Yearly Traffic Safety Analysis

228 CRASHES IN
IOWA, IA
2015

In 2015, Mills County recorded 228 vehicle crashes, resulting in 2 fatalities and 113 injuries. A significant portion of these incidents, 66.2%, were single-vehicle, non-collision events. The leading contributing factor cited in crashes was encounters with animals, accounting for 25.9% of all incidents.

228

Total Crash Events

2

Persons Killed

113

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 fatalities and injuries in Mills County in 2015 involved motorists. A total of 2 motorists were killed and 113 were injured in crashes. There were no recorded fatalities or injuries involving pedestrians or cyclists during this period.

2

Motorists Killed

113

Motorists Injured

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in Mills County occurred most frequently on Wednesdays, which saw 44 incidents in 2015. The peak time for crashes was the 4 p.m. hour, with 18 events recorded. Overall, more crashes happened during daylight hours (120) compared to all dark conditions combined (73).

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 228 crashes, 63.2% resulted in no injuries, being classified as property-damage-only events. The remaining 36.8% of crashes involved some level of injury, including 17 serious injury crashes and 31 minor injury crashes. There were 2 fatal crashes during this period, which resulted in a total of 2 fatalities.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
Serious Injury17serious injury crashes7.5%
Minor Injury31minor injury crashes13.6%
Possible Injury34possible injury crashes14.9%
No Injury144no injury crashes63.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Top Contributing Factors

The most common contributing factor identified in crashes was an animal in the roadway, cited in 59 incidents (25.9%). Losing control of the vehicle was the second most frequent factor, contributing to 34 crashes (14.9%). Other significant factors included running off a straight road (19 crashes) and driving too fast for conditions (16 crashes).

Officer-Reported Primary Contributing Cause

Animal59 (25.9%)
Lost Control34 (14.9%)
Ran off road - straight19 (8.3%)
Driving too fast for conditions16 (7%)
FTYROW: From stop sign12 (5.3%)
Operating vehicle in an reckless, erratic, careless, negligent manner11 (4.8%)
Driver Distraction: Other interior distraction8 (3.5%)
Ran off road - left6 (2.6%)
Other (explain in narrative): Other6 (2.6%)
Exceeded authorized speed5 (2.2%)

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

Road & Environmental Conditions

The majority of crashes occurred in favorable conditions, with 65.4% on dry roads and 52.6% in clear weather. Similarly, 120 crashes (52.6%) took place during daylight hours. Adverse conditions still played a role, as 25 crashes happened on wet roads and 65 occurred on unlighted roadways in the dark.

Weather

Clear120 (58.0%)
Cloudy58 (28.0%)
Rain17 (8.2%)
Snow7 (3.4%)
Freezing rain/drizzle2 (1.0%)
Fog, smoke, smog2 (1.0%)
Severe Winds1 (0.5%)

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

Lighting

Daylight120 (58.0%)
Dark - roadway not lighted65 (31.4%)
Dawn9 (4.3%)
Dark - roadway lighted8 (3.9%)
Dusk5 (2.4%)

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

Road Surface

Dry149 (71.3%)
Wet25 (12.0%)
Gravel14 (6.7%)
Ice/frost12 (5.7%)
Snow4 (1.9%)
Mud, dirt2 (1.0%)
Slush2 (1.0%)
Other (explain in narrative)1 (0.5%)

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 represented, with 66 individuals, followed by the 45-54 age group with 61 individuals. Among the 305 vehicles involved, Ford was the most frequent make, appearing in 64 instances. Chevrolet (including abbreviated names) was second with 54 vehicles, and Dodge was third with 24 vehicles.

Top Vehicle Makes (305 vehicles)

1
FORD64 (21%)
2
CHEV31 (10.2%)
3
CHEVROLET23 (7.5%)
4
DODG15 (4.9%)
5
TOYOTA13 (4.3%)
6
CHRY10 (3.3%)
7
GMC10 (3.3%)
8
KIA9 (3%)
9
DODGE9 (3%)
10
HONDA9 (3%)

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

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

Sex Distribution (260 persons with recorded sex)

Male136 (52.3%)
Female124 (47.7%)

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

Major Cause

The leading major cause of crashes was attributed to animals, which was a factor in 59 incidents. Losing control of the vehicle was the second-most cited cause, contributing to 34 crashes. Other frequently recorded causes include running off a straight road (19 crashes), driving too fast for conditions (16 crashes), and failure to yield the right-of-way from a stop sign (12 crashes).

