Yearly Traffic Safety Analysis

126 CRASHES IN
IOWA, IA
2015

In 2015, Shelby County recorded 126 traffic crashes, resulting in 3 fatalities and 61 injuries. A significant portion of these incidents, 38.9%, were single-vehicle, non-collision events. The leading contributing factors cited were animal involvement and loss of control, each accounting for 10.3% of crashes.

126

Total Crash Events

3

Persons Killed

61

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, motorists accounted for all 3 fatalities and the vast majority of injuries, with 60 motorists injured. No cyclists were killed or injured during this period. One pedestrian was reported injured, but there were no pedestrian fatalities.

0

Pedestrians Killed

3

Motorists Killed

1

Pedestrians Injured

60

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 Shelby County during 2015 occurred most frequently on Thursdays, which saw 22 incidents. The single busiest hour for crashes was 4 p.m., with 11 events recorded. Analysis of lighting conditions shows that a majority of crashes, 82 out of 126, happened 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

Of the 126 crashes in 2015, 60.3% (76 crashes) resulted in no injuries. The remaining incidents involved injuries of varying severity, including 26 with possible injuries, 14 with minor injuries, and 8 with serious injuries. There were 2 fatal crashes, which resulted in a total of 3 fatalities.

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

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.6%
Serious Injury8serious injury crashes6.3%
Minor Injury14minor injury crashes11.1%
Possible Injury26possible injury crashes20.6%
No Injury76no injury crashes60.3%

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 factors identified in Shelby County crashes were animal involvement and loss of control, with each cited in 13 incidents (10.3% of the total). Following these, failure to yield the right-of-way from a stop sign and driving too fast for conditions were each noted in 10 crashes (7.9%). Running off a straight road was another significant factor, accounting for 9 crashes.

Officer-Reported Primary Contributing Cause

Animal13 (10.3%)
Lost Control13 (10.3%)
FTYROW: From stop sign10 (7.9%)
Driving too fast for conditions10 (7.9%)
Ran off road - straight9 (7.1%)
Other (explain in narrative): Other7 (5.6%)
Followed too close6 (4.8%)
Ran off road - left5 (4%)
Ran Stop Sign5 (4%)
Driver Distraction: Other interior distraction4 (3.2%)

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 in 2015 occurred in favorable conditions, with 65.1% happening in daylight and 54.0% in clear weather. Similarly, 51.6% of crashes took place on dry road surfaces. Adverse weather was a factor in a smaller number of incidents, including 8 crashes in rain and 7 in snow, while wet road surfaces were present in 19 crashes.

Weather

Clear68 (61.3%)
Cloudy21 (18.9%)
Rain8 (7.2%)
Snow7 (6.3%)
Freezing rain/drizzle5 (4.5%)
Fog, smoke, smog1 (0.9%)
Blowing Snow1 (0.9%)

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

Lighting

Daylight82 (70.1%)
Dark - roadway not lighted17 (14.5%)
Dark - roadway lighted11 (9.4%)
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

Dry65 (56.5%)
Wet19 (16.5%)
Gravel11 (9.6%)
Ice/frost9 (7.8%)
Snow8 (7.0%)
Other (explain in narrative)2 (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 42 individuals, closely followed by the 16-20 age group with 41 individuals. Among the 204 vehicles involved, Ford was the most frequent make with 51 vehicles. Chevrolet vehicles accounted for 41 vehicles, and Dodge vehicles were involved in 20 crashes.

Top Vehicle Makes (204 vehicles)

1
FORD51 (25%)
2
CHEV27 (13.2%)
3
CHEVROLET14 (6.9%)
4
DODG14 (6.9%)
5
BUIC8 (3.9%)
6
PONT7 (3.4%)
7
GMC6 (2.9%)
8
DODGE6 (2.9%)
9
JEEP5 (2.5%)
10
CHRY4 (2%)

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

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

Sex Distribution (187 persons with recorded sex)

Male112 (59.9%)
Female75 (40.1%)

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

Major Cause

The leading major causes of crashes in Shelby County were animal encounters and loss of control, each contributing to 13 incidents. Failure to yield right-of-way from a stop sign and driving too fast for conditions were also significant, each cited as the major cause in 10 crashes. Running off a straight road was the primary cause in another 9 crashes.

