Yearly Traffic Safety Analysis

272 CRASHES IN
IOWA, IA
2015

In 2015, Delaware County recorded 272 traffic crashes, resulting in 2 fatalities and 112 injuries. A significant portion of these incidents were attributed to environmental factors rather than driver error alone. The single most prominent contributing factor was collisions with animals, which accounted for 82 crashes, representing 30.1% of the total for the year.

272

Total Crash Events

2

Persons Killed

112

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, crash data for Delaware County shows that motorists accounted for the majority of individuals killed or injured. One motorist was killed and 111 were injured. Additionally, one pedestrian was killed and one was injured in separate incidents. There were no fatalities or injuries involving cyclists recorded during this period.

1

Pedestrians Killed

1

Motorists Killed

1

Pedestrians Injured

111

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 frequency in Delaware County peaked on Mondays, which saw a total of 48 incidents throughout the year. The most common time for crashes was the 3 p.m. hour, with 21 events recorded. Analysis of lighting conditions shows that 134 crashes, or 49.3% of the total, occurred during daylight hours, while 67 crashes took place in dark, dusk, or dawn conditions.

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 272 total crashes, 213 (78.3%) resulted in no injuries and were classified as property-damage-only. The remaining incidents involved injuries of varying severity, including 4 serious injuries, 29 minor injuries, and 24 possible injuries. There were 2 fatal crashes recorded during the year, which resulted in a total of 2 fatalities.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
Serious Injury4serious injury crashes1.5%
Minor Injury29minor injury crashes10.7%
Possible Injury24possible injury crashes8.8%
No Injury213no injury crashes78.3%

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 leading contributing factor to crashes was animals, cited in 82 incidents, or 30.1% of all crashes. Losing control of the vehicle was the second most common factor, contributing to 33 crashes (12.1%). Running off a straight road was listed as a factor in 21 crashes (7.7%), highlighting a pattern of single-vehicle incidents.

Officer-Reported Primary Contributing Cause

Animal82 (30.1%)
Lost Control33 (12.1%)
Ran off road - straight21 (7.7%)
Other (explain in narrative): Other13 (4.8%)
Followed too close13 (4.8%)
Driving too fast for conditions12 (4.4%)
FTYROW: From stop sign11 (4%)
FTYROW: Making left turn8 (2.9%)
FTYROW: Other (explain in narrative)7 (2.6%)
Driver Distraction: Other interior distraction7 (2.6%)

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 substantial number of crashes occurred in seemingly ideal conditions, with 123 (45.2%) happening in clear weather and 126 (46.3%) on dry road surfaces. Daylight conditions were present for 134 crashes (49.3%). Adverse conditions still played a role, with 15 crashes occurring during rain and 14 in snow, while 25 incidents happened on wet roads and 22 on snow-covered surfaces.

Weather

Clear123 (62.4%)
Cloudy37 (18.8%)
Rain15 (7.6%)
Snow14 (7.1%)
Blowing Snow3 (1.5%)
Fog, smoke, smog3 (1.5%)
Freezing rain/drizzle2 (1.0%)

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

Lighting

Daylight134 (66.7%)
Dark - roadway not lighted41 (20.4%)
Dark - roadway lighted15 (7.5%)
Dusk7 (3.5%)
Dawn4 (2.0%)

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

Road Surface

Dry126 (63.0%)
Wet25 (12.5%)
Snow22 (11.0%)
Gravel16 (8.0%)
Ice/frost10 (5.0%)
Slush1 (0.5%)

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

Vehicles & Demographics

Among the 504 people involved in crashes, the 16-20 age group was the most represented with 89 individuals, followed by the 55-64 age group with 74 individuals. Analysis of the 390 vehicles involved shows that Chevrolet (101), Ford (70), and Dodge (33) were the most frequent makes recorded in crash reports. These top three makes constituted 52% of all vehicles with a specified make.

Top Vehicle Makes (390 vehicles)

1
FORD70 (17.9%)
2
CHEV62 (15.9%)
3
CHEVROLET39 (10%)
4
DODGE19 (4.9%)
5
PONT17 (4.4%)
6
DODG14 (3.6%)
7
BUIC9 (2.3%)
8
TOYOTA9 (2.3%)
9
PONTIAC9 (2.3%)
10
HOND8 (2.1%)

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

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

Sex Distribution (357 persons with recorded sex)

Male221 (61.9%)
Female136 (38.1%)

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

Major Cause

The most frequently cited major cause of crashes was animals, accounting for 82 incidents. The second leading cause was losing control of the vehicle, which was documented in 33 crashes. Running off a straight road contributed to 21 crashes, while following too closely and other unspecified causes were each cited in 13 incidents.

