Yearly Traffic Safety Analysis

81 CRASHES IN
IOWA, IA
2015

In 2015, Decatur County recorded 81 traffic crashes, resulting in 0 fatalities and 25 injuries. The most significant contributing factor identified in these incidents was collisions involving animals, which accounted for 38.3% of all crashes, totaling 31 incidents.

81

Total Crash Events

0

Persons Killed

25

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 25 reported injuries in Decatur County crashes were sustained by motorists. There were no fatalities recorded for any group. Additionally, no pedestrians or cyclists were reported as either killed or injured in traffic collisions during this period.

0

Motorists Killed

25

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 occurrences in Decatur County peaked on Saturdays, with 19 incidents recorded. The most frequent time for crashes was the 6 p.m. hour, which saw 8 crashes. Analysis of lighting conditions shows that while 24 crashes occurred during daylight, a notable 17 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

Of the 81 total crashes, 75.3% (61 incidents) resulted in no injuries and were classified as property-damage-only. The remaining 24.7% involved injuries, including 5 serious injury crashes, 6 minor injury crashes, and 9 possible injury crashes. There were no fatal crashes recorded in 2015, and consequently, no persons were killed.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes6.2%
Minor Injury6minor injury crashes7.4%
Possible Injury9possible injury crashes11.1%
No Injury61no injury crashes75.3%

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 most common contributing factor cited in Decatur County crashes was 'Animal,' which was involved in 31 incidents, representing 38.3% of the total. The second most frequent factor was 'Lost Control,' accounting for 9 crashes (11.1%). Various forms of driver distraction, including adjusting devices, exterior distractions, and reaching for objects, were collectively cited in 6 crashes.

Officer-Reported Primary Contributing Cause

Animal31 (38.3%)
Lost Control9 (11.1%)
Other (explain in narrative): Other6 (7.4%)
Ran off road - straight4 (4.9%)
Followed too close3 (3.7%)
Crossed centerline (undivided)3 (3.7%)
Driver Distraction: Adjusting devices (radio, climate)2 (2.5%)
Driver Distraction: Exterior distraction2 (2.5%)
Driver Distraction: Reaching for object(s)/fallen object(s)2 (2.5%)
FTYROW: From yield sign2 (2.5%)

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

Road & Environmental Conditions

Analysis of environmental conditions shows that many crashes occurred in ideal conditions, with 26 incidents in clear weather and 31 on dry road surfaces. Crashes during daylight hours accounted for 24 incidents. Adverse conditions also played a role, with 10 crashes occurring on wet roads and 6 on icy or frosty surfaces.

Weather

Clear26 (50.0%)
Cloudy9 (17.3%)
Rain6 (11.5%)
Snow4 (7.7%)
Freezing rain/drizzle4 (7.7%)
Blowing Snow2 (3.8%)
Severe Winds1 (1.9%)

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

Lighting

Daylight24 (45.3%)
Dark - roadway not lighted17 (32.1%)
Dawn4 (7.5%)
Dark - roadway lighted3 (5.7%)
Dusk3 (5.7%)
Dark - unknown roadway lighting2 (3.8%)

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

Road Surface

Dry31 (58.5%)
Wet10 (18.9%)
Ice/frost6 (11.3%)
Snow3 (5.7%)
Gravel2 (3.8%)
Slush1 (1.9%)

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

Vehicles & Demographics

Among persons involved in crashes, the most represented age groups were 55-64 years old (24 individuals), 45-54 years old (23 individuals), and 26-34 years old (20 individuals). The most frequent vehicle makes involved in crashes were Ford with 17 vehicles and Chevrolet with 15 vehicles. Dodge was also prominent, appearing with 8 vehicles.

