Yearly Traffic Safety Analysis

274 CRASHES IN
IOWA, IA
2015

In 2015, Tama County recorded 274 total vehicle crashes, which resulted in 4 fatalities and 105 injuries. A highly notable finding from the data is the primary contributing factor to these incidents; collisions involving animals were cited in 111 crashes, accounting for over 40% of the total.

274

Total Crash Events

4

Persons Killed

105

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (4) 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 4 fatalities and 105 injuries recorded in Tama County in 2015 involved motorists. There were no pedestrian or cyclist fatalities or injuries reported during this period. The 105 motorist injuries consisted of 20 serious injuries, 52 minor injuries, and 33 possible injuries.

4

Motorists Killed

105

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 Tama County were most frequent on Fridays, with 46 incidents recorded. The single most common time for a crash was the 7 p.m. hour, which saw 24 incidents. Analysis of crashes with known lighting conditions shows 110 occurred in daylight, while 51 occurred in darkness, including 39 on unlighted roadways and 12 on lighted ones.

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 274 crashes, the majority (75.2%, or 206 incidents) resulted in no injuries. The remaining 66 crashes involved injuries of varying severity, including 13 with serious injuries, 30 with minor injuries, and 23 with possible injuries. Two of these crashes were fatal, leading to a total of 4 fatalities, underscoring that a single crash can result in multiple deaths.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
Serious Injury13serious injury crashes4.7%
Minor Injury30minor injury crashes10.9%
Possible Injury23possible injury crashes8.4%
No Injury206no injury crashes75.2%

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 significant contributing factor identified in Tama County crashes was interaction with an animal, cited in 111 incidents, or 40.5% of the total. Other leading factors included drivers losing control (23 crashes, 8.4%), running off a straight road (19 crashes, 6.9%), and driving too fast for conditions (16 crashes, 5.8%).

Officer-Reported Primary Contributing Cause

Animal111 (40.5%)
Lost Control23 (8.4%)
Ran off road - straight19 (6.9%)
Driving too fast for conditions16 (5.8%)
FTYROW: From stop sign11 (4%)
Ran off road - left8 (2.9%)
Followed too close7 (2.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner7 (2.6%)
Swerving/Evasive Action7 (2.6%)
Exceeded authorized speed4 (1.5%)

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

Road & Environmental Conditions

A substantial number of crashes occurred in seemingly ideal conditions, with 109 incidents in clear weather and 114 on dry road surfaces. Crashes also occurred during adverse conditions, including 12 in snow and 11 in rain. Regarding road surface, 16 crashes happened on wet roads and another 16 on snow-covered roads.

Weather

Clear109 (63.4%)
Cloudy29 (16.9%)
Snow12 (7.0%)
Rain11 (6.4%)
Fog, smoke, smog7 (4.1%)
Freezing rain/drizzle4 (2.3%)

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

Lighting

Daylight110 (64.0%)
Dark - roadway not lighted39 (22.7%)
Dark - roadway lighted12 (7.0%)
Dawn5 (2.9%)
Dusk4 (2.3%)
Dark - unknown roadway lighting2 (1.2%)

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

Road Surface

Dry114 (65.9%)
Wet16 (9.2%)
Snow16 (9.2%)
Gravel15 (8.7%)
Ice/frost10 (5.8%)
Sand1 (0.6%)
Slush1 (0.6%)

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

Vehicles & Demographics

The age groups most frequently involved in crashes were 16-20 year-olds and 45-54 year-olds, with 70 individuals from each group recorded. An analysis of the 370 vehicles involved shows that Ford was the most common make, accounting for 77 vehicles. Chevrolet and its abbreviation 'CHEV' collectively appeared 86 times (50 and 36, respectively), followed by Dodge with 20 vehicles.

Top Vehicle Makes (370 vehicles)

1
FORD77 (20.8%)
2
CHEVROLET50 (13.5%)
3
CHEV36 (9.7%)
4
DODGE20 (5.4%)
5
TOYOTA12 (3.2%)
6
DODG11 (3%)
7
PONT10 (2.7%)
8
JEEP10 (2.7%)
9
KIA9 (2.4%)
10
NISSAN7 (1.9%)

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

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

Sex Distribution (344 persons with recorded sex)

Male210 (61.0%)
Female134 (39.0%)

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 animals were the leading major cause of crashes, accounting for 111 incidents. Following this, losing control was cited as the cause in 23 crashes (8.4%), and running off a straight portion of the road was the cause for another 19 crashes (6.9%). Driving too fast for conditions contributed to 16 crashes (5.8%).