Major Cause

1
Animal59 (26.3%)
2
Lost Control34 (15.2%)
3
Ran off road - straight19 (8.5%)
4
Driving too fast for conditions16 (7.1%)
5
FTYROW: From stop sign12 (5.4%)
6
Operating vehicle in an reckless, erratic, careless, negligent manner11 (4.9%)
7
Driver Distraction: Other interior distraction8 (3.6%)
8
Ran off road - left6 (2.7%)
9
Other (explain in narrative): Other6 (2.7%)

Showing top 9 of 33 reported. 24 additional (53 total) not shown: Exceeded authorized speed, FTYROW: Other (explain in narrative), Driver Distraction: Inattentive/lost in thought, Followed too close, Made improper turn, FTYROW: Making left turn, Swerving/Evasive Action, Ran off road - right, Improper Backing, FTYROW: From parked position, Equipment failure, Driver Distraction: Manual operation of an electronic communication device, Other (explain in narrative): No improper action, Other (explain in narrative): Disregarded signs/road markings, FTYROW: From yield sign, Driver Distraction: Reaching for object(s)/fallen object(s), Failed to keep in proper lane, Improper or erratic lane changing, Driver Distraction: Other electronic device activity, Driver Distraction: Exterior distraction, Over correcting/over steering, Driver Distraction: Adjusting devices (radio, climate), Downhill runaway, Crossed centerline (undivided).

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 59 crashes. The second most frequent event was a collision with another vehicle in traffic, occurring 52 times. Run-off-road events were also common, with 28 crashes involving an overturn or rollover and 18 involving a collision with a ditch.

First Harmful Event

1
Collision with: Animal59 (26.1%)
2
Collision with: Vehicle in traffic52 (23%)
3
Non-collision events: Overturn/rollover28 (12.4%)
4
Collision with fixed object: Ditch18 (8%)
5
Collision with fixed object: Utility pole/light support8 (3.5%)
6
Other (explain in narrative)7 (3.1%)
7
Collision with: Struck/struck by object/cargo/person from other vehicle6 (2.7%)
8
Collision with: Parked motor vehicle6 (2.7%)
9
Collision with fixed object: Embankment5 (2.2%)

Showing top 9 of 29 reported. 20 additional (37 total) not shown: Collision with fixed object: Cable barrier, Collision with fixed object: Traffic sign support, Collision with fixed object: Ground, Collision with fixed object: Culvert/pipe opening, Collision with fixed object: Guardrail - face, Collision with fixed object: Curb/island/raised median, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Other traffic barrier (explain in narrative), Non-collision events: Jackknife, Collision with fixed object: Traffic signal support, Collision with: Re-entering roadway, Collision with fixed object: Mailbox, Collision with fixed object: Guardrail - end, Miscellaneous events: Vehicle out of gear/rolled, Collision with fixed object: Bridge/bridge rail parapet, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge pier or support, Non-collision events: Vehicle went airborne, Collision with fixed object: Tree.

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

Roadway Junction / Feature

A significant majority of crashes, 148 out of 228 (64.9%), occurred on non-junction road segments. In contrast, 31 crashes (13.6%) happened at intersections, with four-way intersections being the most common type (12 crashes). Driveway access points were related to 9 crashes, and interchange areas accounted for another 7 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature148 (71.5%)
2
Intersection: Four-way intersection12 (5.8%)
3
Intersection: T-intersection8 (3.9%)
4
Intersection: Intersection with ramp5 (2.4%)
5
Non-intersection: Driveway access (related, not in)5 (2.4%)
6
Intersection: Other intersection (explain in narrative)4 (1.9%)
7
Non-intersection: Driveway access (within)4 (1.9%)
8
Non-intersection: Crossover-related3 (1.4%)
9
Non-intersection: Other non-intersection (explain in narrative)3 (1.4%)

Showing top 9 of 18 reported. 9 additional (15 total) not shown: Interchange-related: On-ramp merge area, Non-intersection: Railroad grade crossing, Interchange-related: Other interchange (explain in narrative), Interchange-related: Off-ramp, Intersection: Y-intersection, Interchange-related: Off-ramp, diverge area, Interchange-related: Mainline, between ramps, Intersection: L-intersection, Non-intersection: Bike lanes.

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

Vehicle Type

Passenger cars were the most prevalent vehicle type involved in crashes, accounting for 136 of the 305 vehicles. Light trucks and pickups were the second most common with 57 vehicles, followed by sport utility vehicles with 50. Commercial vehicles and motorcycles were also present, with 14 tractor-trailers and 12 motorcycles involved in incidents.

Vehicle Type

"Other" combines 6 smaller categories (12 records): Cargo/panel van (3), Single unit truck (2-axle, 6-tire) (3), Single-unit truck (>= 3 axles) (3), Motor home/recreational vehicle (1), Other (explain in narrative) (1), All-terrain vehicle (ATV) (1).

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

Traffic Control Device

For vehicles involved in crashes, the overwhelming majority (245 instances) were in areas with no traffic controls present. Stop signs were the most common form of traffic control noted, being relevant in 26 instances. All other forms of traffic control, such as yield signs and traffic signals, were present in fewer than 5 instances each.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): Warning sign (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 67 instances. Rear impacts were noted in 24 cases, suggesting a share of rear-end collisions. Damage to the driver's side was recorded 20 times, and damage to the passenger's side was recorded 15 times, indicating the presence of angle or sideswipe collisions.

