Yearly Traffic Safety Analysis

160 CRASHES IN
IOWA, IA
2015

In 2015, Kossuth County recorded 160 traffic crashes, resulting in 2 fatalities and 89 injuries. A notable finding from the data is that single-vehicle, non-collision events, such as running off the road, were the most common type of crash, accounting for 35% of all incidents. The majority of crashes occurred in clear weather and daylight conditions.

160

Total Crash Events

2

Persons Killed

89

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

In 2015, motorists accounted for all fatalities and the vast majority of injuries. Two motorists were killed and 84 were injured in crashes. Vulnerable road users were also impacted, with 3 cyclists and 2 pedestrians sustaining injuries, although none were fatal.

0

Pedestrians Killed

0

Cyclists Killed

2

Motorists Killed

2

Pedestrians Injured

3

Cyclists Injured

84

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 Kossuth County show a clear peak during the work week, with Thursday being the most frequent day for incidents, recording 37 crashes. The afternoon commute appears to be the most hazardous time, as the single busiest hour was 5 p.m., with 15 crashes. The vast majority of collisions, 120 out of 160, 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

Over half of the crashes, 87 out of 160 (54.4%), resulted in no injuries. The remaining incidents involved injuries of varying severity, including 8 serious injury crashes and 38 minor injury crashes. Two crashes were fatal, leading to a total of 2 fatalities for the year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.3%
Serious Injury8serious injury crashes5%
Minor Injury38minor injury crashes23.8%
Possible Injury25possible injury crashes15.6%
No Injury87no injury crashes54.4%

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 drivers losing control, which was cited in 22 incidents (13.8%). Following too closely was the second most common factor, contributing to 14 crashes (8.8%), while driving too fast for conditions was a factor in 12 crashes (7.5%).

Officer-Reported Primary Contributing Cause

Lost Control22 (13.8%)
Followed too close14 (8.8%)
Driving too fast for conditions12 (7.5%)
FTYROW: From stop sign10 (6.3%)
Made improper turn8 (5%)
Other (explain in narrative): Other7 (4.4%)
Ran off road - left7 (4.4%)
Ran off road - straight7 (4.4%)
Animal5 (3.1%)
FTYROW: At uncontrolled intersection5 (3.1%)

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 in 2015 occurred under ideal driving conditions. Data shows that 120 crashes (75%) happened in daylight, 98 (61.3%) in clear weather, and 106 (66.3%) on dry road surfaces. Adverse conditions were less frequent, with rain cited in 12 crashes and snow in 11 crashes.

Weather

Clear98 (63.2%)
Cloudy29 (18.7%)
Rain12 (7.7%)
Snow11 (7.1%)
Freezing rain/drizzle2 (1.3%)
Severe Winds1 (0.6%)
Fog, smoke, smog1 (0.6%)
Sleet, hail1 (0.6%)

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

Lighting

Daylight120 (77.9%)
Dark - roadway not lighted13 (8.4%)
Dark - roadway lighted13 (8.4%)
Dawn4 (2.6%)
Dark - unknown roadway lighting2 (1.3%)
Dusk2 (1.3%)

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

Road Surface

Dry106 (68.4%)
Wet19 (12.3%)
Ice/frost13 (8.4%)
Gravel8 (5.2%)
Snow7 (4.5%)
Slush1 (0.6%)
Sand1 (0.6%)

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

Vehicles & Demographics

Among the 360 people involved in crashes, the 26-34 and 65+ age groups were the most represented, each with 56 individuals. An analysis of the 267 vehicles involved shows that Chevrolet (56), Ford (47), and Dodge (22) were the most frequent makes recorded in crash reports. Passenger cars were the most common vehicle type, accounting for 102 of the vehicles involved.

Top Vehicle Makes (267 vehicles)

1
FORD47 (17.6%)
2
CHEV33 (12.4%)
3
CHEVROLET23 (8.6%)
4
DODG12 (4.5%)
5
GMC11 (4.1%)
6
DODGE10 (3.7%)
7
BUIC9 (3.4%)
8
JEEP9 (3.4%)
9
PONT8 (3%)
10
PONTIAC7 (2.6%)

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

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

Sex Distribution (242 persons with recorded sex)

Male150 (62.0%)
Female92 (38.0%)

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 for crashes was a driver losing control, accounting for 22 incidents. Following too closely was the cause for 14 crashes, and driving too fast for conditions was listed for 12 crashes. Failure to yield from a stop sign contributed to another 10 collisions.

