Yearly Traffic Safety Analysis

150 CRASHES IN
IOWA, IA
2015

In 2015, Humboldt County recorded 150 traffic crashes, resulting in 0 fatalities and 33 injuries. The most significant contributing factor identified in these incidents was collisions with animals, which accounted for 43 of the total crashes, representing 28.7% of all incidents.

150

Total Crash Events

0

Persons Killed

33

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 33 reported injuries in Humboldt County crashes involved motorists. There were no fatalities or injuries recorded for pedestrians or cyclists during this period. Similarly, no motorists were killed in traffic crashes.

0

Motorists Killed

33

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

Crash patterns in Humboldt County during 2015 show a concentration on weekdays, with Thursday being the peak day for incidents, recording 28 crashes. The most frequent time for crashes was the 3 p.m. hour, which saw 19 incidents. The majority of crashes, 91 out of 150, occurred during daylight hours.

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 in 2015, 122 out of 150 (81.3%), resulted in no injuries and were classified as property-damage-only. There were 28 crashes that involved injuries, categorized as either minor (11 crashes) or possible (17 crashes). No fatal crashes were recorded during this period, and there were no fatalities.

Outcome by Severity (Crash Events)

Minor Injury11minor injury crashes7.3%
Possible Injury17possible injury crashes11.3%
No Injury122no injury crashes81.3%

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 for crashes was interaction with an animal, cited in 43 incidents and representing 28.7% of the total. Following this, 'Lost Control' was a factor in 12 crashes (8.0%), and 'Ran off road - straight' was noted in 10 crashes (6.7%).

Officer-Reported Primary Contributing Cause

Animal43 (28.7%)
Lost Control12 (8%)
Ran off road - straight10 (6.7%)
Other (explain in narrative): Other9 (6%)
Ran off road - left8 (5.3%)
Driving too fast for conditions8 (5.3%)
FTYROW: From stop sign6 (4%)
Ran Stop Sign6 (4%)
FTYROW: From yield sign5 (3.3%)
Driver Distraction: Other interior distraction5 (3.3%)

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 91 incidents (60.7%) happening in daylight, 69 (46%) in clear weather, and 81 (54%) on dry road surfaces. Adverse weather was a factor in a smaller portion of crashes, with 13 incidents occurring during snow and 8 during rain. Icy or frosty road surfaces were present in 16 crashes.

Weather

Clear69 (58.5%)
Cloudy22 (18.6%)
Snow13 (11.0%)
Rain8 (6.8%)
Blowing Snow3 (2.5%)
Freezing rain/drizzle3 (2.5%)

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

Lighting

Daylight91 (76.5%)
Dark - roadway not lighted20 (16.8%)
Dusk3 (2.5%)
Dark - unknown roadway lighting2 (1.7%)
Dawn2 (1.7%)
Dark - roadway lighted1 (0.8%)

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

Road Surface

Dry81 (68.1%)
Ice/frost16 (13.4%)
Wet10 (8.4%)
Snow9 (7.6%)
Gravel2 (1.7%)
Slush1 (0.8%)

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 individuals aged 65 and older, with 47 persons recorded, followed by the 45-54 age group with 35 persons. Analysis of vehicle makes shows Chevrolet was the most common with 70 vehicles involved, followed by Ford with 39 vehicles and Dodge with 24 vehicles.

Top Vehicle Makes (226 vehicles)

1
CHEV40 (17.7%)
2
FORD39 (17.3%)
3
CHEVROLET30 (13.3%)
4
DODG13 (5.8%)
5
DODGE11 (4.9%)
6
PONTIAC8 (3.5%)
7
GMC7 (3.1%)
8
CHRYSLER7 (3.1%)
9
TOYOTA6 (2.7%)
10
TOYT5 (2.2%)

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

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

Sex Distribution (209 persons with recorded sex)

Male124 (59.3%)
Female85 (40.7%)

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

Major Cause

The most frequently cited major cause of crashes was 'Animal', which was attributed to 43 incidents. 'Lost Control' was the second leading cause with 12 crashes, followed by 'Ran off road - straight' with 10 crashes. Other notable causes included 'Driving too fast for conditions' and 'Ran off road - left', each contributing to 8 crashes.

Major Cause

1
Animal43 (31.6%)
2
Lost Control12 (8.8%)
3
Ran off road - straight10 (7.4%)
4
Other (explain in narrative): Other9 (6.6%)
5
Ran off road - left8 (5.9%)
6
Driving too fast for conditions8 (5.9%)
7
FTYROW: From stop sign6 (4.4%)
8
Ran Stop Sign6 (4.4%)
9
FTYROW: From yield sign5 (3.7%)

Showing top 9 of 26 reported. 17 additional (29 total) not shown: Driver Distraction: Other interior distraction, Followed too close, Ran Traffic Signal, Improper Backing, Passing: Through/around barrier, Ran off road - right, FTYROW: From driveway, Exceeded authorized speed, Cargo/equipment loss or shift, Driver Distraction: Inattentive/lost in thought, FTYROW: Making left turn, FTYROW: Other (explain in narrative), Improper or erratic lane changing, Made improper turn, Other (explain in narrative): Vision obstructed, Passing: With insufficient distance/inadequate visibility, Driver Distraction: Adjusting devices (radio, climate).

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 another vehicle in traffic, which occurred in 63 crashes. The second most frequent event was a collision with an animal, recorded in 43 incidents. Run-off-road events were also significant, including 9 rollovers and 9 crashes where the first harmful event was striking a ditch.