Most Damaged Area

"Other" combines 9 smaller categories (67 records): Driver side - front (14), Rear - driver side corner (12), Passenger side - front (9), Other (explain in narrative) (7), Driver side - rear (7), Passenger side - rear (7), Rear - passenger side corner (7), Non-collision/no damage (3), Undercarriage (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 in 12 crashes, representing 5.3% of all incidents in 2015. Of these, 11 cases involved alcohol, and one case involved drugs. These figures should be considered a minimum, as impairment is often difficult to determine at the scene of a crash.

Crashes by City

Within Mills County, the city of Glenwood experienced the highest volume of crashes, with 38 incidents reported. The towns of Malvern and Pacific Junction recorded the next highest totals, with 9 and 8 crashes, respectively. A number of crashes also occurred in smaller municipalities like Hastings and Emerson, each with 3 reported incidents.

Crashes by City

1
GLENWOOD38 (59.4%)
2
MALVERN9 (14.1%)
3
PACIFIC JUNCTION8 (12.5%)
4
HASTINGS3 (4.7%)
5
EMERSON3 (4.7%)
6
TABOR2 (3.1%)
7
HENDERSON1 (1.6%)

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 (203) occurred on paved roads. However, a notable 24 crashes, representing 10.6% of the total for which this was recorded, took place on unpaved surfaces such as gravel or dirt roads. This highlights the role of the county's secondary road network in traffic incidents.

Paved vs Unpaved Road

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

Roadway Contributing Factor

Roadway factors were identified as contributors in a minority of crashes. The most common factor was the road surface condition, such as being wet or icy, which was cited in 25 incidents. An additional 5 crashes were attributed to a slippery, loose, or worn surface.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)25 (83.3%)
2
Slippery, loose or worn surface5 (16.7%)

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,' specific conditions were noted for some. Driving under the influence of alcohol was the most cited condition, with 12 instances. Driver fatigue or falling asleep was the second most common, recorded in 10 instances.

Driver Condition

1
Under the influence of alcohol12 (44.4%)
2
Asleep/fatigued10 (37%)
3
Medical condition (seizure, reaction)2 (7.4%)
4
Emotional (e.g. depressed, angry)1 (3.7%)
5
Illness/fainted1 (3.7%)
6
Under the influence of drugs/meds1 (3.7%)

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 145 crashes. A substantial number of crashes, 71, resulted in damages between $7,500 and $25,000. Six crashes were estimated to have caused high-value damage exceeding $25,000.

Property Damage

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

Manner of Collision

The predominant crash type was a non-collision event involving a single vehicle, such as a run-off-road or overturn, which accounted for 151 crashes or 66.2% of the total. Among multi-vehicle incidents, rear-end collisions were the most common, with 21 occurrences (9.2%). Broadside collisions were the next most frequent type, with 13 incidents.

Manner of Collision

"Other" combines 3 smaller categories (9 records): Head-on (front to front) (4), Rear to side (3), Rear to rear (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 moving essentially straight, which was the case for 196 of the 305 vehicles involved. Turning left was the next most frequent maneuver, recorded for 20 vehicles prior to a crash. Backing was the third most common action, noted for 13 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight196 (67.8%)
2
Turning left20 (6.9%)
3
Backing13 (4.5%)
4
Turning right12 (4.2%)
5
Legally Parked11 (3.8%)
6
Other (explain in narrative)9 (3.1%)
7
Negotiating a curve7 (2.4%)
8
Slowing/stopping (deceleration)6 (2.1%)
9
Stopped in traffic4 (1.4%)

Showing top 9 of 17 reported. 8 additional (11 total) not shown: Entering traffic lane (merging), Starting in road, Entering a parked position, Changing lanes, Leaving a parked position, Leaving traffic lane, Overtaking/passing, Accelerating in road.

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

Person Type

Of the 421 people involved in crashes, the vast majority were drivers, accounting for 398 individuals (94.5%). The remaining 23 individuals (5.5%) were passengers. No pedestrians or cyclists were recorded as being involved in these incidents.

Person Type

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

Person Injury Severity

Across all 421 people involved in crashes, 115 were either injured or killed. This includes 2 fatalities, 24 serious injuries, 44 minor injuries, and 45 possible injuries. The majority of individuals involved in crashes did not sustain a reported injury.

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 82 vehicle occupants for whom safety equipment use was documented, 10 individuals (12.2%) were recorded as using no restraints. The most common restraint type was a shoulder and lap belt, used by 65 people. Three individuals were in a child safety seat and three 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, accounting for 158 incidents, or 69.3% of all crashes. Two-vehicle collisions were the next most frequent, with 64 occurrences. There were also 5 three-vehicle crashes and one four-vehicle crash reported during the year.

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: 228
  • Total persons involved: 421
  • Total vehicles involved: 305

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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