Major Cause

1
Lost Control22 (14.2%)
2
Followed too close14 (9%)
3
Driving too fast for conditions12 (7.7%)
4
FTYROW: From stop sign10 (6.5%)
5
Made improper turn8 (5.2%)
6
Other (explain in narrative): Other7 (4.5%)
7
Ran off road - left7 (4.5%)
8
Ran off road - straight7 (4.5%)
9
Animal5 (3.2%)

Showing top 9 of 36 reported. 27 additional (63 total) not shown: FTYROW: At uncontrolled intersection, FTYROW: Making left turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Ran Traffic Signal, Improper Backing, FTYROW: From yield sign, Driver Distraction: Other interior distraction, Swerving/Evasive Action, Driver Distraction: Inattentive/lost in thought, Ran Stop Sign, Exceeded authorized speed, FTYROW: To pedestrian, Improper or erratic lane changing, Passing: Other passing (explain in narrative), Ran off road - right, Failed to keep in proper lane, FTYROW: From parked position, Other (explain in narrative): Vision obstructed, Crossed centerline (undivided), Passing: Where prohibited by signs/markings, Driver Distraction: Exterior distraction, FTYROW: From driveway, FTYROW: Making right turn on red signal, Driver Distraction: Manual operation of an electronic communication device, Other (explain in narrative): Improper operation, Other (explain in narrative): No improper action, FTYROW: Other (explain in narrative).

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 81 of the 160 crashes. Run-off-road events were also significant, with the first harmful event being a collision with a ditch in 19 cases and an overturn or rollover in 12 cases. Collisions with animals were the first harmful event in 5 crashes.

First Harmful Event

1
Collision with: Vehicle in traffic81 (51.6%)
2
Collision with fixed object: Ditch19 (12.1%)
3
Collision with: Parked motor vehicle13 (8.3%)
4
Non-collision events: Overturn/rollover12 (7.6%)
5
Collision with: Animal5 (3.2%)
6
Collision with fixed object: Utility pole/light support4 (2.5%)
7
Collision with fixed object: Curb/island/raised median4 (2.5%)
8
Collision with: Non-motorist (see non-motorist section - NOT a unit)3 (1.9%)
9
Collision with fixed object: Building2 (1.3%)

Showing top 9 of 20 reported. 11 additional (14 total) not shown: Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Bridge pier or support, Non-collision events: Non-contact vehicle (phantom), Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Fire hydrant, Collision with fixed object: Ground, Collision with fixed object: Tree, Collision with fixed object: Embankment, Collision with: Re-entering roadway.

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 75 incidents. Four-way intersections were the most common junction type for crashes, with 38 incidents occurring at these locations. T-intersections were the site of another 14 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature75 (49%)
2
Intersection: Four-way intersection38 (24.8%)
3
Intersection: T-intersection14 (9.2%)
4
Non-intersection: Driveway access (related, not in)6 (3.9%)
5
Intersection: Y-intersection4 (2.6%)
6
Non-intersection: Railroad grade crossing4 (2.6%)
7
Intersection: Other intersection (explain in narrative)3 (2%)
8
Non-intersection: Driveway access (within)2 (1.3%)
9
Non-intersection: Bike lanes1 (0.7%)

Showing top 9 of 15 reported. 6 additional (6 total) not shown: Intersection: Five points or more, Intersection: Traffic circle, Non-intersection: Alley, Interchange-related: Other interchange (explain in narrative), Non-intersection: Crossover-related, Non-intersection: Other non-intersection (explain in narrative).

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 102 units recorded. Light trucks and SUVs were also frequently involved, with 64 four-tire light trucks and 38 sport utility vehicles documented. Tractor/semi-trailers were involved in 13 crashes, and motorcycles were involved in 10.

Vehicle Type

"Other" combines 12 smaller categories (17 records): Cargo/panel van (3), School bus (seats > 15) (2), Single-unit truck (>= 3 axles) (2), All-terrain vehicle (ATV) (2), Passenger van (seats 9-15) (1), Farm tractor (1), Moped (1), Farm equipment (explain in narrative) (1), Snowmobile (1), Other light truck (<=10000 lbs) (1), Other (explain in narrative) (1), Other bus (seats > 15) (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 were in areas with no traffic controls present, accounting for 175 vehicles. For crashes at controlled locations, stop signs were the most common device, present for 44 vehicles, followed by traffic signals, which were present for 28 vehicles.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): No Passing Zone (marked) (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 frequent area of impact, recorded as the most damaged area for 77 vehicles. Front-passenger side corner impacts were also common, with 37 instances. Rear-end collisions were indicated by 26 vehicles having the rear as their most damaged area.

Most Damaged Area

"Other" combines 8 smaller categories (60 records): Driver side - rear (14), Passenger side - front (12), Rear - passenger side corner (10), Passenger side - rear (8), Rear - driver side corner (7), Other (explain in narrative) (5), Non-collision/no damage (2), Top (2).