Major Cause

1
Animal111 (41.6%)
2
Lost Control23 (8.6%)
3
Ran off road - straight19 (7.1%)
4
Driving too fast for conditions16 (6%)
5
FTYROW: From stop sign11 (4.1%)
6
Ran off road - left8 (3%)
7
Followed too close7 (2.6%)
8
Operating vehicle in an reckless, erratic, careless, negligent manner7 (2.6%)
9
Swerving/Evasive Action7 (2.6%)

Showing top 9 of 37 reported. 28 additional (58 total) not shown: Exceeded authorized speed, FTYROW: Making left turn, Other (explain in narrative): Other, Driver Distraction: Exterior distraction, Ran Stop Sign, FTYROW: From yield sign, FTYROW: Other (explain in narrative), Passing: Other passing (explain in narrative), Driver Distraction: Reaching for object(s)/fallen object(s), Ran off road - right, Driver Distraction: Other interior distraction, Other (explain in narrative): No improper action, Driver Distraction: Passenger, FTYROW: From driveway, Improper Backing, Driver Distraction: Inattentive/lost in thought, Made improper turn, FTYROW: From parked position, Ran Traffic Signal, Traveling wrong way or on wrong side of road, Other (explain in narrative): Vision obstructed, Passing: On wrong side, Passing: Where prohibited by signs/markings, Passing: With insufficient distance/inadequate visibility, Downhill runaway, Failed to yield to emergency vehicle, Crossed centerline (undivided), Driver Distraction: Other electronic device activity.

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, which initiated 111 crashes. The second most frequent event was a collision with another vehicle in traffic, occurring 72 times. Non-collision events, primarily rollovers (26 incidents), and collisions with a fixed object, most often a ditch (25 incidents), were also significant first harmful events.

First Harmful Event

1
Collision with: Animal111 (42%)
2
Collision with: Vehicle in traffic72 (27.3%)
3
Non-collision events: Overturn/rollover26 (9.8%)
4
Collision with fixed object: Ditch25 (9.5%)
5
Collision with: Parked motor vehicle6 (2.3%)
6
Collision with fixed object: Utility pole/light support5 (1.9%)
7
Collision with fixed object: Traffic sign support3 (1.1%)
8
Collision with fixed object: Building2 (0.8%)
9
Collision with: Re-entering roadway2 (0.8%)

Showing top 9 of 19 reported. 10 additional (12 total) not shown: Collision with fixed object: Snow bank, Collision with fixed object: Embankment, Collision with: Thrown or falling object, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Other fixed object (explain in narrative), Other (explain in narrative), Collision with fixed object: Landscape/shrubbery, Collision with fixed object: Fence, Collision with: Struck/struck by object/cargo/person from other vehicle.

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

Roadway Junction / Feature

Crashes were more likely to occur on non-junction segments of the roadway than at intersections. Ninety-five crashes happened on straight or curved road segments with no junction feature. In contrast, 58 crashes occurred at various types of intersections, with four-way intersections being the most common type, accounting for 30 of these incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature95 (54.6%)
2
Intersection: Four-way intersection30 (17.2%)
3
Intersection: T-intersection17 (9.8%)
4
Non-intersection: Driveway access (related, not in)9 (5.2%)
5
Intersection: Other intersection (explain in narrative)6 (3.4%)
6
Intersection: Y-intersection4 (2.3%)
7
Non-intersection: Driveway access (within)3 (1.7%)
8
Non-intersection: Alley2 (1.1%)
9
Interchange-related: On-ramp merge area2 (1.1%)

Showing top 9 of 14 reported. 5 additional (6 total) not shown: Non-intersection: Crossover-related, Interchange-related: Off-ramp, Non-intersection: Other non-intersection (explain in narrative), Non-intersection: Railroad grade crossing, Intersection: Intersection with ramp.

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 186 units recorded. Sport utility vehicles (66) and light trucks or pickups (64) were the next most frequent. The data also includes 17 tractor/semi-trailers and 5 motorcycles among the 370 vehicles involved in collisions.

Vehicle Type

"Other" combines 8 smaller categories (12 records): Single unit truck (2-axle, 6-tire) (4), Farm tractor (2), Cargo/panel van (1), Farm equipment (explain in narrative) (1), Other light truck (<=10000 lbs) (1), Train (1), Truck/trailer (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

The majority of crashes, 196 incidents, occurred in areas with no traffic controls present. For crashes at locations with traffic controls, stop signs were the most common device, associated with 40 crashes. A smaller number of incidents were recorded at locations with no passing zones (8) and yield signs (6).

Traffic Control Device

"Other" combines 3 smaller categories (5 records): Flashing traffic control signal (2), Other (explain in narrative) (2), Railway crossing device (1).

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 damage, with 81 vehicles sustaining damage to the front and an additional 45 vehicles damaged on the front corners. Rear impacts were noted on 23 vehicles, suggesting a share of rear-end collisions. Notably, 22 vehicles sustained damage to the top, which is often indicative of a rollover event.

