Yearly Traffic Safety Analysis

370 CRASHES IN
IOWA, IA
2015

In 2015, Buena Vista County recorded 370 traffic crashes, resulting in 3 fatalities and 124 injuries. A notable finding from the data is that collisions involving an animal were the single most common contributing factor, cited in 60 crashes, or 16.2% of the total.

370

Total Crash Events

3

Persons Killed

124

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (3) 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

Motorists comprised all 3 traffic fatalities and the vast majority of those injured, with 119 motorist injuries recorded. There were no fatalities among pedestrians or bicyclists. Two pedestrians and three bicyclists sustained non-fatal injuries in crashes during this period.

0

Pedestrians Killed

0

Cyclists Killed

3

Motorists Killed

2

Pedestrians Injured

3

Cyclists Injured

119

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 Buena Vista County occurred most frequently on Fridays, with 75 incidents, and during the 5 p.m. hour, which saw 33 crashes. The majority of collisions, 235 incidents or 63.5% of the total, happened during daylight hours. Crashes in dark conditions, including both unlit and lit roadways, accounted for 81 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 vast majority of crashes, 275 out of 370 (74.3%), resulted in no injuries. There were 95 crashes that involved some level of injury, including 2 fatal crashes. These 2 incidents resulted in a total of 3 persons killed.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
Serious Injury1serious injury crashes0.3%
Minor Injury30minor injury crashes8.1%
Possible Injury62possible injury crashes16.8%
No Injury275no injury crashes74.3%

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 leading contributing factor identified in crashes was an animal, which was cited in 60 incidents (16.2%). Other primary factors included a driver losing control (30 crashes, 8.1%), driving too fast for conditions (24 crashes, 6.5%), and failure to yield the right-of-way from a stop sign (20 crashes, 5.4%).

Officer-Reported Primary Contributing Cause

Animal60 (16.2%)
Other (explain in narrative): Other51 (13.8%)
Lost Control30 (8.1%)
Driving too fast for conditions24 (6.5%)
FTYROW: From stop sign20 (5.4%)
Followed too close16 (4.3%)
FTYROW: Making left turn13 (3.5%)
Ran off road - straight13 (3.5%)
Ran off road - left9 (2.4%)
Ran Stop Sign9 (2.4%)

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

Road & Environmental Conditions

Most crashes occurred in favorable conditions, with 60.3% (223 crashes) happening in clear weather and 56.5% (209 crashes) on dry road surfaces. Overall, 235 crashes, or 63.5% of the total, took place in daylight. Crashes during snowfall were reported in 27 instances, while 38 crashes occurred on snow-covered roads.

Weather

Clear223 (67.2%)
Cloudy43 (13.0%)
Rain29 (8.7%)
Snow27 (8.1%)
Freezing rain/drizzle5 (1.5%)
Severe Winds2 (0.6%)
Blowing Snow2 (0.6%)
Fog, smoke, smog1 (0.3%)

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

Lighting

Daylight235 (70.1%)
Dark - roadway not lighted55 (16.4%)
Dark - roadway lighted24 (7.2%)
Dawn11 (3.3%)
Dusk8 (2.4%)
Dark - unknown roadway lighting2 (0.6%)

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

Road Surface

Dry209 (62.2%)
Wet42 (12.5%)
Snow38 (11.3%)
Ice/frost29 (8.6%)
Gravel14 (4.2%)
Slush4 (1.2%)

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

Vehicles & Demographics

Among the 718 people involved in crashes, the 26-34 age group was the most represented demographic, with 114 individuals. An analysis of the 588 vehicles involved shows that the most frequent makes were Chevrolet (127 vehicles, combining 'CHEV' and 'CHEVROLET' entries), Ford (86 vehicles), and Dodge (49 vehicles, combining 'DODG' and 'DODGE').

Top Vehicle Makes (588 vehicles)

1
FORD86 (14.6%)
2
CHEV82 (13.9%)
3
CHEVROLET45 (7.7%)
4
DODG29 (4.9%)
5
HOND24 (4.1%)
6
GMC24 (4.1%)
7
DODGE20 (3.4%)
8
PONT19 (3.2%)
9
BUIC19 (3.2%)
10
CHRY17 (2.9%)

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

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

Sex Distribution (529 persons with recorded sex)

Male324 (61.2%)
Female205 (38.8%)

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, accounting for 60 incidents (16.2%). Other leading causes included a driver losing control (30 crashes, 8.1%), driving too fast for conditions (24 crashes, 6.5%), and failure to yield the right-of-way from a stop sign (20 crashes, 5.4%).

