Yearly Traffic Safety Analysis

256 CRASHES IN
IOWA, IA
2015

In 2015, Jefferson County recorded 256 traffic crashes, resulting in 1 fatality and 79 injuries. A significant portion of these incidents were attributed to collisions with animals, which was the primary contributing factor in 81 crashes, representing 31.6% of the total. The single fatality was a pedestrian.

256

Total Crash Events

1

Persons Killed

79

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

The single fatality recorded in 2015 was a pedestrian. In addition to this fatality, 79 individuals were injured. The injured parties included 77 motorists and 2 cyclists. No cyclists or motorists were killed in this period.

1

Pedestrians Killed

0

Cyclists Killed

0

Motorists Killed

0

Pedestrians Injured

2

Cyclists Injured

77

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 Jefferson County during this period occurred most frequently on Mondays, which saw a total of 55 incidents. The afternoon commute hour of 5 p.m. was the peak time for crashes, with 23 recorded events. Overall, a majority of crashes happened during daylight hours, accounting for 140 of the 256 total incidents.

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, 195 out of 256 (76.2%), resulted in no injuries and were classified as property-damage-only. Crashes involving injuries or a fatality accounted for the remaining 23.8% of incidents. There was one fatal crash recorded during this period, which resulted in one person being killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
Serious Injury8serious injury crashes3.1%
Minor Injury26minor injury crashes10.2%
Possible Injury26possible injury crashes10.2%
No Injury195no injury crashes76.2%

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 prevalent contributing factor cited in crashes was 'Animal,' accounting for 81 incidents or 31.6% of all crashes. 'Lost Control' was the second-leading factor, cited in 27 crashes (10.5%). Other significant factors included 'Failure to yield right of way from a stop sign' with 15 crashes (5.9%) and 'Followed too close' with 14 crashes (5.5%).

Officer-Reported Primary Contributing Cause

Animal81 (31.6%)
Lost Control27 (10.5%)
FTYROW: From stop sign15 (5.9%)
Followed too close14 (5.5%)
Ran Stop Sign12 (4.7%)
Ran off road - left11 (4.3%)
Driving too fast for conditions10 (3.9%)
Other (explain in narrative): Other10 (3.9%)
Ran off road - straight9 (3.5%)
FTYROW: From yield sign5 (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

A majority of crashes occurred in favorable conditions. Daylight was the lighting condition for 140 crashes (54.7%), while roads were reported as dry for 135 crashes (52.7%) and weather was clear for 122 crashes (47.6%). Adverse conditions included 13 crashes in snow, 11 in rain, and 27 on dark, unlighted roadways.

Weather

Clear122 (65.2%)
Cloudy32 (17.1%)
Snow13 (7.0%)
Rain11 (5.9%)
Fog, smoke, smog5 (2.7%)
Freezing rain/drizzle2 (1.1%)
Sleet, hail1 (0.5%)
Blowing sand, soil, dirt1 (0.5%)

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

Lighting

Daylight140 (74.1%)
Dark - roadway not lighted27 (14.3%)
Dark - roadway lighted11 (5.8%)
Dusk6 (3.2%)
Dawn5 (2.6%)

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

Road Surface

Dry135 (71.8%)
Wet20 (10.6%)
Snow18 (9.6%)
Gravel7 (3.7%)
Ice/frost3 (1.6%)
Slush3 (1.6%)
Other (explain in narrative)2 (1.1%)

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

Vehicles & Demographics

Among the 446 people involved in crashes, the most represented age groups were 26-34 and 65+, each with 75 individuals. The most common vehicle makes involved were Ford (58 vehicles), Chevrolet (combining 'CHEV' and 'CHEVROLET' for 69 vehicles), and Dodge (combining 'DODG' and 'DODGE' for 45 vehicles).

Top Vehicle Makes (366 vehicles)

1
FORD58 (15.8%)
2
CHEV35 (9.6%)
3
CHEVROLET34 (9.3%)
4
DODG26 (7.1%)
5
TOYT25 (6.8%)
6
DODGE19 (5.2%)
7
GMC16 (4.4%)
8
TOYOTA14 (3.8%)
9
BUIC10 (2.7%)
10
KIA9 (2.5%)

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

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

Sex Distribution (339 persons with recorded sex)

Male194 (57.2%)
Female145 (42.8%)

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 identified for crashes was 'Animal,' which was cited in 81 incidents. 'Lost Control' was the second most common cause with 27 crashes, followed by 'Failure to yield right of way from a stop sign' with 15 crashes. 'Followed too close' (14 crashes) and 'Ran Stop Sign' (12 crashes) were also frequently cited.

