Yearly Traffic Safety Analysis

180 CRASHES IN
IOWA, IA
2015

In 2015, Page County recorded 180 traffic crashes, which resulted in 1 fatality and 57 injuries. A significant finding from the data is that incidents involving animals were the single most common contributing factor, accounting for 27 crashes, or 15% of the total.

180

Total Crash Events

1

Persons Killed

57

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, vehicle occupants accounted for the single fatality and the vast majority of injuries. One motorist was killed and 55 were injured. Additionally, one pedestrian and one cyclist sustained injuries, though no fatalities were recorded for these groups.

0

Pedestrians Killed

0

Cyclists Killed

1

Motorists Killed

1

Pedestrians Injured

1

Cyclists Injured

55

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 Page County during 2015 were most frequent on Saturdays, with 36 incidents recorded. The single most common time for crashes was the 5 p.m. hour, which saw 18 incidents. A majority of crashes, 114 out of 180, 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 majority of crashes, 132 out of 180 (73.3%), resulted in no injuries and were property-damage-only events. Crashes involving an injury accounted for 26.1% of the total, distributed among serious (5 crashes), minor (16 crashes), and possible injuries (26 crashes). There was one fatal crash recorded in 2015, which resulted in one person's death.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury5serious injury crashes2.8%
Minor Injury16minor injury crashes8.9%
Possible Injury26possible injury crashes14.4%
No Injury132no injury crashes73.3%

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 frequently cited contributing factor in Page County crashes was an animal, involved in 27 incidents (15%). This was followed by failure to yield the right-of-way from a stop sign, which contributed to 16 crashes (8.9%). Losing control of the vehicle was cited as a factor in 13 crashes (7.2%).

Officer-Reported Primary Contributing Cause

Animal27 (15%)
FTYROW: From stop sign16 (8.9%)
Lost Control13 (7.2%)
FTYROW: Making left turn10 (5.6%)
Operating vehicle in an reckless, erratic, careless, negligent manner9 (5%)
Other (explain in narrative): Other9 (5%)
Followed too close8 (4.4%)
Ran Stop Sign7 (3.9%)
FTYROW: At uncontrolled intersection6 (3.3%)
Ran off road - straight5 (2.8%)

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 under favorable conditions, with 66.1% on dry roads (119 crashes) and 63.3% in daylight (114 crashes). Clear weather was reported for 101 crashes (56.1%). Crashes in adverse weather were less frequent, with 7 incidents occurring in rain and 4 in snow.

Weather

Clear101 (64.3%)
Cloudy43 (27.4%)
Rain7 (4.5%)
Snow4 (2.5%)
Freezing rain/drizzle1 (0.6%)
Severe Winds1 (0.6%)

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

Lighting

Daylight114 (72.6%)
Dark - roadway not lighted22 (14.0%)
Dark - roadway lighted11 (7.0%)
Dusk6 (3.8%)
Dawn3 (1.9%)
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry119 (75.8%)
Wet18 (11.5%)
Snow8 (5.1%)
Gravel7 (4.5%)
Ice/frost3 (1.9%)
Mud, dirt2 (1.3%)

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 most represented age group was 65 and older, with 54 individuals. Among the 299 vehicles involved, the most common makes were Chevrolet (a combined 70 vehicles across 'CHEV' and 'CHEVROLET' entries), Ford (56 vehicles), and Dodge (a combined 39 vehicles across 'DODG' and 'DODGE' entries).

Top Vehicle Makes (299 vehicles)

1
FORD56 (18.7%)
2
CHEV41 (13.7%)
3
CHEVROLET29 (9.7%)
4
DODGE20 (6.7%)
5
DODG19 (6.4%)
6
JEEP12 (4%)
7
BUIC12 (4%)
8
BUICK7 (2.3%)
9
NISS7 (2.3%)
10
GMC7 (2.3%)

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

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

Sex Distribution (257 persons with recorded sex)

Male140 (54.5%)
Female117 (45.5%)

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 cause attributed to crashes was 'Animal,' cited in 27 incidents. Failure to yield the right-of-way was also a significant factor, with 16 cases occurring at a stop sign and 10 cases involving a left turn. 'Lost Control' was listed as the cause for 13 crashes.