Major Cause

1
Animal60 (17%)
2
Other (explain in narrative): Other51 (14.5%)
3
Lost Control30 (8.5%)
4
Driving too fast for conditions24 (6.8%)
5
FTYROW: From stop sign20 (5.7%)
6
Followed too close16 (4.5%)
7
FTYROW: Making left turn13 (3.7%)
8
Ran off road - straight13 (3.7%)
9
Ran off road - left9 (2.6%)

Showing top 9 of 46 reported. 37 additional (116 total) not shown: Ran Stop Sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Made improper turn, FTYROW: Other (explain in narrative), Driver Distraction: Other interior distraction, Improper Backing, Other (explain in narrative): No improper action, FTYROW: At uncontrolled intersection, FTYROW: From parked position, FTYROW: From driveway, Driver Distraction: Exterior distraction, Driver Distraction: Adjusting devices (radio, climate), Ran Traffic Signal, Passing: Other passing (explain in narrative), Driver Distraction: Inattentive/lost in thought, Failure to signal intentions, FTYROW: Making right turn on red signal, FTYROW: To pedestrian, Improper or erratic lane changing, Driver Distraction: Talking on a hand-held device, Driver Distraction: Passenger, Operator inexperience, Driver Distraction: Manual operation of an electronic communication device, Other (explain in narrative): Vision obstructed, Failed to keep in proper lane, Passing: On wrong side, Driver Distraction: Reaching for object(s)/fallen object(s), Passing: Where prohibited by signs/markings, Passing: With insufficient distance/inadequate visibility, Crossed centerline (undivided), Ran off road - right, Aggressive driving/road rage, Exceeded authorized speed, FTYROW: From yield sign, Separation of units, Other (explain in narrative): Improper operation, Swerving/Evasive Action.

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

First Harmful Event

A collision with another vehicle in traffic was the most common first harmful event, occurring in 184 crashes, which is 49.7% of all incidents. The second most frequent event was a collision with an animal, noted in 60 crashes (16.2%). Running off the road into a ditch was the first harmful event in 33 crashes (8.9%).

First Harmful Event

1
Collision with: Vehicle in traffic184 (49.9%)
2
Collision with: Animal60 (16.3%)
3
Collision with fixed object: Ditch33 (8.9%)
4
Non-collision events: Overturn/rollover22 (6%)
5
Collision with: Parked motor vehicle13 (3.5%)
6
Collision with fixed object: Utility pole/light support8 (2.2%)
7
Collision with fixed object: Traffic signal support5 (1.4%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)5 (1.4%)
9
Miscellaneous events: Hit and run5 (1.4%)

Showing top 9 of 28 reported. 19 additional (34 total) not shown: Collision with fixed object: Traffic sign support, Collision with fixed object: Building, Other (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Other fixed object (explain in narrative), Collision with fixed object: Ground, Collision with fixed object: Curb/island/raised median, Collision with: Re-entering roadway, Collision with fixed object: Fire hydrant, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Bridge overhead structure, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Other traffic barrier (explain in narrative), Collision with fixed object: Snow bank, Collision with fixed object: Embankment, Collision with fixed object: Tree, Collision with fixed object: Landscape/shrubbery, Collision with: Other non-fixed object (explain in narrative), Collision with fixed object: Culvert/pipe opening.

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

Roadway Junction / Feature

The majority of crashes, 215 out of 370 (58.1%), occurred at non-intersection locations. Crashes at intersections accounted for 26.8% of the total, with 76 at four-way intersections and 21 at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature215 (63.6%)
2
Intersection: Four-way intersection76 (22.5%)
3
Intersection: T-intersection21 (6.2%)
4
Non-intersection: Driveway access (related, not in)18 (5.3%)
5
Non-intersection: Other non-intersection (explain in narrative)3 (0.9%)
6
Non-intersection: Driveway access (within)2 (0.6%)
7
Intersection: Y-intersection1 (0.3%)
8
Non-intersection: Alley1 (0.3%)
9
Intersection: Other intersection (explain in narrative)1 (0.3%)

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, accounting for 240 of the 588 vehicles in crashes. Sport utility vehicles (142 vehicles) and four-tire light trucks or pickups (105 vehicles) were also frequently involved. These three categories together represented 82.8% of all vehicles in collisions.

Vehicle Type

"Other" combines 9 smaller categories (21 records): Farm tractor (5), Single-unit truck (>= 3 axles) (3), Cargo/panel van (3), Other (explain in narrative) (3), School bus (seats > 15) (3), Maintenance/construction vehicle (1), Passenger van (seats 9-15) (1), Truck tractor (bobtail) (1), Other light truck (<=10000 lbs) (1).

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

Traffic Control Device

The data indicates that for a majority of vehicles involved in crashes, no traffic controls were present, with this being the case for 379 vehicles. Where controls were present, stop signs were the most common, associated with 73 vehicles, followed by traffic signals for 71 vehicles.

Traffic Control Device

"Other" combines 3 smaller categories (5 records): Warning sign (2), Traffic director (person) (2), Yield signs (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 vehicle damage, recorded as the primary impact point for 143 vehicles. When including front-corner impacts, a total of 242 vehicles sustained front-end damage. Rear-end damage was recorded for 50 vehicles, while side impacts were the most damaged area for 86 vehicles.

