Yearly Traffic Safety Analysis

135 CRASHES IN
IOWA, IA
2015

In 2015, Monona County recorded 135 total traffic crashes, resulting in 3 fatalities and 71 injuries. A significant portion of these incidents, 24.4%, were attributed to collisions involving animals. Single-vehicle crashes, which include animal strikes and run-off-road events, constituted just over half of all incidents.

135

Total Crash Events

3

Persons Killed

71

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

In 2015, all 3 fatalities and 70 of the 71 injuries recorded in Monona County involved motorists. There were no reported fatalities or injuries among pedestrians or cyclists. One additional injury was recorded for a person classified as an 'other non-motorist'.

3

Motorists Killed

0

Other Killed

70

Motorists Injured

1

Other 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 Monona County peaked on Mondays, which saw 27 incidents in 2015. The most frequent time for crashes was the 1 p.m. hour, with 11 events, though morning and evening commute times also saw elevated numbers. While a majority of crashes (73) occurred during daylight hours, a notable 29 crashes took place on unlit roadways after dark.

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

Out of 135 total crashes, 86 incidents (63.7%) resulted in no injuries. The remaining crashes included 47 that caused injuries of varying severity and 2 that were fatal. These 2 fatal crashes resulted in a total of 3 deaths.

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

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.5%
Serious Injury9serious injury crashes6.7%
Minor Injury14minor injury crashes10.4%
Possible Injury24possible injury crashes17.8%
No Injury86no injury crashes63.7%

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 frequently cited contributing factor in Monona County crashes was 'Animal,' accounting for 33 incidents, or 24.4% of the total. Following this, 'Lost Control' was noted in 16 crashes (11.9%), and 'Ran off road - straight' was a factor in 12 crashes (8.9%). Various forms of driver distraction and failure to yield the right-of-way were also cited in multiple incidents.

Officer-Reported Primary Contributing Cause

Animal33 (24.4%)
Lost Control16 (11.9%)
Ran off road - straight12 (8.9%)
Followed too close7 (5.2%)
FTYROW: At uncontrolled intersection5 (3.7%)
Driving too fast for conditions5 (3.7%)
Swerving/Evasive Action5 (3.7%)
Driver Distraction: Other interior distraction5 (3.7%)
FTYROW: From stop sign5 (3.7%)
Driver Distraction: Other electronic device activity3 (2.2%)

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

Road & Environmental Conditions

The majority of crashes occurred in ideal driving conditions, with 83 incidents (61.5%) happening in clear weather and 85 (63%) on dry road surfaces. Over half of the crashes (73) took place during daylight hours. However, adverse conditions were also present, including 11 crashes on snow-covered roads and 29 crashes on unlit roadways in the dark.

Weather

Clear83 (71.6%)
Cloudy17 (14.7%)
Snow6 (5.2%)
Rain5 (4.3%)
Blowing Snow3 (2.6%)
Sleet, hail1 (0.9%)
Fog, smoke, smog1 (0.9%)

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

Lighting

Daylight73 (62.4%)
Dark - roadway not lighted29 (24.8%)
Dark - roadway lighted8 (6.8%)
Dusk5 (4.3%)
Dawn2 (1.7%)

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

Road Surface

Dry85 (73.3%)
Snow11 (9.5%)
Wet6 (5.2%)
Ice/frost6 (5.2%)
Gravel5 (4.3%)
Mud, dirt2 (1.7%)
Slush1 (0.9%)

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

Vehicles & Demographics

Analysis of persons involved in crashes shows the 45-54 age group was the most represented, with 64 individuals, followed by the 26-34 age group with 40 individuals. The most common vehicle makes involved were Chevrolet (45 vehicles), Ford (38 vehicles), and Dodge (19 vehicles). These figures represent the makes of vehicles in collisions and do not reflect local vehicle registration data.

Top Vehicle Makes (198 vehicles)

1
FORD38 (19.2%)
2
CHEV23 (11.6%)
3
CHEVROLET22 (11.1%)
4
DODGE10 (5.1%)
5
DODG9 (4.5%)
6
GMC8 (4%)
7
PONT5 (2.5%)
8
HONDA5 (2.5%)
9
JEEP4 (2%)
10
CHRY4 (2%)

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

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

Sex Distribution (173 persons with recorded sex)

Male101 (58.4%)
Female72 (41.6%)

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

Major Cause

The primary major cause attributed to crashes was contact with an animal, cited in 33 incidents. 'Lost Control' was the second most common cause, listed for 16 crashes, followed by 'Ran off road - straight' in 12 crashes. These three factors collectively account for more than 45% of all crashes with a determined cause.