Top Vehicle Makes (110 vehicles)

1
FORD17 (15.5%)
2
CHEVROLET15 (13.6%)
3
DODGE8 (7.3%)
4
CHEV6 (5.5%)
5
FREIGHTLINER5 (4.5%)
6
PETERBILT4 (3.6%)
7
CHRYSLER4 (3.6%)
8
DODG4 (3.6%)
9
KENWORTH4 (3.6%)
10
GMC4 (3.6%)

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

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

Sex Distribution (91 persons with recorded sex)

Male67 (73.6%)
Female24 (26.4%)

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

Major Cause

The primary major cause of crashes was interaction with an 'Animal,' cited in 31 incidents, or 38.3% of the total. 'Lost Control' was the second leading cause, contributing to 9 crashes (11.1%). Other notable causes included 'Ran off road - straight' with 4 crashes and 'Followed too close' with 3 crashes.

Major Cause

1
Animal31 (39.2%)
2
Lost Control9 (11.4%)
3
Other (explain in narrative): Other6 (7.6%)
4
Ran off road - straight4 (5.1%)
5
Followed too close3 (3.8%)
6
Crossed centerline (undivided)3 (3.8%)
7
Driver Distraction: Adjusting devices (radio, climate)2 (2.5%)
8
Driver Distraction: Exterior distraction2 (2.5%)
9
Driver Distraction: Reaching for object(s)/fallen object(s)2 (2.5%)

Showing top 9 of 22 reported. 13 additional (17 total) not shown: FTYROW: From yield sign, Passing: Other passing (explain in narrative), Ran off road - left, Ran Stop Sign, Made improper turn, Other (explain in narrative): No improper action, Driving too fast for conditions, Driver Distraction: Other interior distraction, Swerving/Evasive Action, FTYROW: From parked position, Driver Distraction: Talking on a hand-held device, Improper or erratic lane changing, Failed to keep in proper lane.

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: Animal,' which occurred in 31 crashes. The second most common event was a 'Collision with: Vehicle in traffic,' recorded in 25 crashes. Single-vehicle events were also significant, with 6 crashes involving a ditch and 5 involving an overturn or rollover.

First Harmful Event

1
Collision with: Animal31 (39.7%)
2
Collision with: Vehicle in traffic25 (32.1%)
3
Collision with fixed object: Ditch6 (7.7%)
4
Non-collision events: Overturn/rollover5 (6.4%)
5
Non-collision events: Jackknife2 (2.6%)
6
Collision with fixed object: Traffic sign support1 (1.3%)
7
Collision with: Other non-fixed object (explain in narrative)1 (1.3%)
8
Collision with: Parked motor vehicle1 (1.3%)
9
Collision with: Re-entering roadway1 (1.3%)

Showing top 9 of 14 reported. 5 additional (5 total) not shown: Collision with fixed object: Embankment, Non-collision events: Fell/jumped from vehicle, Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Mailbox, Collision with fixed object: Curb/island/raised median.

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

Roadway Junction / Feature

A significant majority of crashes, 38 in total, occurred at non-intersection locations. In contrast, 8 crashes were recorded at various types of intersections, including 4 at four-way intersections and 2 at T-intersections. Interchange-related crashes, such as on off-ramps, accounted for another 4 incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature38 (73.1%)
2
Intersection: Four-way intersection4 (7.7%)
3
Intersection: T-intersection2 (3.8%)
4
Interchange-related: Off-ramp2 (3.8%)
5
Non-intersection: Other non-intersection (explain in narrative)1 (1.9%)
6
Intersection: Other intersection (explain in narrative)1 (1.9%)
7
Interchange-related: Off-ramp, diverge area1 (1.9%)
8
Intersection: Intersection with ramp1 (1.9%)
9
Interchange-related: Mainline, between ramps1 (1.9%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Non-intersection: Driveway access (related, not in).

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 38 units recorded. Light trucks and pickups were the second most frequent with 25 vehicles, followed by tractor/semi-trailers with 15 vehicles and sport utility vehicles with 12. One motorcycle was involved in a crash during this period.

