lbs) (cannot classify) (1).

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

Traffic Control Device

For a majority of vehicles involved in crashes, no traffic controls were present, a situation noted for 286 vehicles. Where traffic controls were a factor, traffic signals were present for 74 vehicles and stop signs for 54 vehicles. Yield signs were noted for 16 vehicles involved in crashes.

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 vehicle damage, with 129 vehicles sustaining damage primarily to the front. Side impacts were also frequent, with damage reported to the driver's side on 71 vehicles and the passenger's side on 60 vehicles. Rear-end collisions were indicated by the 46 vehicles that sustained damage to the rear.

Most Damaged Area

"Other" combines 10 smaller categories (104 records): Passenger side - rear (22), Driver side - rear (19), Passenger side - front (15), Rear - passenger side corner (13), Other (explain in narrative) (9), Non-collision/no damage (9), Top (9), Rear - driver side corner (6), Cargo loss (1), Undercarriage (1).

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

Crashes by City

Within Clay County, the city of Spencer accounted for the highest volume of crashes, with 177 incidents. The towns of Everly and Dickens followed with 9 crashes each. Other municipalities such as Webb and Greenville recorded 3 crashes apiece.

Crashes by City

1
SPENCER177 (85.9%)
2
EVERLY9 (4.4%)
3
DICKENS9 (4.4%)
4
WEBB3 (1.5%)
5
GREENVILLE3 (1.5%)
6
PETERSON2 (1%)
7
GILLETT GROVE2 (1%)
8
ROYAL1 (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, 273, occurred on paved roads. Crashes on unpaved surfaces, such as gravel or dirt roads, accounted for 30 incidents, representing nearly 10% of the total for which this data was recorded.

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 identified as contributing to a crash, adverse surface conditions such as wet or icy roads were the most common, cited in 30 incidents. An additional 7 crashes were attributed to a slippery, loose, or worn surface. One crash was related to a work zone.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)30 (71.4%)
2
Slippery, loose or worn surface7 (16.7%)
3
Obstruction in roadway2 (4.8%)
4
Disabled vehicle1 (2.4%)
5
Ruts/holes/bumps1 (2.4%)
6
Work Zone (roadway-related)1 (2.4%)

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,' several other driver conditions were noted. The most frequently recorded conditions were being under the influence of alcohol (9 drivers) and being asleep or fatigued (8 drivers). An emotional state was cited for 3 drivers, and a medical condition was noted for 2 drivers.

Driver Condition

1
Under the influence of alcohol9 (40.9%)
2
Asleep/fatigued8 (36.4%)
3
Emotional (e.g. depressed, angry)3 (13.6%)
4
Medical condition (seizure, reaction)2 (9.1%)

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

Property Damage

The estimated property damage was most commonly in the $1,500 to $7,500 range, which applied to 229 crashes (75.3%). A smaller number of crashes resulted in higher damage estimates, with 55 incidents falling in the $7,500 to $25,000 range and 3 crashes exceeding $25,000 in damage.

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 incident was a non-collision, single-vehicle crash, such as a run-off-road or overturn, which accounted for 114 cases (37.5%). Among multi-vehicle crashes, broadside collisions were the most common with 65 incidents (21.4%), followed by rear-end collisions with 50 incidents (16.4%).

Manner of Collision

"Other" combines 2 smaller categories (9 records): Head-on (front to front) (5), Sideswipe, opposite direction (4).

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

Pre-Crash Driver Action

The predominant pre-crash action for vehicles involved was moving essentially straight, which was the case for 298 vehicles. Maneuvering actions were less common, with 37 vehicles turning left and 13 turning right prior to impact. Stationary vehicles were also involved, including 24 legally parked vehicles and 23 vehicles stopped in traffic.

Pre-Crash Driver Action

1
Movement essentially straight298 (66.8%)
2
Turning left37 (8.3%)
3
Legally Parked24 (5.4%)
4
Stopped in traffic23 (5.2%)
5
Slowing/stopping (deceleration)17 (3.8%)
6
Turning right13 (2.9%)
7
Backing12 (2.7%)
8
Other (explain in narrative)6 (1.3%)
9
Changing lanes4 (0.9%)

Showing top 9 of 15 reported. 6 additional (12 total) not shown: Negotiating a curve, Illegally Parked/Unattended, Leaving a parked position, Leaving traffic lane, Entering a parked position, Starting in road.

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

Pedestrian/Cyclist Action

Among the non-motorists whose actions were recorded, the most common action prior to the crash was entering or crossing the roadway, which was noted in 9 instances. Other actions included one case of a person dealing with a disabled vehicle and one person moving along the roadway with traffic.

Pedestrian/Cyclist Action

1
Entering or crossing roadway9 (69.2%)
2
Other2 (15.4%)
3
Disabled vehicle-related/pushing vehicle1 (7.7%)
4
Movement: Along roadway with traffic1 (7.7%)

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

Person Type

Of the 582 individuals involved in crashes, the vast majority (553, or 95.0%) were drivers of motor vehicles. Passengers accounted for 16 of the individuals, while vulnerable road users included 6 pedestrians and 5 bicyclists.

Person Type

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

Person Injury Severity

Across all people involved in crashes, a total of 94 individuals sustained some level of injury or were fatally injured. This included one fatality, 6 serious injuries, 40 minor injuries, and 47 possible injuries. The majority of reported injuries were classified as either minor or 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 small subset of 49 participants for whom safety equipment use was recorded, 39 were noted as using a shoulder and lap belt. Four individuals were recorded as using no safety equipment. Use of child safety seats was noted for 3 children, and 3 individuals 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 crash configuration, accounting for 157 of the 304 total incidents. Single-vehicle crashes were also very frequent, with 133 incidents recorded, representing 43.8% of all crashes. Crashes involving three vehicles were less common, with 14 such incidents reported.

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: 304
  • Total persons involved: 582
  • Total vehicles involved: 486

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

ThatCarHitMe.com · An Injuria.ai Company