Most Damaged Area

"Other" combines 9 smaller categories (65 records): Driver side - front (13), Passenger side - front (11), Passenger side - rear (11), Rear - driver side corner (9), Driver side - rear (8), Other (explain in narrative) (8), Rear - passenger side corner (2), Non-collision/no damage (2), Undercarriage (1).

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

Impairment (Alcohol / Drugs)

A total of 11 crashes were recorded as involving an impaired driver, representing 4.0% of all crashes. Of these, alcohol was the sole factor in 9 incidents, drugs were the sole factor in one incident, and a combination of alcohol and drugs was noted in one crash.

Crashes by City

The highest concentration of crashes within municipal limits occurred in the city of Tama, which recorded 25 incidents. The city of Toledo had the second-highest volume with 16 crashes, followed by Traer with 15 crashes. Several other towns, including Chelsea, Gladbrook, and Dysart, each recorded 3 crashes.

Crashes by City

1
TAMA25 (34.7%)
2
TOLEDO16 (22.2%)
3
TRAER15 (20.8%)
4
CHELSEA3 (4.2%)
5
GLADBROOK3 (4.2%)
6
DYSART3 (4.2%)
7
GARWIN2 (2.8%)
8
ELBERON2 (2.8%)
9
WALCOTT1 (1.4%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: LINCOLN, MONTOUR.

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, 240 out of 274, took place on paved roads. However, a notable portion, 34 crashes or 12.4% of the total, occurred on unpaved surfaces such as gravel or dirt roads.

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 where a roadway factor was cited, adverse surface conditions were the leading contributor, noted in 27 incidents. A slippery, loose, or worn surface was a factor in 2 crashes, and one crash was related to a work zone. For most crashes, no specific roadway factor was identified.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)27 (90%)
2
Slippery, loose or worn surface2 (6.7%)
3
Work Zone (roadway-related)1 (3.3%)

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

Driver Condition

Among drivers for whom a condition other than 'apparently normal' was recorded, influence of alcohol was the most frequent, cited for 12 drivers. The next most common condition was being asleep or fatigued, which was noted for 6 drivers. Other recorded conditions included illness or medical events, affecting 4 drivers.

Driver Condition

1
Under the influence of alcohol12 (50%)
2
Asleep/fatigued6 (25%)
3
Illness/fainted2 (8.3%)
4
Medical condition (seizure, reaction)2 (8.3%)
5
Emotional (e.g. depressed, angry)1 (4.2%)
6
Physical impairment1 (4.2%)

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

Property Damage

The most common estimated property damage cost was in the $1,500 to $7,500 range, which applied to 191 crashes. Seventy crashes resulted in damages between $7,500 and $25,000. A smaller number of 10 crashes involved extensive property 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, non-collision events were the dominant manner of collision, accounting for 141 crashes, or 51.5% of the total. For multi-vehicle incidents, broadside collisions were the most frequent type with 27 crashes (9.9%), followed by rear-end collisions, which occurred 21 times (7.7%).

Manner of Collision

"Other" combines 3 smaller categories (8 records): Head-on (front to front) (4), Other (explain in narrative) (3), Rear to rear (1).

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

Pre-Crash Driver Action

The most common action of vehicles immediately before a crash was moving essentially straight, which was the case for 194 vehicles. Turning left was the pre-crash action for 31 vehicles, and turning right was the action for 14 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight194 (65.5%)
2
Turning left31 (10.5%)
3
Turning right14 (4.7%)
4
Negotiating a curve10 (3.4%)
5
Backing8 (2.7%)
6
Legally Parked8 (2.7%)
7
Other (explain in narrative)8 (2.7%)
8
Overtaking/passing7 (2.4%)
9
Stopped in traffic5 (1.7%)

Showing top 9 of 15 reported. 6 additional (11 total) not shown: Illegally Parked/Unattended, Making U-turn, Slowing/stopping (deceleration), Starting in road, Entering a parked position, Entering traffic lane (merging).

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

Person Type

Of the 483 people involved in crashes, the vast majority were drivers, accounting for 449 individuals. The remaining 34 people were passengers. No other person types, such as pedestrians or cyclists, were recorded in the crash data for this period.

Person Type

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

Person Injury Severity

A total of 109 individuals sustained some level of injury or were killed in crashes. This includes 4 fatalities, 20 serious injuries, 52 minor injuries, and 33 possible injuries. The data indicates that 4 people involved in crashes had no apparent 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 individuals where safety equipment use was documented, 75 were reported as using a shoulder and lap belt. However, 14 individuals were recorded as using no safety equipment at all. Additionally, 5 children were secured in child safety seats and 3 people 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, with 185 incidents, representing 67.5% of all crashes. Two-vehicle collisions accounted for 82 crashes, while a smaller number of multi-vehicle pile-ups involved three vehicles in 7 separate incidents.

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: 274
  • Total persons involved: 483
  • Total vehicles involved: 370

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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