Yearly Traffic Safety Analysis

342 CRASHES IN
IOWA, IA
2015

In 2015, Henry County recorded 342 traffic crashes, which resulted in 3 fatalities and 109 injuries. The single most prominent contributing factor in these incidents was collisions with animals, which accounted for 34.5% of all crashes.

342

Total Crash Events

3

Persons Killed

109

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, motorists accounted for all 3 fatalities and 107 of the 109 total injuries recorded in Henry County. No pedestrians were killed or injured in traffic crashes during this period. One cyclist was reported as injured, but there were no cyclist fatalities.

0

Cyclists Killed

3

Motorists Killed

0

Other Killed

1

Cyclists Injured

107

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

Crashes in Henry County were most frequent on Wednesdays, which saw 65 incidents in 2015. The single busiest hour for crashes was 3 p.m., with 31 events recorded. Overall, collisions occurred more often during daylight hours, which accounted for 164 crashes, compared to 81 crashes during dark, dawn, or dusk conditions.

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 in 2015, approximately 76.3% (261 incidents), resulted in no injuries. The remaining incidents involved at least one injury or fatality. There were 3 fatal crashes recorded, which resulted in a total of 3 fatalities.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
Serious Injury2serious injury crashes0.6%
Minor Injury33minor injury crashes9.6%
Possible Injury43possible injury crashes12.6%
No Injury261no injury crashes76.3%

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 frequently cited contributing factor in Henry County crashes was 'Animal,' accounting for 118 incidents, or 34.5% of the total. Following this, 'Lost Control' was noted in 31 crashes (9.1%), and 'Ran off road - straight' was a factor in 19 crashes (5.6%). Failure to yield the right-of-way from a stop sign contributed to 16 crashes.

Officer-Reported Primary Contributing Cause

Animal118 (34.5%)
Lost Control31 (9.1%)
Ran off road - straight19 (5.6%)
FTYROW: From stop sign16 (4.7%)
Followed too close15 (4.4%)
Driving too fast for conditions14 (4.1%)
Ran Stop Sign12 (3.5%)
Ran off road - left11 (3.2%)
Other (explain in narrative): Other10 (2.9%)
FTYROW: Making left turn7 (2%)

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 substantial portion of crashes occurred in ideal driving conditions, with 51.7% of incidents happening on dry roads (177 crashes) and 48% taking place in daylight (164 crashes). Crashes during clear weather accounted for 158 incidents. Adverse weather such as snow, rain, or freezing rain was present in a combined 26 crashes.

Weather

Clear158 (64.5%)
Cloudy51 (20.8%)
Snow12 (4.9%)
Fog, smoke, smog8 (3.3%)
Freezing rain/drizzle7 (2.9%)
Rain7 (2.9%)
Severe Winds1 (0.4%)
Blowing Snow1 (0.4%)

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

Lighting

Daylight164 (66.9%)
Dark - roadway not lighted54 (22.0%)
Dark - roadway lighted13 (5.3%)
Dawn10 (4.1%)
Dusk4 (1.6%)

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

Road Surface

Dry177 (72.0%)
Snow19 (7.7%)
Wet18 (7.3%)
Ice/frost14 (5.7%)
Gravel10 (4.1%)
Slush5 (2.0%)
Mud, dirt2 (0.8%)
Other (explain in narrative)1 (0.4%)

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 26-34 age group was the most frequently represented, with 111 individuals, followed by the 45-54 age group with 99 individuals. Among the 483 vehicles involved, Ford was the most common make with 72 vehicles, followed by 'CHEV' with 50 vehicles and 'DODGE' with 40 vehicles.

Top Vehicle Makes (483 vehicles)

1
FORD72 (14.9%)
2
CHEV50 (10.4%)
3
DODGE40 (8.3%)
4
CHEVROLET38 (7.9%)
5
DODG26 (5.4%)
6
TOYT23 (4.8%)
7
TOYOTA18 (3.7%)
8
JEEP17 (3.5%)
9
PONT16 (3.3%)
10
GMC15 (3.1%)

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

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

Sex Distribution (438 persons with recorded sex)

Male260 (59.4%)
Female178 (40.6%)

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

Major Cause

The primary major cause identified in crashes was interaction with an animal, cited in 118 incidents (34.5%). 'Lost Control' was the second most common cause, contributing to 31 crashes (9.1%), followed by 'Ran off road - straight' with 19 crashes (5.6%). Other notable causes included 'Failure to yield from a stop sign' (16 crashes) and 'Followed too close' (15 crashes).