First Harmful Event

1
Collision with: Vehicle in traffic63 (42.3%)
2
Collision with: Animal43 (28.9%)
3
Collision with fixed object: Ditch9 (6%)
4
Non-collision events: Overturn/rollover9 (6%)
5
Collision with fixed object: Utility pole/light support3 (2%)
6
Collision with: Re-entering roadway3 (2%)
7
Collision with: Parked motor vehicle3 (2%)
8
Collision with fixed object: Tree2 (1.3%)
9
Collision with fixed object: Building2 (1.3%)

Showing top 9 of 20 reported. 11 additional (12 total) not shown: Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Traffic sign support, Collision with fixed object: Snow bank, Collision with fixed object: Mailbox, Collision with fixed object: Fence, Collision with: Thrown or falling object, Collision with fixed object: Embankment, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Culvert/pipe opening, Non-collision events: Vehicle went airborne.

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-intersection road segments, which accounted for 59 incidents. Four-way intersections were the most common junction type for crashes, with 39 incidents occurring at these locations. An additional 6 crashes happened at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature59 (49.2%)
2
Intersection: Four-way intersection39 (32.5%)
3
Intersection: T-intersection6 (5%)
4
Non-intersection: Driveway access (related, not in)6 (5%)
5
Non-intersection: Driveway access (within)3 (2.5%)
6
Intersection: Other intersection (explain in narrative)3 (2.5%)
7
Non-intersection: Other non-intersection (explain in narrative)3 (2.5%)
8
Intersection: L-intersection1 (0.8%)

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 92 vehicles recorded. Light trucks and pickups were the second most frequent type with 53 vehicles, followed by sport utility vehicles with 41. Heavy commercial vehicles, such as tractor-trailers, were involved in 5 crashes, and one motorcycle was involved in a crash.

Vehicle Type

"Other" combines 4 smaller categories (5 records): Moped (2), Single-unit truck (>= 3 axles) (1), Passenger van (seats 9-15) (1), Motorcycle (1).

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

Traffic Control Device

The majority of vehicles involved in crashes, 139 out of 226, were in areas with no traffic controls present. For vehicles at locations with controls, stop signs were the most common type, associated with 29 vehicles. Traffic signals and yield signs were each present for 8 vehicles involved in crashes.

Traffic Control Device

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 impact, with 52 vehicles sustaining damage to the front center. Front-corner impacts were also frequent, with 21 on the passenger side and 13 on the driver side. Rear-end impacts were indicated by 15 vehicles with damage to the rear.

Most Damaged Area

"Other" combines 8 smaller categories (54 records): Rear - driver side corner (10), Driver side - front (10), Passenger side - front (9), Top (9), Passenger side - middle (6), Rear - passenger side corner (5), Other (explain in narrative) (3), Non-collision/no damage (2).

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

Crashes by City

Crash incidents within municipal boundaries were concentrated in the city of Humboldt, which recorded 63 crashes. Other towns in the county saw significantly fewer incidents, with Dakota City reporting 4 crashes and Livermore reporting 3. A single crash was recorded in each of Bode, Bradgate, and Rutland.

Crashes by City

1
HUMBOLDT63 (86.3%)
2
DAKOTA CITY4 (5.5%)
3
LIVERMORE3 (4.1%)
4
BODE1 (1.4%)
5
BRADGATE1 (1.4%)
6
RUTLAND1 (1.4%)

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, 142 out of 149 for which road surface type was specified, occurred on paved roads. Crashes on unpaved surfaces such as gravel or dirt accounted for 7 incidents, representing approximately 4.7% of these crashes.

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, the most common was the road surface condition, such as being wet or icy, which was cited in 23 incidents. An additional crash was attributed to ruts, holes, or bumps in the road surface. For most crashes, no specific roadway factor was identified.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)23 (95.8%)
2
Ruts/holes/bumps1 (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 106 crashes. A further 38 crashes resulted in damages estimated between $7,500 and $25,000. Three crashes were estimated to have 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

Single-vehicle, non-collision events, such as running off the road or overturning, were the most common type of incident, accounting for 67 crashes or 44.7% of the total. Among multi-vehicle crashes, broadside collisions were most frequent with 27 incidents (18%), followed by rear-end collisions with 18 incidents (12%).

Manner of Collision

"Other" combines 3 smaller categories (6 records): Rear to rear (2), Other (explain in narrative) (2), Head-on (front to front) (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 involved was 'Movement essentially straight,' which was recorded for 140 of the 226 vehicles. Turning left was the next most frequent action, noted for 16 vehicles. Other actions such as turning right, slowing or stopping, and being legally parked were each recorded for 9 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight140 (66.4%)
2
Turning left16 (7.6%)
3
Turning right9 (4.3%)
4
Legally Parked9 (4.3%)
5
Slowing/stopping (deceleration)9 (4.3%)
6
Backing8 (3.8%)
7
Stopped in traffic5 (2.4%)
8
Negotiating a curve5 (2.4%)
9
Accelerating in road3 (1.4%)

Showing top 9 of 14 reported. 5 additional (7 total) not shown: Other (explain in narrative), Starting in road, Overtaking/passing, Changing lanes, Leaving a parked position.

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

Person Type

The overwhelming majority of individuals involved in crashes were drivers, accounting for 255 of the 259 people recorded. Passengers accounted for the remaining 4 individuals. No pedestrians or cyclists were recorded as being involved in these crashes.

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 33 individuals sustained injuries in crashes. Of these, 21 people had injuries classified as 'Possible,' and 12 people had 'Minor' injuries. There were no fatal or serious injuries recorded among any persons involved in crashes during this period.

Person Injury Severity

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

Vehicles Per Crash

Crashes were nearly evenly split between single-vehicle and two-vehicle incidents. Single-vehicle crashes accounted for 77 incidents (51.3% of the total), while 71 crashes involved two vehicles. There was one crash involving three vehicles and one involving four vehicles.

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: 150
  • Total persons involved: 259
  • Total vehicles involved: 226

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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