Vehicle Type

"Other" combines 5 smaller categories (6 records): Maintenance/construction vehicle (2), Motorcycle (1), Single-unit truck (>= 3 axles) (1), Cargo/panel van (1), School 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 vast majority of vehicles involved in crashes, 67 in total, were at locations with no traffic controls present. Where controls were a factor, stop signs were noted for 4 vehicles and work zone signs were also present for 4 vehicles. Yield signs were a factor for 3 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 damage, reported for 25 vehicles, indicating a prevalence of frontal impacts. The rear of the vehicle was the second most frequent damage area with 14 instances, consistent with rear-end collisions. Damage to the driver-side front and front-driver-side corner was also notable, each reported for 6 vehicles.

Most Damaged Area

"Other" combines 8 smaller categories (16 records): Undercarriage (3), Passenger side - front (3), Driver side - rear (2), Passenger side - middle (2), Rear - driver side corner (2), Rear - passenger side corner (2), Other (explain in narrative) (1), Non-collision/no damage (1).

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

Crashes by City

Crash distribution within Decatur County shows the highest concentration in Leon, with 11 reported incidents. Lamoni followed with 3 crashes, and Decatur City recorded 2 crashes. A number of crashes occurred outside of any specific municipal boundary and are not included in this city-level breakdown.

Crashes by City

1
LEON11 (61.1%)
2
LAMONI3 (16.7%)
3
DECATUR CITY2 (11.1%)
4
DAVIS CITY1 (5.6%)
5
GARDEN GROVE1 (5.6%)

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

Paved vs Unpaved Road

The overwhelming majority of crashes, 79 in total, occurred on paved roadways. A small number of incidents, 2 crashes, were reported 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

Roadway factors were cited as a contributor in a minority of crashes. The most common factor was 'Surface condition,' such as wet or icy roads, which was noted in 11 incidents. Work zones were also a contributing factor, with 3 crashes occurring in roadway-related work zones.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)11 (73.3%)
2
Work Zone (roadway-related)3 (20%)
3
Non-highway work1 (6.7%)

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

Property Damage

The estimated property damage per crash was most commonly in the $1,500 to $7,500 range, which accounted for 47 incidents. A further 25 crashes resulted in damages between $7,500 and $25,000. High-damage crashes, with estimates exceeding $25,000, occurred in 6 instances, representing 7.4% 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

The dominant crash type was 'Non-collision (single vehicle),' such as running off the road or overturning, which accounted for 47 incidents or 58% of all crashes. The most common type of multi-vehicle crash was 'Rear-end,' with 13 incidents, making up 16% of the total. Broadside collisions were reported in 4 crashes.

Manner of Collision

"Other" combines 3 smaller categories (3 records): Rear to side (1), Angle, oncoming left turn (1), 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

The vast majority of drivers involved in crashes, 70 in total, were engaged in 'Movement essentially straight' just prior to the incident. Far less frequent pre-crash actions included 'Turning right,' reported for 5 drivers, and 'Slowing/stopping,' reported for 4 drivers.

Pre-Crash Driver Action

1
Movement essentially straight70 (72.9%)
2
Turning right5 (5.2%)
3
Slowing/stopping (deceleration)4 (4.2%)
4
Backing3 (3.1%)
5
Stopped in traffic3 (3.1%)
6
Turning left3 (3.1%)
7
Overtaking/passing2 (2.1%)
8
Leaving traffic lane2 (2.1%)
9
Starting in road1 (1%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Legally Parked, Negotiating a curve, Changing lanes.

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

Person Type

Of the 135 individuals involved in crashes, the overwhelming majority, 130 people, were drivers. The remaining 5 individuals were recorded as passengers. No other person types, such as pedestrians or cyclists, were involved in crashes during this period.

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 25 individuals sustained injuries in crashes. Among these, 6 people suffered serious injuries, 8 had minor injuries, and 11 were classified with possible injuries. There were no fatalities recorded among any persons involved in crashes.

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, 15 occupants were reported as using a shoulder and lap belt. In 4 instances, it was noted that no safety equipment was used. This information was not recorded for the majority of participants.

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

A majority of the incidents, 52 crashes or 64.2%, involved only a single vehicle. Two-vehicle collisions accounted for the remaining 29 crashes. No crashes involving three or more vehicles were reported during this period.

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: 81
  • Total persons involved: 135
  • Total vehicles involved: 110

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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