Major Cause

1
Animal82 (30.6%)
2
Lost Control33 (12.3%)
3
Ran off road - straight21 (7.8%)
4
Other (explain in narrative): Other13 (4.9%)
5
Followed too close13 (4.9%)
6
Driving too fast for conditions12 (4.5%)
7
FTYROW: From stop sign11 (4.1%)
8
FTYROW: Making left turn8 (3%)
9
FTYROW: Other (explain in narrative)7 (2.6%)

Showing top 9 of 38 reported. 29 additional (68 total) not shown: Driver Distraction: Other interior distraction, Ran off road - left, FTYROW: From driveway, Improper Backing, Made improper turn, Driver Distraction: Inattentive/lost in thought, Swerving/Evasive Action, FTYROW: From parked position, Ran Stop Sign, FTYROW: From yield sign, Crossed centerline (undivided), Driver Distraction: Manual operation of an electronic communication device, Exceeded authorized speed, Other (explain in narrative): No improper action, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Ran off road - right, Driver Distraction: Exterior distraction, Failed to keep in proper lane, Ran Traffic Signal, Passing: On wrong side, Driver Distraction: Adjusting devices (radio, climate), Equipment failure, Cargo/equipment loss or shift, Driver Distraction: Reaching for object(s)/fallen object(s), Improper or erratic lane changing, Aggressive driving/road rage, FTYROW: At uncontrolled intersection, Operating vehicle in an reckless, erratic, careless, negligent manner.

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

First Harmful Event

The initial event in crashes was most often a collision with an animal, which occurred in 81 cases. This was closely followed by collisions with another vehicle in traffic, recorded in 80 incidents. Non-collision events, primarily overturns or rollovers, were the first harmful event in 32 crashes, while striking a ditch was documented 24 times.

First Harmful Event

1
Collision with: Animal81 (29.8%)
2
Collision with: Vehicle in traffic80 (29.4%)
3
Non-collision events: Overturn/rollover32 (11.8%)
4
Collision with fixed object: Ditch24 (8.8%)
5
Collision with: Parked motor vehicle10 (3.7%)
6
Collision with: Re-entering roadway7 (2.6%)
7
Collision with: Struck/struck by object/cargo/person from other vehicle5 (1.8%)
8
Collision with fixed object: Tree4 (1.5%)
9
Other (explain in narrative)3 (1.1%)

Showing top 9 of 28 reported. 19 additional (26 total) not shown: Collision with fixed object: Traffic sign support, Miscellaneous events: Hit and run, Collision with: Other non-fixed object (explain in narrative), Non-collision events: Other non-collision (explain in narrative), Collision with: Non-motorist (see non-motorist section - NOT a unit), Collision with fixed object: Other post/pole/support (explain in narrative), Collision with: Railway vehicle/train, Collision with fixed object: Fence, Collision with fixed object: Embankment, Collision with: Thrown or falling object, Collision with fixed object: Curb/island/raised median, Miscellaneous events: Fire/explosion, Non-collision events: Jackknife, Collision with fixed object: Building, Collision with fixed object: Guardrail - face, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Ground, Collision with fixed object: Utility pole/light support, Collision with fixed object: Fire hydrant.

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

Roadway Junction / Feature

The majority of crashes occurred on non-intersection roadway segments, with 119 incidents specifically noted as happening at a non-junction or area with no special features. In contrast, 29 crashes occurred at four-way intersections and 24 at T-intersections. Overall, crashes at or related to intersections accounted for at least 60 incidents, while non-intersection events accounted for at least 140.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature119 (59.5%)
2
Intersection: Four-way intersection29 (14.5%)
3
Intersection: T-intersection24 (12%)
4
Non-intersection: Driveway access (related, not in)12 (6%)
5
Non-intersection: Driveway access (within)5 (2.5%)
6
Intersection: Other intersection (explain in narrative)4 (2%)
7
Non-intersection: Railroad grade crossing1 (0.5%)
8
Intersection: Intersection with ramp1 (0.5%)
9
Intersection: L-intersection1 (0.5%)

Showing top 9 of 13 reported. 4 additional (4 total) not shown: Intersection: Y-intersection, Non-intersection: Alley, 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 162 units documented. Light trucks and pickups were the second most frequent with 78 vehicles, followed closely by sport utility vehicles with 76. Tractor/semi-trailers were involved in 12 incidents, and motorcycles were involved in 8.

Vehicle Type

"Other" combines 8 smaller categories (19 records): Cargo/panel van (4), School bus (seats > 15) (4), Single unit truck (2-axle, 6-tire) (4), Farm tractor (2), Farm equipment (explain in narrative) (2), Other (explain in narrative) (1), Passenger van (seats 9-15) (1), Train (1).

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

Traffic Control Device

A significant majority of crashes, 243 out of 272, occurred in areas where no traffic controls were present. For crashes where traffic controls were a factor, stop signs were the most common device, present in 44 incidents. Traffic signals were present at the location of 11 crashes.

Traffic Control Device

"Other" combines 1 smaller categories (3 records): Flashing traffic control signal (3).