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

Crashes by City

The distribution of crashes across municipalities in Kossuth County shows a high concentration in Algona, which recorded 105 of the 160 total crashes. Other towns such as Whittemore and Swea City each had 4 crashes, while Ledyard, Lone Rock, Titonka, Wesley, and Fenton each had 3 crashes.

Crashes by City

1
ALGONA105 (77.8%)
2
WHITTEMORE4 (3%)
3
SWEA CITY4 (3%)
4
LAKOTA3 (2.2%)
5
LEDYARD3 (2.2%)
6
LONE ROCK3 (2.2%)
7
TITONKA3 (2.2%)
8
WESLEY3 (2.2%)
9
FENTON3 (2.2%)

Showing top 9 of 12 reported. 3 additional (4 total) not shown: WEST BEND, LU VERNE, BURT.

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 occurred on paved roadways, with 144 incidents. Unpaved gravel or dirt roads were the location for 14 crashes, accounting for 8.9% of the 158 crashes where the road surface type was specified.

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 the crashes where a roadway factor was identified, adverse surface conditions such as wet or icy roads were the leading contributor, cited in 21 incidents. Other factors were less common, with a slippery or loose surface noted in 2 cases and debris on the roadway in 1 case.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)21 (77.8%)
2
Slippery, loose or worn surface2 (7.4%)
3
Debris1 (3.7%)
4
Disabled vehicle1 (3.7%)
5
Shoulders (none, low, soft, high)1 (3.7%)
6
Work Zone (roadway-related)1 (3.7%)

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,' other conditions were noted in a minority of cases. Six drivers were identified as being under the influence of alcohol, and 5 were noted as being asleep or fatigued. Medical conditions and drug influence were each cited for 2 drivers.

Driver Condition

1
Under the influence of alcohol6 (33.3%)
2
Asleep/fatigued5 (27.8%)
3
Emotional (e.g. depressed, angry)2 (11.1%)
4
Medical condition (seizure, reaction)2 (11.1%)
5
Under the influence of drugs/meds2 (11.1%)
6
Physical impairment1 (5.6%)

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 97 crashes. A smaller number of incidents resulted in more significant damage, with 42 crashes estimated between $7,500 and $25,000, and 8 crashes exceeding $25,000 in property damage.

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 most common crash type, comprising 56 of the 160 total incidents (35%). Multi-vehicle crashes were most frequently rear-end collisions (36 crashes, or 22.5%) and broadside collisions (28 crashes, or 17.5%).

Manner of Collision

"Other" combines 3 smaller categories (7 records): Other (explain in narrative) (3), Sideswipe, opposite direction (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

An analysis of vehicle actions prior to collision shows that the majority of vehicles, 162 in total, were moving straight ahead. The next most common actions involved turning, with 29 vehicles turning left, or being stationary, with 19 vehicles legally parked before the crash.

Pre-Crash Driver Action

1
Movement essentially straight162 (61.4%)
2
Turning left29 (11%)
3
Legally Parked19 (7.2%)
4
Turning right18 (6.8%)
5
Stopped in traffic10 (3.8%)
6
Backing8 (3%)
7
Slowing/stopping (deceleration)4 (1.5%)
8
Other (explain in narrative)3 (1.1%)
9
Overtaking/passing3 (1.1%)

Showing top 9 of 16 reported. 7 additional (8 total) not shown: Changing lanes, Entering a parked position, Leaving a parked position, Leaving traffic lane, Making U-turn, Negotiating a curve, Accelerating in road.

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

Person Type

Of the 360 individuals involved in crashes, the overwhelming majority, 341 people, were drivers. Passengers accounted for 14 of the individuals, while vulnerable road users included 3 bicyclists and 2 pedestrians.

Person Type

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

Person Injury Severity

Among all 360 people involved in crashes, 2 sustained fatal injuries and 11 suffered serious injuries. A larger number experienced less severe outcomes, with 47 minor injuries and 31 possible injuries recorded. The data indicates that 89 individuals were injured in total.

Person Injury Severity

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

Occupant Safety Equipment

Among participants for whom safety equipment use was documented, 47 were reported to have used a shoulder and lap belt. Notably, 8 individuals were recorded as having used no safety equipment at all. Three participants 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

Two-vehicle collisions were the most frequent type of crash, with 97 incidents recorded. Single-vehicle crashes were the second most common, accounting for 57 incidents. Most other crashes involved three vehicles (4 incidents), with one crash 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: 160
  • Total persons involved: 360
  • Total vehicles involved: 267

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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