Major Cause

1
Animal13 (10.7%)
2
Lost Control13 (10.7%)
3
FTYROW: From stop sign10 (8.2%)
4
Driving too fast for conditions10 (8.2%)
5
Ran off road - straight9 (7.4%)
6
Other (explain in narrative): Other7 (5.7%)
7
Followed too close6 (4.9%)
8
Ran off road - left5 (4.1%)
9
Ran Stop Sign5 (4.1%)

Showing top 9 of 32 reported. 23 additional (44 total) not shown: Driver Distraction: Other interior distraction, FTYROW: From driveway, Swerving/Evasive Action, Exceeded authorized speed, Made improper turn, Operating vehicle in an reckless, erratic, careless, negligent manner, Passing: Other passing (explain in narrative), FTYROW: Other (explain in narrative), Improper or erratic lane changing, FTYROW: Making left turn, Other (explain in narrative): Vision obstructed, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Exterior distraction, Crossed centerline (undivided), Cargo/equipment loss or shift, FTYROW: From parked position, Traveling wrong way or on wrong side of road, Equipment failure, Improper Backing, Driver Distraction: Reaching for object(s)/fallen object(s), Operator inexperience, Other (explain in narrative): No improper action, Driver Distraction: Passenger.

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, which occurred in 59 of the 126 crashes (46.8%). Collisions with fixed objects were also common, with hitting a ditch being the most prevalent event in this category, accounting for 21 crashes. Collisions with animals were recorded as the first harmful event in 13 incidents.

First Harmful Event

1
Collision with: Vehicle in traffic59 (47.2%)
2
Collision with fixed object: Ditch21 (16.8%)
3
Collision with: Animal13 (10.4%)
4
Other (explain in narrative)10 (8%)
5
Non-collision events: Overturn/rollover4 (3.2%)
6
Non-collision events: Other non-collision (explain in narrative)2 (1.6%)
7
Collision with fixed object: Utility pole/light support2 (1.6%)
8
Collision with fixed object: Other post/pole/support (explain in narrative)1 (0.8%)
9
Collision with fixed object: Traffic sign support1 (0.8%)

Showing top 9 of 21 reported. 12 additional (12 total) not shown: Collision with fixed object: Tree, Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with: Re-entering roadway, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Building, Miscellaneous events: Hit and run, Miscellaneous events: Vehicle out of gear/rolled, Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Embankment, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Ground, Collision with fixed object: Mailbox.

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

Roadway Junction / Feature

Over half of the crashes, 66 out of 126 (52.4%), occurred at non-junction locations along a road segment. Intersections were the site of 37 crashes, with four-way intersections being the most common type, accounting for 22 of these incidents. An additional 11 crashes happened at T-intersections.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature66 (57.4%)
2
Intersection: Four-way intersection22 (19.1%)
3
Intersection: T-intersection11 (9.6%)
4
Non-intersection: Driveway access (within)6 (5.2%)
5
Intersection: Other intersection (explain in narrative)3 (2.6%)
6
Non-intersection: Alley2 (1.7%)
7
Non-intersection: Driveway access (related, not in)2 (1.7%)
8
Non-intersection: Other non-intersection (explain in narrative)1 (0.9%)
9
Non-intersection: Crossover-related1 (0.9%)

Showing top 9 of 10 reported. 1 additional (1 total) not shown: Intersection: L-intersection.

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 71 of the 204 vehicles. Sport utility vehicles and four-tire light trucks were also frequently involved, with 47 of each type recorded. Commercial vehicles like tractor-trailers were involved in 5 crashes, and motorcycles were involved in 3 crashes.

Vehicle Type

"Other" combines 7 smaller categories (9 records): Cargo/panel van (2), Farm equipment (explain in narrative) (2), Other (explain in narrative) (1), School bus (seats > 15) (1), Single-unit truck (>= 3 axles) (1), Snowmobile (1), Truck/trailer (1).

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

Traffic Control Device

For the majority of vehicles involved in crashes, no traffic controls were present; this was the case for 156 of the 204 vehicles. Stop signs were the most common form of traffic control device noted, being relevant to 32 vehicles involved in collisions. Traffic signals were a factor for only 2 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 common area of impact, recorded as the most damaged area for 43 vehicles. Various types of side and corner impacts were also frequent, including 19 vehicles with primary damage to the driver-side front and 18 to the front-passenger-side corner. Rear-end impacts, where the rear was the most damaged area, were noted for 15 vehicles.

