Yearly Traffic Safety Analysis

141 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Union County, total vehicle crashes decreased slightly from 146 in 2024 to 141 in 2025, a 3.4% reduction. Despite the drop in overall incidents, the severity of crashes increased significantly. The number of fatalities rose from 1 to 3, and total injuries climbed from 41 to 55 during the same period.

141

▼ -3.4%was 146

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

55

▲ 34.1%was 41

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

While the total number of crashes in Union County showed a minor year-over-year decline of 3.4%, from 146 to 141, the outcomes grew more severe. Fatalities tripled from 1 to 3, and the number of people injured increased by 34.1% from 41 to 55. This indicates a trend towards fewer but more serious collisions in 2025 compared to the prior year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

53

Motorists Injured

Prior: 41↑29.3%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between 2024 and 2025. Friday remained the peak day for crashes in both periods, with 28 incidents in 2025 compared to 32 in 2024. However, the peak hour for collisions moved from the early afternoon (1:00 PM and 2:00 PM) in 2024, which each saw 14 crashes, to the mid-morning in 2025, with a peak of 15 crashes at 10:00 AM.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2025 compared to 2024. The number of fatal crashes increased from 1 to 3, and the share of crashes resulting in a fatality rose from 0.7% to 2.1%. Similarly, serious injury crashes more than doubled from 4 to 9, with their proportion increasing from 2.7% to 6.4% of all crashes. Consequently, the share of crashes with no reported injuries decreased from 77.4% in 2024 to 66.7% in 2025.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.1%
↑200.0%prior 1
Serious Injury9serious injury crashes6.4%
↑125.0%prior 4
Minor Injury15minor injury crashes10.6%
↓-11.8%prior 17
Possible Injury20possible injury crashes14.2%
↑81.8%prior 11
No Injury94no injury crashes66.7%
↓-16.8%prior 113

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained consistent year-over-year, though some secondary causes shifted. Collisions involving an animal remained the top factor, increasing slightly from 20 incidents in 2024 to 22 in 2025. Failure to yield from a stop sign was the second-ranked cause in both years, with an identical count of 17 crashes. Notably, crashes attributed to 'Driving too fast for conditions' decreased significantly from 13 in 2024 to 3 in 2025, while crashes involving 'Improper or erratic lane changing' increased from 1 to 8.

Officer-Reported Primary Contributing Cause

Animal22 (15.6%)↑10.0%prior 20
FTYROW: From stop sign17 (12.1%)→0.0%prior 17
Lost Control9 (6.4%)↑50.0%prior 6
Other (explain in narrative): Other8 (5.7%)↑33.3%prior 6
Improper or erratic lane changing8 (5.7%)
Operating vehicle in an reckless, erratic, careless, negligent manner6 (4.3%)↓-25.0%prior 8
Made improper turn6 (4.3%)↑20.0%prior 5
Ran Stop Sign6 (4.3%)
Ran off road - left5 (3.5%)↓-16.7%prior 6
Driver Distraction: Other interior distraction5 (3.5%)↓-37.5%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions shifted from 2024 to 2025, with fewer incidents occurring in adverse weather. Crashes on roads with snow, ice, or slush dropped from 22 in 2024 to 9 in 2025. Correspondingly, the proportion of crashes on dry road surfaces increased from 64.4% to 72.3%. Similarly, crashes during snowy weather conditions fell from 12 to 3. The distribution of crashes by lighting conditions remained relatively stable year-over-year, with daylight accounting for approximately 70% of incidents in both periods.

Weather

Clear103 (81.1%)
↑2.0%prior 101
Cloudy15 (11.8%)
↓-6.3%prior 16
Fog, smoke, smog3 (2.4%)
Rain3 (2.4%)
Snow3 (2.4%)
↓-66.7%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight99 (76.7%)
↓-2.0%prior 101
Dark - roadway not lighted14 (10.9%)
↓-17.6%prior 17
Dark - roadway lighted10 (7.8%)
↓-16.7%prior 12
Dusk3 (2.3%)
Dawn2 (1.6%)
Dark - unknown roadway lighting1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry102 (80.3%)
↑8.5%prior 94
Wet8 (6.3%)
↓-11.1%prior 9
Gravel8 (6.3%)
→0.0%prior 8
Snow5 (3.9%)
↓-73.7%prior 19
Slush3 (2.4%)
Ice/frost1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained stable, with Chevrolet (56) and Ford (45) leading in 2025, similar to their 2024 counts of 61 and 49, respectively. A notable demographic shift occurred in the age of persons involved in crashes. The 65+ age group saw a significant increase in involvement, rising from 34 individuals in 2024 to 54 in 2025. The 16-20 age group also saw an increase from 32 to 40 persons involved.

Top Vehicle Makes (239 vehicles)

1
CHEV45 (18.8%)
↓-6.3%prior 48
2
FORD45 (18.8%)
↓-8.2%prior 49
3
JEEP17 (7.1%)
↑88.9%prior 9
4
DODG15 (6.3%)
↑25.0%prior 12
5
KIA11 (4.6%)
↑57.1%prior 7
6
CHEVROLET11 (4.6%)
↓-15.4%prior 13
7
GMC10 (4.2%)
↓-37.5%prior 16
8
NISS8 (3.3%)
↑33.3%prior 6
9
BUIC6 (2.5%)
10
TOYT4 (1.7%)
↓-42.9%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (162 persons with recorded sex)

Male90 (55.6%)
↓-10.9%prior 101
Female72 (44.4%)
↑20.0%prior 60

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

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: 2025-01-01 through 2025-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 141
  • Total persons involved: 249
  • Total vehicles involved: 239

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: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2025-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