Yearly Traffic Safety Analysis

172 CRASHES IN
IOWA, IA
2015

In 2015, Louisa County recorded 172 traffic crashes, resulting in 1 fatality and 43 injuries. A significant majority of these incidents, 59.3%, were attributed to collisions with animals, which was the leading contributing factor by a large margin.

172

Total Crash Events

1

Persons Killed

43

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

In 2015, all recorded fatalities and injuries in Louisa County involved motorists. One motorist was killed and 43 were injured in traffic crashes. There were no reported fatalities or injuries involving pedestrians or cyclists during this period.

1

Motorists Killed

43

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 Louisa County peaked on Thursdays, with 31 incidents reported. The most frequent time for crashes was the 6 a.m. hour, which saw 19 events. Significant crash activity also occurred during the evening hours between 5 p.m. and 9 p.m.

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 172 crashes, a large majority (77.9%) resulted in no injuries. Injury-related crashes accounted for approximately 22.1% of the total, including 7 serious injury and 14 minor injury incidents. One fatal crash occurred, resulting in one fatality.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury7serious injury crashes4.1%
Minor Injury14minor injury crashes8.1%
Possible Injury16possible injury crashes9.3%
No Injury134no injury crashes77.9%

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The primary contributing factor to crashes was encounters with animals, cited in 102 incidents, accounting for 59.3% of all crashes. Far less frequent factors included losing control of the vehicle, which was noted in 15 crashes (8.7%), and driving too fast for conditions, which was a factor in 7 crashes (4.1%).

Officer-Reported Primary Contributing Cause

Animal102 (59.3%)
Lost Control15 (8.7%)
Driving too fast for conditions7 (4.1%)
Ran off road - straight7 (4.1%)
FTYROW: From stop sign5 (2.9%)
Driver Distraction: Other interior distraction3 (1.7%)
Ran off road - left3 (1.7%)
Other (explain in narrative): Other2 (1.2%)
Passing: Other passing (explain in narrative)2 (1.2%)
FTYROW: Making left turn2 (1.2%)

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 majority of crashes occurred in favorable conditions, with 59% of incidents with available data happening in clear weather and 74% on dry road surfaces. Daylight conditions were present for 58% of the crashes. Crashes in darkness on unlighted roadways accounted for 28 incidents.

Weather

Clear52 (59.1%)
Cloudy25 (28.4%)
Snow5 (5.7%)
Freezing rain/drizzle2 (2.3%)
Rain2 (2.3%)
Blowing sand, soil, dirt1 (1.1%)
Fog, smoke, smog1 (1.1%)

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

Lighting

Daylight54 (58.1%)
Dark - roadway not lighted28 (30.1%)
Dawn6 (6.5%)
Dusk3 (3.2%)
Dark - roadway lighted2 (2.2%)

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

Road Surface

Dry69 (74.2%)
Wet8 (8.6%)
Gravel6 (6.5%)
Ice/frost5 (5.4%)
Snow4 (4.3%)
Slush1 (1.1%)

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

Vehicles & Demographics

The age group most frequently involved in crashes was 26-34 years old, with 46 individuals recorded, followed by the 16-20 age group with 40 individuals. The most common vehicle makes involved were Ford (31 vehicles) and Chevrolet (37 vehicles, combining 'CHEVROLET' and 'CHEV'), followed by Dodge (26 vehicles, combining 'DODGE' and 'DODG').

Top Vehicle Makes (201 vehicles)

1
FORD31 (15.4%)
2
CHEVROLET23 (11.4%)
3
DODGE14 (7%)
4
CHEV14 (7%)
5
DODG12 (6%)
6
CHRYSLER11 (5.5%)
7
TOYOTA8 (4%)
8
PONTIAC7 (3.5%)
9
PONT7 (3.5%)
10
NISSAN5 (2.5%)

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

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

Sex Distribution (188 persons with recorded sex)

Male97 (51.6%)
Female91 (48.4%)

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

Major Cause

The predominant major cause of crashes was an animal in the roadway, accounting for 102 incidents. Other significant causes included losing control of the vehicle, which was cited in 15 crashes, and driving too fast for conditions, which contributed to 7 crashes. Running off a straight road was also listed as the cause for 7 incidents.

Major Cause

1
Animal102 (60.7%)
2
Lost Control15 (8.9%)
3
Driving too fast for conditions7 (4.2%)
4
Ran off road - straight7 (4.2%)
5
FTYROW: From stop sign5 (3%)
6
Driver Distraction: Other interior distraction3 (1.8%)
7
Ran off road - left3 (1.8%)
8
Other (explain in narrative): Other2 (1.2%)
9
Passing: Other passing (explain in narrative)2 (1.2%)

Showing top 9 of 24 reported. 15 additional (22 total) not shown: FTYROW: Making left turn, Driver Distraction: Reaching for object(s)/fallen object(s), Ran off road - right, Exceeded authorized speed, Swerving/Evasive Action, Made improper turn, Driver Distraction: Exterior distraction, Driver Distraction: Talking on a hand-held device, Followed too close, FTYROW: From driveway, Driver Distraction: Adjusting devices (radio, climate), Operating vehicle in an reckless, erratic, careless, negligent manner, Passing: Where prohibited by signs/markings, Crossed centerline (undivided), Driver Distraction: Inattentive/lost in thought.

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 occurred in 102 crashes. Collisions with another vehicle in traffic were the second most frequent event, with 24 occurrences. Crashes involving a fixed object, such as a ditch, accounted for 20 incidents, while overturns or rollovers were the first harmful event in 11 cases.