Major Cause

1
Animal118 (35.5%)
2
Lost Control31 (9.3%)
3
Ran off road - straight19 (5.7%)
4
FTYROW: From stop sign16 (4.8%)
5
Followed too close15 (4.5%)
6
Driving too fast for conditions14 (4.2%)
7
Ran Stop Sign12 (3.6%)
8
Ran off road - left11 (3.3%)
9
Other (explain in narrative): Other10 (3%)

Showing top 9 of 44 reported. 35 additional (86 total) not shown: FTYROW: Making left turn, Driver Distraction: Other interior distraction, FTYROW: From parked position, Made improper turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Reaching for object(s)/fallen object(s), Ran Traffic Signal, FTYROW: From driveway, Driver Distraction: Exterior distraction, FTYROW: From yield sign, FTYROW: Other (explain in narrative), Driver Distraction: Inattentive/lost in thought, Exceeded authorized speed, Driver Distraction: Adjusting devices (radio, climate), Driver Distraction: Manual operation of an electronic communication device, Improper Backing, Driver Distraction: Passenger, Other (explain in narrative): No improper action, Aggressive driving/road rage, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Ran off road - right, Swerving/Evasive Action, Traveling wrong way or on wrong side of road, Passing: Through/around barrier, Passing: Where prohibited by signs/markings, Passing: With insufficient distance/inadequate visibility, Disregarded RR Signal, FTYROW: To pedestrian, Drove around RR grade crossing gates, Crossed centerline (undivided), FTYROW: At uncontrolled intersection, Failed to keep in proper lane, Cargo/equipment loss or shift, Equipment failure.

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 122 crashes. This was closely followed by 'Collision with an animal,' documented in 118 incidents. Collisions with fixed objects were also frequent, with the most common being collisions with a ditch (30 crashes) and non-collision overturns/rollovers (18 crashes).

First Harmful Event

1
Collision with: Vehicle in traffic122 (35.8%)
2
Collision with: Animal118 (34.6%)
3
Collision with fixed object: Ditch30 (8.8%)
4
Non-collision events: Overturn/rollover18 (5.3%)
5
Collision with fixed object: Tree7 (2.1%)
6
Collision with fixed object: Bridge/bridge rail parapet6 (1.8%)
7
Collision with fixed object: Utility pole/light support5 (1.5%)
8
Collision with fixed object: Guardrail - end4 (1.2%)
9
Collision with fixed object: Guardrail - face4 (1.2%)

Showing top 9 of 24 reported. 15 additional (27 total) not shown: Collision with: Parked motor vehicle, Collision with fixed object: Traffic sign support, Collision with fixed object: Building, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Other non-fixed object (explain in narrative), Miscellaneous events: Hit and run, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Bridge pier or support, Collision with fixed object: Traffic signal support, Other (explain in narrative), Collision with fixed object: Mailbox, Collision with: Re-entering roadway, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Cable barrier.

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

Roadway Junction / Feature

Analysis of crash locations shows that a majority of incidents occurred on non-intersection road segments, with 130 crashes coded as 'Non-junction/no special feature.' In contrast, 62 crashes occurred at four-way intersections and 12 at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature130 (53.1%)
2
Intersection: Four-way intersection62 (25.3%)
3
Intersection: T-intersection12 (4.9%)
4
Non-intersection: Driveway access (related, not in)8 (3.3%)
5
Non-intersection: Crossover-related7 (2.9%)
6
Non-intersection: Other non-intersection (explain in narrative)5 (2%)
7
Intersection: Other intersection (explain in narrative)4 (1.6%)
8
Interchange-related: On-ramp merge area4 (1.6%)
9
Non-intersection: Driveway access (within)3 (1.2%)

Showing top 9 of 15 reported. 6 additional (10 total) not shown: Interchange-related: Off-ramp, Interchange-related: Off-ramp, diverge area, Non-intersection: Railroad grade crossing, Interchange-related: On-ramp, Intersection: Traffic circle, 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 209 of the 483 vehicles. Light trucks and pickups were the second most frequent with 99 vehicles, followed by sport utility vehicles with 89. Commercial tractor-trailers were involved in 19 incidents, while motorcycles were involved in 3.

Vehicle Type

"Other" combines 7 smaller categories (13 records): Farm tractor (4), Motorcycle (3), Cargo/panel van (2), School bus (seats > 15) (1), Truck tractor (bobtail) (1), Truck/trailer (1), Farm equipment (explain in narrative) (1).

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

Traffic Control Device

A significant majority of incidents, 261 cases, occurred where no traffic controls were present. For crashes at controlled locations, stop signs were the most common form of traffic control, noted in 67 cases. Traffic signals were present in 15 crashes.

Traffic Control Device

"Other" combines 3 smaller categories (8 records): Other (explain in narrative) (4), Railway crossing device (3), School zone 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 area of damage, recorded in 106 instances. Rear impacts, often associated with rear-end collisions, were noted in 36 cases. Side impacts were also common, with 23 vehicles damaged on the driver's side middle and 21 on the passenger's side middle.