Major Cause

1
Animal33 (25%)
2
Lost Control16 (12.1%)
3
Ran off road - straight12 (9.1%)
4
Followed too close7 (5.3%)
5
FTYROW: At uncontrolled intersection5 (3.8%)
6
Driving too fast for conditions5 (3.8%)
7
Swerving/Evasive Action5 (3.8%)
8
Driver Distraction: Other interior distraction5 (3.8%)
9
FTYROW: From stop sign5 (3.8%)

Showing top 9 of 33 reported. 24 additional (39 total) not shown: Driver Distraction: Other electronic device activity, FTYROW: From driveway, Operating vehicle in an reckless, erratic, careless, negligent manner, Ran off road - left, Ran Stop Sign, Other (explain in narrative): No improper action, FTYROW: Other (explain in narrative), Driver Distraction: Exterior distraction, Ran Traffic Signal, Driver Distraction: Unrestrained animal, Other (explain in narrative): Other, Passing: Other passing (explain in narrative), Passing: Through/around barrier, Passing: Where prohibited by signs/markings, Ran off road - right, Driver Distraction: Inattentive/lost in thought, Failed to keep in proper lane, Exceeded authorized speed, Crossed centerline (undivided), FTYROW: From parked position, FTYROW: From yield sign, FTYROW: Making left turn, Driver Distraction: Reaching for object(s)/fallen object(s), Made improper turn.

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

First Harmful Event

The most frequent first harmful event was a collision with another vehicle in traffic, occurring in 42 crashes. The second most common event was a collision with an animal, which initiated 33 crashes. Run-off-road events were also prevalent, including 14 rollovers and 13 crashes where the first harmful event was striking a ditch.

First Harmful Event

1
Collision with: Vehicle in traffic42 (31.1%)
2
Collision with: Animal33 (24.4%)
3
Non-collision events: Overturn/rollover14 (10.4%)
4
Collision with fixed object: Ditch13 (9.6%)
5
Collision with: Re-entering roadway5 (3.7%)
6
Other (explain in narrative)4 (3%)
7
Collision with: Struck/struck by object/cargo/person from other vehicle4 (3%)
8
Non-collision events: Non-contact vehicle (phantom)4 (3%)
9
Collision with fixed object: Utility pole/light support3 (2.2%)

Showing top 9 of 20 reported. 11 additional (13 total) not shown: Collision with: Other non-fixed object (explain in narrative), Collision with: Parked motor vehicle, Collision with fixed object: Fence, Collision with fixed object: Curb/island/raised median, Collision with: Thrown or falling object, Collision with fixed object: Embankment, Non-collision events: Jackknife, Collision with fixed object: Bridge/bridge rail parapet, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Guardrail - end, Collision with fixed object: Traffic sign support.

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

Roadway Junction / Feature

A majority of crashes, 68 incidents or 50.4%, occurred at non-junction locations along a road segment. Intersections accounted for a smaller share, with 20 crashes at four-way intersections and 9 at T-intersections. Driveway-related incidents were noted in 10 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature68 (58.1%)
2
Intersection: Four-way intersection20 (17.1%)
3
Intersection: T-intersection9 (7.7%)
4
Non-intersection: Driveway access (related, not in)7 (6%)
5
Non-intersection: Other non-intersection (explain in narrative)4 (3.4%)
6
Non-intersection: Driveway access (within)3 (2.6%)
7
Non-intersection: Alley1 (0.9%)
8
Interchange-related: On-ramp merge area1 (0.9%)
9
Interchange-related: Other interchange (explain in narrative)1 (0.9%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Interchange-related: Off-ramp, diverge area, Intersection: Intersection with ramp, Interchange-related: Off-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, accounting for 74 of the vehicles. Light trucks and pickups were the second most frequent with 44 vehicles, followed by sport utility vehicles with 35. Ten tractor/semi-trailers and six motorcycles were also involved in crashes during this period.

Vehicle Type

"Other" combines 7 smaller categories (10 records): Single unit truck (2-axle, 6-tire) (3), Single-unit truck (>= 3 axles) (2), Other (explain in narrative) (1), Farm tractor (1), Motor home/recreational vehicle (1), Other bus (seats > 15) (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

For vehicles involved in crashes, the most common situation was the absence of traffic controls, noted for 145 vehicles. Where traffic controls were present, 12 vehicles were subject to stop signs and 11 were at traffic signals. A 'No Passing Zone' was the relevant traffic control for 6 vehicles.