Major Cause

1
Animal81 (33.1%)
2
Lost Control27 (11%)
3
FTYROW: From stop sign15 (6.1%)
4
Followed too close14 (5.7%)
5
Ran Stop Sign12 (4.9%)
6
Ran off road - left11 (4.5%)
7
Driving too fast for conditions10 (4.1%)
8
Other (explain in narrative): Other10 (4.1%)
9
Ran off road - straight9 (3.7%)

Showing top 9 of 37 reported. 28 additional (56 total) not shown: FTYROW: From yield sign, Operating vehicle in an reckless, erratic, careless, negligent manner, Driver Distraction: Inattentive/lost in thought, Swerving/Evasive Action, Other (explain in narrative): No improper action, Ran Traffic Signal, FTYROW: Making left turn, Improper Backing, Driver Distraction: Other interior distraction, Driver Distraction: Talking on a hand-held device, Operator inexperience, Made improper turn, Passing: Through/around barrier, FTYROW: Other (explain in narrative), FTYROW: To pedestrian, Driver Distraction: Exterior distraction, Driver Distraction: Manual operation of an electronic communication device, Driver Distraction: Unrestrained animal, Equipment failure, Exceeded authorized speed, Failed to keep in proper lane, Failure to signal intentions, FTYROW: Making right turn on red signal, Aggressive driving/road rage, Improper or erratic lane changing, Other (explain in narrative): Vision obstructed, Passing: Other passing (explain in narrative), Ran off road - right.

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

First Harmful Event

The most common first harmful event was a 'Collision with: Vehicle in traffic,' which occurred in 95 crashes. A 'Collision with: Animal' was a very close second, recorded as the first harmful event in 80 crashes. Single-vehicle events like 'Overturn/rollover' (20 crashes) and striking a ditch (15 crashes) were also significant.

First Harmful Event

1
Collision with: Vehicle in traffic95 (37.4%)
2
Collision with: Animal80 (31.5%)
3
Non-collision events: Overturn/rollover20 (7.9%)
4
Collision with fixed object: Ditch15 (5.9%)
5
Collision with: Parked motor vehicle6 (2.4%)
6
Collision with fixed object: Traffic sign support4 (1.6%)
7
Collision with fixed object: Building3 (1.2%)
8
Other (explain in narrative)3 (1.2%)
9
Collision with fixed object: Utility pole/light support3 (1.2%)

Showing top 9 of 27 reported. 18 additional (25 total) not shown: Collision with: Thrown or falling object, Collision with fixed object: Fence, Collision with: Struck/struck by object/cargo/person from other vehicle, Collision with fixed object: Tree, Collision with: Non-motorist (see non-motorist section - NOT a unit), Non-collision events: Fell/jumped from vehicle, Collision with fixed object: Bridge/bridge rail parapet, Collision with fixed object: Cable barrier, Collision with fixed object: Concrete traffic barrier (median or right side), Collision with fixed object: Embankment, Collision with fixed object: Ground, Collision with fixed object: Guardrail - face, Collision with fixed object: Other post/pole/support (explain in narrative), Collision with fixed object: Wall, Collision with: Other non-fixed object (explain in narrative), Miscellaneous events: Hit and run, Miscellaneous events: Immersion, Non-collision events: Vehicle went airborne.

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

Roadway Junction / Feature

A majority of crashes, 104 incidents, occurred at non-intersection locations described as having no special feature. Four-way intersections were the most common junction type for crashes, accounting for 48 incidents. T-intersections were the location for another 13 crashes.

Roadway Junction / Feature

1
Non-intersection: Non-junction/no special feature104 (55%)
2
Intersection: Four-way intersection48 (25.4%)
3
Intersection: T-intersection13 (6.9%)
4
Non-intersection: Driveway access (related, not in)6 (3.2%)
5
Intersection: Other intersection (explain in narrative)5 (2.6%)
6
Interchange-related: On-ramp merge area3 (1.6%)
7
Non-intersection: Crossover-related2 (1.1%)
8
Non-intersection: Driveway access (within)2 (1.1%)
9
Non-intersection: Other non-intersection (explain in narrative)2 (1.1%)

Showing top 9 of 12 reported. 3 additional (4 total) not shown: Intersection: Y-intersection, 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 common vehicle type involved in crashes, with 178 vehicles recorded. Light trucks and pickups were the next most frequent type with 75 vehicles, followed by sport utility vehicles (SUVs) with 66. Seven tractor-trailers and four motorcycles were also involved in incidents.

Vehicle Type

"Other" combines 6 smaller categories (7 records): Single unit truck (2-axle, 6-tire) (2), Other (explain in narrative) (1), Single-unit truck (>= 3 axles) (1), Moped (1), Farm equipment (explain in narrative) (1), Cargo/panel van (1).

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

Traffic Control Device

The majority of crashes, 194 incidents, occurred on roadway segments where no traffic controls were present. Stop signs were the most common form of traffic control at crash locations, present in 59 cases. Traffic signals were present for 25 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 impact, with 88 vehicles sustaining primary damage there. Rear impacts, indicative of rear-end collisions, were the second most frequent, with 31 vehicles damaged at the rear. Front-corner impacts were also common, with 30 vehicles damaged on the front passenger side corner.