Most Damaged Area

"Other" combines 10 smaller categories (92 records): Rear - driver side corner (15), Passenger side - rear (14), Driver side - rear (13), Driver side - front (12), Rear - passenger side corner (12), Top (11), Other (explain in narrative) (7), Non-collision/no damage (4), Undercarriage (3), Cargo loss (1).

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

Impairment (Alcohol / Drugs)

Driver impairment was noted as a factor in 11 crashes, representing 3.2% of all incidents. Of these, 9 cases involved alcohol, 1 involved drugs, and 1 involved both alcohol and drugs.

Crashes by City

Crash data is available for several municipalities, with Mount Pleasant reporting the highest volume at 112 crashes. New London followed with 7 crashes, and Olds recorded 6 crashes. Other towns like Winfield (5 crashes) and Salem (3 crashes) reported fewer incidents.

Crashes by City

1
MOUNT PLEASANT112 (80.6%)
2
NEW LONDON7 (5%)
3
OLDS6 (4.3%)
4
WINFIELD5 (3.6%)
5
SALEM3 (2.2%)
6
MOUNT UNION2 (1.4%)
7
ROME2 (1.4%)
8
WAYLAND1 (0.7%)
9
HINTON1 (0.7%)

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, 313 incidents, occurred on paved roads. Crashes on unpaved surfaces like gravel or dirt accounted for 27 incidents, representing approximately 7.9% of the crashes where road surface type was specified.

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, 'Surface condition' such as wet or icy roads was the most common, cited in 28 incidents. Other noted factors were minor, including 'Debris' in the roadway (2 incidents) and 'Obstruction in roadway' (1 incident).

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)28 (84.8%)
2
Debris2 (6.1%)
3
Obstruction in roadway1 (3%)
4
Slippery, loose or worn surface1 (3%)
5
Traffic backup, prior crash1 (3%)

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,' 11 drivers were noted as being under the influence of alcohol. Driver fatigue was also a factor, with 9 drivers recorded as 'asleep/fatigued.' An emotional state, such as anger or depression, was noted for 4 drivers.

Driver Condition

1
Under the influence of alcohol11 (44%)
2
Asleep/fatigued9 (36%)
3
Emotional (e.g. depressed, angry)4 (16%)
4
Medical condition (seizure, reaction)1 (4%)

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

Property Damage

The estimated cost of property damage was most frequently in the $1,500 to $7,500 range, which applied to 257 crashes (75.1%). A smaller number of high-cost incidents occurred, with 9 crashes resulting in property damage estimated at over $25,000. Crashes with damage between $7,500 and $25,000 accounted for 68 incidents.

Property Damage

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

Manner of Collision

Nearly half of all crashes, 170 incidents or 49.7%, were single-vehicle, non-collision events such as running off the road or overturning. Among multi-vehicle crashes, rear-end and broadside collisions were the most common types, each accounting for 43 incidents (12.6% of the total).

Manner of Collision

"Other" combines 3 smaller categories (8 records): Rear to rear (3), Head-on (front to front) (3), Other (explain in narrative) (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 269 of the 483 vehicles involved in crashes. Turning maneuvers were also frequent precursors to crashes, with 33 vehicles turning left and 16 vehicles turning right immediately before their respective incidents.

Pre-Crash Driver Action

1
Movement essentially straight269 (65.1%)
2
Turning left33 (8%)
3
Turning right16 (3.9%)
4
Stopped in traffic15 (3.6%)
5
Backing14 (3.4%)
6
Slowing/stopping (deceleration)13 (3.1%)
7
Legally Parked12 (2.9%)
8
Negotiating a curve10 (2.4%)
9
Other (explain in narrative)7 (1.7%)

Showing top 9 of 17 reported. 8 additional (24 total) not shown: Overtaking/passing, Entering traffic lane (merging), Making U-turn, Accelerating in road, Leaving a parked position, Illegally Parked/Unattended, Changing lanes, Leaving traffic lane.

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

Person Type

Of the 595 individuals involved in crashes, the vast majority, 561 people (94.3%), were drivers. Passengers accounted for 32 of the individuals involved. The data also includes one bicyclist and one 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

Among all 595 people involved in crashes, 3 sustained fatal injuries. An additional 109 individuals were injured, including 5 with serious injuries, 39 with minor injuries, and 65 with possible injuries. The remaining 483 individuals were not 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 the limited data available for safety equipment use, 73 occupants were recorded as using both a shoulder and lap belt. In 12 instances, it was noted that no safety equipment was used, representing 13.6% of the subset with available data. An additional 3 individuals used only a lap belt.

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 of incident, accounting for 210 of the 342 total crashes (61.4%). Two-vehicle collisions made up another 124 incidents (36.3%). Crashes involving three or more vehicles were less frequent, with a total of 8 such events 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: 342
  • Total persons involved: 595
  • Total vehicles involved: 483

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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