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, with the primary damage being to the front of the vehicle in 85 cases and to the front corners in an additional 50 cases. This pattern is consistent with head-on collisions, rear-end collisions, and striking objects like animals. Damage to the rear was the most severe in 30 vehicles, while side damage was most prominent in 48 vehicles.

Most Damaged Area

"Other" combines 9 smaller categories (74 records): Driver side - front (16), Passenger side - rear (14), Driver side - rear (10), Passenger side - front (10), Rear - driver side corner (9), Rear - passenger side corner (6), Other (explain in narrative) (5), Non-collision/no damage (2), Undercarriage (2).

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

Crashes by City

Of the crashes occurring within city limits, Manchester reported the highest volume with 79 incidents. Dyersville recorded the second-highest number with 13 crashes. Following these were Delhi with 6 crashes and Earlville with 4 crashes.

Crashes by City

1
MANCHESTER79 (75.2%)
2
DYERSVILLE13 (12.4%)
3
DELHI6 (5.7%)
4
EARLVILLE4 (3.8%)
5
DELAWARE2 (1.9%)
6
EDGEWOOD1 (1%)

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, 238 out of 272, occurred on paved roadways. However, a notable portion, 34 crashes or 12.5% of the total, took place on unpaved surfaces such as gravel or dirt roads, reflecting the county's rural road network.

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-related factors were cited as a contributor in a minority of crashes. The most common factor was the surface condition, such as wet or icy roads, which was noted in 25 incidents. An obstruction in the roadway and a slippery or worn surface were each cited as a factor in one crash.

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)25 (92.6%)
2
Obstruction in roadway1 (3.7%)
3
Slippery, loose or worn surface1 (3.7%)

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

Driver Condition

Among drivers whose condition was noted as something other than 'apparently normal', being under the influence of alcohol was the most frequent, recorded for 9 drivers. Additionally, 3 drivers were noted as being asleep or fatigued, and 2 experienced a medical condition. These figures represent a small subset of the 454 drivers involved in crashes.

Driver Condition

1
Under the influence of alcohol9 (64.3%)
2
Asleep/fatigued3 (21.4%)
3
Medical condition (seizure, reaction)2 (14.3%)

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

Property Damage

The most common estimated cost of property damage fell within the $1,500 to $7,500 range, which was assigned to 209 crashes. A smaller number of crashes, 56, resulted in damages estimated between $7,500 and $25,000. Only 5 crashes were estimated to have damage costs exceeding $25,000.

Property Damage

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

Manner of Collision

Nearly half of all incidents, 131 crashes or 48.2%, were non-collision events involving a single vehicle. Among multi-vehicle crashes, the most common types were rear-end collisions, with 28 incidents (10.3%), and broadside collisions, with 27 incidents (9.9%).

Manner of Collision

"Other" combines 2 smaller categories (10 records): Sideswipe, opposite direction (7), Head-on (front to front) (3).

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

Pre-Crash Driver Action

Prior to impact, the most common action for the 390 vehicles involved was moving essentially straight, which was the case for 212 vehicles. Turning left was the pre-crash action for 31 vehicles, while 19 vehicles were legally parked at the time of the incident. Another 18 vehicles were in the process of backing.

Pre-Crash Driver Action

1
Movement essentially straight212 (63.1%)
2
Turning left31 (9.2%)
3
Legally Parked19 (5.7%)
4
Backing18 (5.4%)
5
Turning right15 (4.5%)
6
Stopped in traffic11 (3.3%)
7
Slowing/stopping (deceleration)10 (3%)
8
Negotiating a curve6 (1.8%)
9
Other (explain in narrative)4 (1.2%)

Showing top 9 of 16 reported. 7 additional (10 total) not shown: Entering traffic lane (merging), Making U-turn, Overtaking/passing, Leaving a parked position, Illegally Parked/Unattended, Changing lanes, Accelerating in road.

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

Person Type

Of the 504 individuals involved in crashes, the vast majority, 454 people or 90.1%, were drivers. Passengers accounted for 48 of the individuals, representing 9.5% of the total. A small number of pedestrians were also involved, making up 2 of the recorded persons.

Person Type

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

Person Injury Severity

Out of 504 people involved in crashes, 114 sustained some level of injury or were fatally wounded. This includes 2 fatalities, 4 serious injuries, 68 minor injuries, and 40 possible injuries. The total number of injured persons was 112.

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 87 individuals for whom safety equipment usage was documented, 49 were reported as using a shoulder and lap belt. However, a notable 36 individuals were recorded as using no safety equipment at all. Two 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

Single-vehicle crashes were the most common type of incident, accounting for 163 of the 272 total crashes (59.9%). Two-vehicle collisions were the next most frequent, with 102 incidents. A small number of crashes involved more than two vehicles, including six 3-vehicle crashes and one 5-vehicle crash.

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: 272
  • Total persons involved: 504
  • Total vehicles involved: 390

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