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 frequent area of most severe damage, recorded for 53 vehicles. An additional 29 vehicles sustained primary damage to a front corner. Rear impacts were the principal point of damage for 18 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (41 records): Passenger side - rear (8), Top (7), Other (explain in narrative) (6), Passenger side - middle (5), Rear - passenger side corner (5), Driver side - rear (5), Undercarriage (2), Rear - driver side corner (2), Cargo loss (1).

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

Crashes by City

Crash distribution within Monona County shows the highest concentration in Onawa, with 33 incidents. Mapleton recorded the second-highest volume with 8 crashes, followed by Whiting with 4. Several other municipalities, including Soldier, Castana, and Ute, each reported 2 crashes.

Crashes by City

1
ONAWA33 (60%)
2
MAPLETON8 (14.5%)
3
WHITING4 (7.3%)
4
SOLDIER2 (3.6%)
5
CASTANA2 (3.6%)
6
UTE2 (3.6%)
7
RODNEY1 (1.8%)
8
MOORHEAD1 (1.8%)
9
BLENCOE1 (1.8%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: TURIN.

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, 124 out of 135, occurred on paved roadways. A smaller portion, 11 crashes or 8.1% of the total, took place 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, 'Surface condition' such as wet or icy roads was the leading contributor, noted in 14 incidents. A 'Slippery, loose or worn surface' was a factor in 4 crashes. Additionally, 2 crashes were related to a work zone.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)14 (60.9%)
2
Slippery, loose or worn surface4 (17.4%)
3
Obstruction in roadway2 (8.7%)
4
Work Zone (roadway-related)2 (8.7%)
5
Shoulders (none, low, soft, high)1 (4.3%)

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, driving under the influence of alcohol was the most frequent, noted for 9 individuals. An additional 3 drivers were reported as asleep or fatigued. One driver was noted as being under the influence of drugs or medication.

Driver Condition

1
Under the influence of alcohol9 (60%)
2
Asleep/fatigued3 (20%)
3
Emotional (e.g. depressed, angry)2 (13.3%)
4
Under the influence of drugs/meds1 (6.7%)

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 95 crashes. A further 33 crashes resulted in damages estimated between $7,500 and $25,000. High-damage crashes, with costs exceeding $25,000, accounted for 7 incidents, or 5.2% of the total.

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 68 crashes, or 50.4% of all incidents. Among multi-vehicle crashes, rear-end collisions were the most frequent type, with 18 occurrences (13.3%), followed by broadside collisions with 15 occurrences (11.1%).

Manner of Collision

"Other" combines 2 smaller categories (3 records): Head-on (front to front) (2), Other (explain in narrative) (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 pre-crash action for vehicles involved was 'Movement essentially straight,' recorded for 136 vehicles. Turning maneuvers were the next most frequent actions, with 16 vehicles turning left and 7 turning right immediately prior to their respective crashes.

Pre-Crash Driver Action

1
Movement essentially straight136 (73.5%)
2
Turning left16 (8.6%)
3
Turning right7 (3.8%)
4
Legally Parked7 (3.8%)
5
Backing5 (2.7%)
6
Negotiating a curve5 (2.7%)
7
Other (explain in narrative)3 (1.6%)
8
Entering traffic lane (merging)2 (1.1%)
9
Making U-turn1 (0.5%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Entering a parked position, Slowing/stopping (deceleration), Overtaking/passing.

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

Person Type

Of the 274 individuals involved in crashes, the vast majority, 253 people (92.3%), were drivers. Passengers accounted for 20 of the individuals involved (7.3%), and one person was classified as an 'other non-motorist'.

Person Type

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

Person Injury Severity

Among all persons for whom an injury status was recorded, 3 individuals sustained fatal injuries. A total of 71 people were injured, including 14 with serious injuries, 19 with minor injuries, and 38 with possible injuries. Two individuals were recorded as having no 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 available data for safety equipment usage, 43 occupants were reported as using a shoulder and lap belt. A notable 12 individuals were recorded as using no safety equipment at all. The data also shows usage of various child safety seats for 5 occupants.

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 of incident, accounting for 75 of the 135 total crashes (55.6%). Two-vehicle collisions were also frequent, with 58 incidents. There was one crash involving three vehicles and 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: 135
  • Total persons involved: 274
  • Total vehicles involved: 198

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

ThatCarHitMe.com · An Injuria.ai Company