Most Damaged Area

"Other" combines 8 smaller categories (48 records): Passenger side - middle (10), Driver side - rear (10), Top (9), Passenger side - rear (6), Rear - passenger side corner (5), Other (explain in narrative) (3), Rear - driver side corner (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 distribution within Shelby County was concentrated in Harlan, which recorded 60 of the incidents. The town of Shelby had the next highest volume with 5 crashes. Other municipalities, including Earling and Elk Horn, each accounted for 2 crashes, while Defiance and Portsmouth each had one.

Crashes by City

1
HARLAN60 (84.5%)
2
SHELBY5 (7%)
3
EARLING2 (2.8%)
4
ELK HORN2 (2.8%)
5
DEFIANCE1 (1.4%)
6
PORTSMOUTH1 (1.4%)

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

Paved vs Unpaved Road

Analysis of the road surface type shows that 104 crashes (82.5%) occurred on paved roads. A notable portion, 22 crashes or 17.5% of the total, took place on unpaved surfaces such as gravel or dirt roads. This reflects the presence of a significant secondary road network within the county.

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 the road surface condition, such as being wet or icy, which was noted in 20 incidents. A slippery, loose, or worn surface was identified as a contributing factor in 5 additional crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)20 (76.9%)
2
Slippery, loose or worn surface5 (19.2%)
3
Traffic backup, prior non-recurring incident1 (3.8%)

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, being under the influence of alcohol was the most frequent, noted for 7 drivers. Driver fatigue or falling asleep was the next most common condition, contributing to 4 incidents. Other recorded conditions included emotional state, illness, and medical issues, each noted once.

Driver Condition

1
Under the influence of alcohol7 (50%)
2
Asleep/fatigued4 (28.6%)
3
Emotional (e.g. depressed, angry)1 (7.1%)
4
Illness/fainted1 (7.1%)
5
Medical condition (seizure, reaction)1 (7.1%)

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

Property Damage

Officer-estimated property damage was most commonly in the $1,500 to $7,500 range, which applied to 79 crashes. A significant number of incidents, 41, resulted in damages estimated between $7,500 and $25,000. High-damage crashes, with costs exceeding $25,000, accounted for 4 incidents, or 3.2% 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

The most frequent type of incident was a non-collision single-vehicle crash, such as running off the road or an overturn, which accounted for 49 crashes or 38.9% of the total. Among multi-vehicle crashes, broadside collisions were the most common, with 27 incidents (21.4%). Rear-end collisions were the third most frequent manner of collision, occurring 19 times.

Manner of Collision

"Other" combines 2 smaller categories (3 records): Angle, oncoming left turn (2), 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 vehicles involved in crashes, 134 out of 204, were moving essentially straight just prior to the collision. Turning maneuvers were the next most common pre-crash actions, with 19 vehicles turning left and 10 vehicles turning right. A notable 11 vehicles were legally parked when they were involved in a crash.

Pre-Crash Driver Action

1
Movement essentially straight134 (69.1%)
2
Turning left19 (9.8%)
3
Legally Parked11 (5.7%)
4
Turning right10 (5.2%)
5
Other (explain in narrative)6 (3.1%)
6
Backing4 (2.1%)
7
Changing lanes4 (2.1%)
8
Stopped in traffic2 (1%)
9
Negotiating a curve1 (0.5%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Overtaking/passing, Leaving traffic lane, Entering traffic lane (merging).

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

Person Type

Of the 270 individuals involved in crashes, the overwhelming majority, 254 people (94.1%), were drivers. Passengers accounted for another 15 individuals involved in these incidents. A single pedestrian was also recorded as being involved in a crash 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

Across all 270 people involved in crashes, 3 individuals sustained fatal injuries and 61 sustained non-fatal injuries. This means approximately 24% of all persons involved were either injured or killed. The non-fatal injuries included 9 serious injuries, 17 minor injuries, and 35 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

Among the 52 vehicle occupants for whom safety equipment use was specified, 38 were using a shoulder and lap belt. However, 12 individuals, representing 23% of this specific group, were recorded as using no safety equipment at all. This data represents only a subset of all occupants involved in crashes.

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

The most common scenario was a two-vehicle crash, which accounted for 66 of the 126 total incidents (52.4%). Single-vehicle crashes were also frequent, comprising 54 incidents or 42.9% of the total. A smaller number of crashes, 6 in total, involved three 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: 126
  • Total persons involved: 270
  • Total vehicles involved: 204

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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Shelby County, IA Crash Report — 2015 | ThatCarHitMe.com