Most Damaged Area

"Other" combines 10 smaller categories (138 records): Driver side - front (27), Driver side - rear (27), Passenger side - front (23), Top (19), Passenger side - rear (16), Rear - passenger side corner (14), Other (explain in narrative) (5), Cargo loss (3), 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)

Ten crashes, or 2.7% of the total, were recorded as involving an impaired driver. Of these incidents, nine were attributed to alcohol and one was attributed to drugs.

Crashes by City

Storm Lake accounted for the largest number of crashes among municipalities with 195 incidents. Considerably fewer crashes were recorded in Alta (12) and Sioux Rapids (11). A substantial number of incidents, 133 crashes, occurred in areas outside of any incorporated city limits.

Crashes by City

1
STORM LAKE195 (82.3%)
2
ALTA12 (5.1%)
3
SIOUX RAPIDS11 (4.6%)
4
NEWELL6 (2.5%)
5
ALBERT CITY5 (2.1%)
6
LAKESIDE4 (1.7%)
7
MARATHON2 (0.8%)
8
LINN GROVE2 (0.8%)

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 (346) occurred on paved roadways. Crashes on unpaved surfaces, such as gravel or dirt roads, accounted for 22 incidents, representing 6.0% of the crashes where road surface type was documented.

Paved vs Unpaved Road

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

Roadway Contributing Factor

Among roadway-related contributing factors, adverse surface conditions such as wet or icy roads were the most frequently cited, contributing to 52 crashes. Work zones were noted as a factor in 2 incidents, and a slippery or worn surface was cited once.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)52 (89.7%)
2
Work Zone (roadway-related)2 (3.4%)
3
Non-highway work1 (1.7%)
4
Shoulders (none, low, soft, high)1 (1.7%)
5
Slippery, loose or worn surface1 (1.7%)
6
Traffic backup, prior crash1 (1.7%)

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

Driver Condition

In cases where a driver's condition was noted as something other than 'apparently normal,' being under the influence of alcohol was the most common, recorded for 8 drivers. An emotional state (e.g., depressed, angry) and a medical condition were each cited for 5 drivers, while fatigue or falling asleep was noted for 3 drivers.

Driver Condition

1
Under the influence of alcohol8 (36.4%)
2
Emotional (e.g. depressed, angry)5 (22.7%)
3
Medical condition (seizure, reaction)5 (22.7%)
4
Asleep/fatigued3 (13.6%)
5
Paraplegic/wheelchair restricted1 (4.5%)

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

Property Damage

The most common range for officer-estimated property damage was between $1,500 and $7,500, a category that included 280 crashes. Eight crashes were estimated to have caused property damage in excess of $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, such as rollovers or running off the road, were the most common crash type, accounting for 147 incidents (39.7%). The next most frequent types were broadside collisions (66 crashes, 17.8%) and rear-end collisions (61 crashes, 16.5%).

Manner of Collision

"Other" combines 3 smaller categories (13 records): Head-on (front to front) (8), Other (explain in narrative) (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

Among the 588 vehicles involved in crashes, the most common pre-crash action was moving straight ahead, which was reported for 347 vehicles. The next most frequent actions were turning left (58 vehicles) and backing (31 vehicles).

Pre-Crash Driver Action

1
Movement essentially straight347 (62.3%)
2
Turning left58 (10.4%)
3
Backing31 (5.6%)
4
Legally Parked29 (5.2%)
5
Turning right25 (4.5%)
6
Stopped in traffic20 (3.6%)
7
Slowing/stopping (deceleration)19 (3.4%)
8
Other (explain in narrative)6 (1.1%)
9
Overtaking/passing6 (1.1%)

Showing top 9 of 16 reported. 7 additional (16 total) not shown: Illegally Parked/Unattended, Leaving a parked position, Changing lanes, Entering traffic lane (merging), Negotiating a curve, Leaving traffic lane, Accelerating in road.

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

Person Type

Drivers constituted the overwhelming majority of individuals involved in crashes, accounting for 686 of the 718 people (95.5%). Passengers made up 3.8% of the total with 27 individuals. Pedestrians and bicyclists together represented less than 1% of all persons involved.

Person Type

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

Person Injury Severity

Out of 718 people involved in crashes, a total of 127 sustained some level of injury or were killed. This figure includes 3 fatalities, 1 serious injury, 39 minor injuries, and 84 possible injuries.

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 95 occupants, 91 (95.8%) were reported to have used a shoulder and lap belt. Only two occupants in this subset were recorded as not using any safety restraints.

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 201 of the 370 incidents (54.3%). Single-vehicle crashes were the second most frequent type, with 161 incidents, representing 43.5% of the total.

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: 370
  • Total persons involved: 718
  • Total vehicles involved: 588

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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