Major Cause

1
Animal27 (16.1%)
2
FTYROW: From stop sign16 (9.5%)
3
Lost Control13 (7.7%)
4
FTYROW: Making left turn10 (6%)
5
Operating vehicle in an reckless, erratic, careless, negligent manner9 (5.4%)
6
Other (explain in narrative): Other9 (5.4%)
7
Followed too close8 (4.8%)
8
Ran Stop Sign7 (4.2%)
9
FTYROW: At uncontrolled intersection6 (3.6%)

Showing top 9 of 35 reported. 26 additional (63 total) not shown: Ran off road - straight, Driver Distraction: Other interior distraction, Swerving/Evasive Action, Improper Backing, FTYROW: From yield sign, FTYROW: From parked position, Driver Distraction: Exterior distraction, Driving too fast for conditions, Driver Distraction: Inattentive/lost in thought, Ran off road - left, Driver Distraction: Talking on a hand-held device, FTYROW: Other (explain in narrative), FTYROW: From driveway, Driver Distraction: Adjusting devices (radio, climate), Made improper turn, Downhill runaway, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Passenger, Driver Distraction: Reaching for object(s)/fallen object(s), Equipment failure, FTYROW: To pedestrian, Improper or erratic lane changing, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed, Ran off road - right, Ran Traffic Signal.

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 97 crashes. The second most common event was a collision with an animal, accounting for 27 incidents. Collisions with a fixed object were also notable, including 14 crashes where the first harmful event was hitting a ditch.

First Harmful Event

1
Collision with: Vehicle in traffic97 (54.5%)
2
Collision with: Animal27 (15.2%)
3
Collision with fixed object: Ditch14 (7.9%)
4
Collision with: Re-entering roadway7 (3.9%)
5
Collision with: Parked motor vehicle5 (2.8%)
6
Non-collision events: Overturn/rollover5 (2.8%)
7
Collision with: Non-motorist (see non-motorist section - NOT a unit)2 (1.1%)
8
Collision with fixed object: Embankment2 (1.1%)
9
Other (explain in narrative)2 (1.1%)

Showing top 9 of 24 reported. 15 additional (17 total) not shown: Non-collision events: Other non-collision (explain in narrative), Collision with fixed object: Utility pole/light support, Miscellaneous events: Eluding law enforcement, Miscellaneous events: Hit and run, Miscellaneous events: Immersion, Miscellaneous events: Vehicle out of gear/rolled, Non-collision events: Non-contact vehicle (phantom), Non-collision events: Vehicle went airborne, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Mailbox, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Traffic sign support, Collision with: Other non-fixed object (explain in narrative), Collision with: Thrown or falling object, Collision with fixed object: Fence.

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

Roadway Junction / Feature

Crashes were more common on non-intersection road segments, with 75 incidents occurring at a 'Non-junction/no special feature'. In contrast, 67 crashes occurred at intersections, with four-way intersections being the most common type, accounting for 50 of these incidents.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature75 (47.8%)
2
Intersection: Four-way intersection50 (31.8%)
3
Intersection: T-intersection9 (5.7%)
4
Non-intersection: Other non-intersection (explain in narrative)5 (3.2%)
5
Non-intersection: Driveway access (related, not in)4 (2.5%)
6
Non-intersection: Driveway access (within)4 (2.5%)
7
Intersection: Other intersection (explain in narrative)3 (1.9%)
8
Intersection: Y-intersection3 (1.9%)
9
Intersection: Five points or more2 (1.3%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Non-intersection: Alley, Non-intersection: Railroad grade crossing.

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

Vehicle Type

Passenger cars were the most prevalent vehicle type involved in crashes, accounting for 143 vehicles. Light trucks and pickups were the second most common with 66 vehicles, followed by Sport Utility Vehicles with 54. Motorcycles were involved in 6 crashes, and tractor/semi-trailers were involved in 3.

Vehicle Type

"Other" combines 6 smaller categories (9 records): Single unit truck (2-axle, 6-tire) (3), Motor home/recreational vehicle (2), Farm tractor (1), School bus (seats > 15) (1), Single-unit truck (>= 3 axles) (1), Truck tractor (bobtail) (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 locations with no traffic controls present, a situation recorded for 193 vehicles. For crashes at controlled locations, stop signs were the most common device, present for 47 vehicles involved in crashes. Traffic signals were noted for 11 vehicles.

Traffic Control Device

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

Most Damaged Area

Frontal impacts were the most common type of vehicle damage, with 77 vehicles sustaining damage to the front center and a combined 60 vehicles damaged on the front corners. Rear impacts, indicative of rear-end collisions, were recorded for 25 vehicles. Damage to the side of the vehicle was also frequent, noted in various forms on 79 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (58 records): Rear - driver side corner (11), Passenger side - rear (11), Driver side - rear (10), Rear - passenger side corner (9), Driver side - front (8), Top (5), Non-collision/no damage (2), Undercarriage (1), Other (explain in narrative) (1).