First Harmful Event

1
Collision with: Animal102 (59.6%)
2
Collision with: Vehicle in traffic24 (14%)
3
Collision with fixed object: Ditch20 (11.7%)
4
Non-collision events: Overturn/rollover11 (6.4%)
5
Non-collision events: Other non-collision (explain in narrative)3 (1.8%)
6
Other (explain in narrative)2 (1.2%)
7
Collision with fixed object: Tree1 (0.6%)
8
Collision with: Parked motor vehicle1 (0.6%)
9
Miscellaneous events: Hit and run1 (0.6%)

Showing top 9 of 15 reported. 6 additional (6 total) not shown: Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Embankment, Collision with fixed object: Fence, Collision with fixed object: Ground, Collision with fixed object: Guardrail - end, Collision with fixed object: Mailbox.

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

Roadway Junction / Feature

The majority of crashes, 75 out of 95 with available data, occurred at non-intersection locations. This includes 68 crashes on straight or curved road segments without a special feature. Intersections accounted for 20 crashes, with T-intersections being the most common type, site of 10 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature68 (71.6%)
2
Intersection: T-intersection10 (10.5%)
3
Intersection: Four-way intersection8 (8.4%)
4
Non-intersection: Driveway access (within)4 (4.2%)
5
Non-intersection: Driveway access (related, not in)3 (3.2%)
6
Intersection: Other intersection (explain in narrative)1 (1.1%)
7
Intersection: L-intersection1 (1.1%)

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 90 recorded. Sport utility vehicles (39) and light trucks or pickups (35) were also frequently involved. Tractor/semi-trailers were involved in 11 crashes, while one motorcycle was recorded.

Vehicle Type

"Other" combines 3 smaller categories (3 records): Farm equipment (explain in narrative) (1), All-terrain vehicle (ATV) (1), Motorcycle (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 crashes, 96 out of 122 with this data, occurred where no traffic controls were present. Stop signs were the most common form of traffic control at crash locations, present in 12 incidents. Ten crashes occurred in marked no-passing zones.

Traffic Control Device

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

Most Damaged Area

The most frequently damaged area on vehicles was the front, which was the primary point of impact in 30 cases. Combined with front-corner impacts, frontal damage was noted in 62 vehicles. Damage to the top of the vehicle, often associated with rollovers, was the second most common category, recorded for 20 vehicles.

Most Damaged Area

"Other" combines 7 smaller categories (22 records): Driver side - middle (5), Driver side - front (4), Passenger side - middle (4), Rear - driver side corner (3), Undercarriage (3), Rear (2), Passenger side - rear (1).

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

Crashes by City

Within Louisa County, crash distribution was highest in Columbus Junction, which recorded 9 incidents. Wapello had the second-highest volume with 3 crashes. A number of crashes occurred outside of any specific city limits and are not included in this breakdown.

Crashes by City

1
COLUMBUS JUNCTION9 (64.3%)
2
WAPELLO3 (21.4%)
3
COLUMBUS CITY1 (7.1%)
4
OAKVILLE1 (7.1%)

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

Paved vs Unpaved Road

Crashes predominantly occurred on paved roads, which accounted for 150 incidents. Unpaved surfaces, such as gravel or dirt roads, were the site of 19 crashes, making up 11.2% of the total where surface type 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 a minority of crashes, a roadway factor was identified as a contributor. The most common factor was the surface condition, such as wet or icy roads, cited in 9 incidents. One crash was noted as occurring in a work zone.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)9 (81.8%)
2
Slippery, loose or worn surface1 (9.1%)
3
Work Zone (roadway-related)1 (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 for the vast majority of crashes (149 incidents) fell within the $1,500 to $7,500 range. Twenty crashes resulted in damages estimated between $7,500 and $25,000. Three crashes were categorized as having high damage costs, 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 most common type of crash was a non-collision event involving a single vehicle, such as running off the road or an overturn, which accounted for 118 incidents or 68.6% of all crashes. Among multi-vehicle crashes, the most frequent manners were same-direction sideswipes (9 crashes) and broadside collisions (7 crashes).

Manner of Collision

"Other" combines 1 smaller categories (1 records): Head-on (front to front) (1).

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

Pre-Crash Driver Action

Prior to the crash, the most common driver action was moving essentially straight, which was the case in 108 incidents. Turning left was the pre-crash action in 13 cases, and negotiating a curve was the action in 9 cases. These actions represent the driver's intended maneuver immediately before the incident.

Pre-Crash Driver Action

1
Movement essentially straight108 (71.1%)
2
Turning left13 (8.6%)
3
Negotiating a curve9 (5.9%)
4
Overtaking/passing5 (3.3%)
5
Slowing/stopping (deceleration)4 (2.6%)
6
Turning right4 (2.6%)
7
Backing3 (2%)
8
Stopped in traffic2 (1.3%)
9
Other (explain in narrative)1 (0.7%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Legally Parked, Making U-turn, Accelerating in road.

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

Person Type

Of the 246 individuals involved in crashes, the vast majority (242 people, or 98.4%) were drivers. Passengers accounted for the remaining 4 individuals. No pedestrians or other non-occupant types were recorded 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 246 people involved in crashes, there was 1 fatality and 43 injuries. The injuries consisted of 8 serious injuries, 16 minor injuries, and 19 possible injuries. The remaining individuals were not reported as injured.

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 37 individuals for whom safety equipment use was specified, 32 were using a shoulder and lap belt. Four individuals were recorded as not using any safety equipment. One child was secured in a forward-facing child safety seat.

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

The majority of crashes were single-vehicle incidents, which accounted for 143 of the 172 total crashes, or 83.1%. The remaining 29 crashes involved two vehicles. No crashes involving three or more vehicles were 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: 172
  • Total persons involved: 246
  • Total vehicles involved: 201

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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