Most Damaged Area

"Other" combines 9 smaller categories (63 records): Passenger side - middle (13), Passenger side - front (12), Driver side - rear (10), Rear - driver side corner (7), Rear - passenger side corner (6), Other (explain in narrative) (6), Passenger side - rear (6), Non-collision/no damage (2), Undercarriage (1).

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

Crashes by City

The highest number of crashes occurred in Fairfield, which recorded 108 incidents. Far fewer crashes were recorded in other municipalities, with Lockridge reporting 7 crashes and Maharishi Vedic City reporting 3. A single crash was also recorded in Batavia, Libertyville, and Sioux City within the county's jurisdiction.

Crashes by City

1
FAIRFIELD108 (89.3%)
2
LOCKRIDGE7 (5.8%)
3
MAHARISHI VEDIC CITY3 (2.5%)
4
BATAVIA1 (0.8%)
5
LIBERTYVILLE1 (0.8%)
6
SIOUX CITY1 (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, 228 incidents, took place on paved roads. However, a notable 25 crashes, representing 9.9% of the total where surface type was known, occurred 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

Among crashes where a roadway factor was cited, 'Surface condition (e.g. wet, icy)' was the most common contributor, noted in 24 incidents. Other less frequent factors included 'Slippery, loose or worn surface' (3 crashes) and 'Debris' on the roadway (2 crashes).

Roadway Contributing Factor

1
Surface condition (e.g.wet, icy)24 (77.4%)
2
Slippery, loose or worn surface3 (9.7%)
3
Debris2 (6.5%)
4
Non-highway work1 (3.2%)
5
Traffic backup, regular congestion1 (3.2%)

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 noted as something other than 'apparently normal,' 'Under the influence of alcohol' was recorded for 8 drivers. 'Asleep/fatigued' was the condition for 7 drivers, and 'Emotional' (e.g., depressed, angry) was noted for 4 drivers.

Driver Condition

1
Under the influence of alcohol8 (33.3%)
2
Asleep/fatigued7 (29.2%)
3
Emotional (e.g. depressed, angry)4 (16.7%)
4
Under the influence of drugs/meds2 (8.3%)
5
Medical condition (seizure, reaction)1 (4.2%)
6
Illness/fainted1 (4.2%)
7
Paraplegic/wheelchair restricted1 (4.2%)

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

Property Damage

For crashes with property damage estimates, the most frequent cost bracket was '$1,500 - $7,500,' which applied to 200 incidents. Forty-four crashes resulted in damages estimated between $7,500 and $25,000, while only two crashes were estimated to have damage 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

Single-vehicle crashes were the predominant manner of collision, with 129 'Non-collision (single vehicle)' events making up 50.4% of all incidents. Among multi-vehicle crashes, broadside collisions were most common with 44 incidents (17.2%), followed by rear-end collisions with 35 incidents (13.7%).

Manner of Collision

"Other" combines 1 smaller categories (1 records): Rear to side (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, 243 in total, were engaged in 'Movement essentially straight' just before the incident. The next most common pre-crash action was 'Turning left,' which was reported for 20 vehicles. Nine vehicles were 'Stopped in traffic' prior to being involved in a collision.

Pre-Crash Driver Action

1
Movement essentially straight243 (75%)
2
Turning left20 (6.2%)
3
Stopped in traffic9 (2.8%)
4
Legally Parked9 (2.8%)
5
Turning right8 (2.5%)
6
Slowing/stopping (deceleration)7 (2.2%)
7
Overtaking/passing7 (2.2%)
8
Other (explain in narrative)5 (1.5%)
9
Backing4 (1.2%)

Showing top 9 of 15 reported. 6 additional (12 total) not shown: Entering traffic lane (merging), Negotiating a curve, Starting in road, Entering a parked position, Leaving a parked position, Changing lanes.

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

Person Type

Of the 446 individuals involved in crashes, the overwhelming majority, 424 people (95.1%), were drivers. Passengers accounted for 19 individuals, while 2 were bicyclists and 1 was a pedestrian.

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 80 individuals sustained injuries in crashes. Among them, 1 injury was fatal, 8 were classified as serious, 35 were minor, and 36 were categorized as 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

Based on the limited available data for safety equipment usage, 49 individuals were recorded as using a shoulder and lap belt. Five individuals were explicitly noted as having used no safety equipment. Other recorded uses included various types of child safety seats and one 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, with 151 incidents, accounting for 59.0% of the total. Two-vehicle crashes were the next most frequent, with 100 incidents (39.1%). A small number of crashes, 5 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: 256
  • Total persons involved: 446
  • Total vehicles involved: 366

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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