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

Crashes by City

The majority of crashes within municipal limits occurred in the county's two largest cities. Shenandoah recorded 58 crashes, and Clarinda recorded 52. Smaller towns such as Yorktown, Essex, and Hepburn each reported 3 crashes.

Crashes by City

1
SHENANDOAH58 (47.2%)
2
CLARINDA52 (42.3%)
3
YORKTOWN3 (2.4%)
4
ESSEX3 (2.4%)
5
HEPBURN3 (2.4%)
6
SHAMBAUGH2 (1.6%)
7
NORTHBORO1 (0.8%)
8
BRADDYVILLE1 (0.8%)

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, 159 out of 180, occurred on paved roadways. A notable portion, 21 crashes or 11.7% 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, specific roadway factors were noted as contributors. The most cited factor was 'Surface condition (e.g. wet, icy),' which was a factor in 11 crashes. Other noted factors included 'Slippery, loose or worn surface' in 3 crashes and 'Ruts/holes/bumps' in 2 crashes.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)11 (64.7%)
2
Slippery, loose or worn surface3 (17.6%)
3
Ruts/holes/bumps2 (11.8%)
4
Shoulders (none, low, soft, high)1 (5.9%)

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

Driver Condition

In cases where a driver's condition was recorded as something other than 'apparently normal,' the most common factor was being asleep or fatigued, noted for 5 drivers. Emotional distress was cited for 3 drivers, and being under the influence of alcohol was also recorded for 3 drivers.

Driver Condition

1
Asleep/fatigued5 (41.7%)
2
Emotional (e.g. depressed, angry)3 (25%)
3
Under the influence of alcohol3 (25%)
4
Paraplegic/wheelchair restricted1 (8.3%)

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

Property Damage

The estimated property damage for most crashes fell into the '$1,500 - $7,500' range, which applied to 125 incidents. A smaller number of crashes, 45, resulted in damage estimated between $7,500 and $25,000. High-damage crashes, those exceeding $25,000, accounted for 4 incidents.

Property Damage

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

Manner of Collision

The most common type of crash was a non-collision event involving a single vehicle, such as running off the road, which accounted for 65 incidents or 36.1% of the total. Among multi-vehicle crashes, broadside collisions were most frequent with 44 incidents (24.4%), followed by rear-end collisions with 30 incidents (16.7%).

Manner of Collision

"Other" combines 3 smaller categories (11 records): Sideswipe, opposite direction (5), Other (explain in narrative) (5), 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 driver actions prior to a crash shows that the vast majority of vehicles, 187 out of 299, were moving essentially straight. The next most common pre-crash actions were turning left, reported for 27 vehicles, and being legally parked, reported for 22 vehicles.

Pre-Crash Driver Action

1
Movement essentially straight187 (64.3%)
2
Turning left27 (9.3%)
3
Legally Parked22 (7.6%)
4
Backing14 (4.8%)
5
Other (explain in narrative)11 (3.8%)
6
Turning right9 (3.1%)
7
Stopped in traffic7 (2.4%)
8
Negotiating a curve3 (1%)
9
Entering traffic lane (merging)3 (1%)

Showing top 9 of 15 reported. 6 additional (8 total) not shown: Starting in road, Changing lanes, Accelerating in road, Leaving traffic lane, Leaving a parked position, Slowing/stopping (deceleration).

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 vast majority, 341 people, were drivers. Passengers accounted for 17 individuals, while one pedestrian and one bicyclist were also involved in incidents over the year.

Person Type

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

Person Injury Severity

Among the 360 people involved in crashes, a total of 58 sustained some level of injury or were killed. This includes one fatality, 7 serious injuries, 17 minor injuries, and 33 possible injuries. This represents 16.1% of all persons involved.

Person Injury Severity

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

Occupant Safety Equipment

In the subset of crash reports where safety equipment use was specified, 29 individuals were recorded as using a shoulder and lap belt. Notably, 9 individuals were recorded as using no restraints. Additionally, 2 participants were noted as wearing 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

The most common crash configuration involved two vehicles, which occurred in 109 incidents. Single-vehicle crashes were also frequent, accounting for 66 incidents, or 36.7% of the total. A small number of crashes, 5, 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: 180
  • Total persons involved: 360
  • Total vehicles involved: 299

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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