Yearly Traffic Safety Analysis

385 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, there were 385 total crashes in Iowa, compared to 393 in 2024, representing a 2.0% decrease. The most significant year-over-year change was the reduction in crash severity, with total fatalities falling by 66.7% from 6 to 2 and fatal crashes decreasing from 6 to 2. DUI-related crashes also saw a substantial decline, dropping from 11 to 3 incidents.

385

▼ -2.0%was 393

Total Crash Events

2

▼ -66.7%was 6

Persons Killed

93

▼ -7.0%was 100

Persons Injured

2

▼ -66.7%was 6

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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety metrics improved from 2024 to 2025. Total crashes decreased by 2.0% from 393 to 385. More significantly, total fatalities dropped by 66.7% from 6 to 2, and the number of injuries fell by 7.0% from 100 to 93, indicating a positive trend in reducing severe outcomes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

1

Motorists Killed

Prior: 6↓-83.3%

0

Pedestrians Injured

Prior: 0→0.0%

93

Motorists Injured

Prior: 99↓-6.1%

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 timing of crashes showed a notable shift between the two periods. While the peak day for crashes moved slightly from Friday (80 incidents) in 2024 to Saturday (79 incidents) in 2025, the peak hour changed dramatically. In 2024, the most crashes occurred at 6 a.m. (33 incidents), whereas in 2025, the peak shifted to 6 p.m. (33 incidents).

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 decreased significantly year-over-year. The number of fatal crashes fell from 6 in 2024 to 2 in 2025, and their share of all crashes dropped from 1.5% to 0.5%. The proportion of crashes resulting in any type of injury remained stable at approximately 20% for both periods. Consequently, the share of non-injury crashes increased slightly from 78.4% to 79.2%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
↓-66.7%prior 6
Serious Injury9serious injury crashes2.3%
↑80.0%prior 5
Minor Injury31minor injury crashes8.1%
↑3.3%prior 30
Possible Injury38possible injury crashes9.9%
↓-13.6%prior 44
No Injury305no injury crashes79.2%
↓-1.0%prior 308

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

Collisions with an animal remained the leading contributing factor in both periods, with counts holding nearly constant at 131 in 2024 and 132 in 2025. A notable change was the increase in 'Lost Control' crashes, which grew by 64% from 25 to 41 incidents, making it the second-leading factor in the current period. In contrast, crashes attributed to 'Driving too fast for conditions' decreased from 43 to 41, and 'Ran off road - straight' incidents fell from 33 to 27.

Officer-Reported Primary Contributing Cause

Animal132 (34.3%)↑0.8%prior 131
Lost Control41 (10.6%)↑64.0%prior 25
Driving too fast for conditions41 (10.6%)↓-4.7%prior 43
Ran off road - straight27 (7%)↓-18.2%prior 33
Ran off road - left25 (6.5%)↑66.7%prior 15
FTYROW: From stop sign15 (3.9%)↑15.4%prior 13
Followed too close14 (3.6%)↓-36.4%prior 22
Other (explain in narrative): Other7 (1.8%)↓-30.0%prior 10
Ran off road - right7 (1.8%)
Driver Distraction: Inattentive/lost in thought6 (1.6%)↓-45.5%prior 11

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

Road & Environmental Conditions

The distribution of crashes by environmental conditions showed minor shifts. The share of crashes on dry road surfaces decreased from 64.4% in 2024 to 59.6% in 2025 among incidents with known road conditions. Correspondingly, the proportion of crashes on adverse surfaces like snow, ice, or wet pavement increased from 35.6% to 40.4%. The share of crashes occurring in daylight versus darkness remained relatively stable across both periods.

Weather

Clear118 (46.6%)
↓-18.6%prior 145
Cloudy70 (27.7%)
↓-2.8%prior 72
Snow36 (14.2%)
↑50.0%prior 24
Blowing Snow16 (6.3%)
→0.0%prior 16
Fog, smoke, smog5 (2.0%)
↓-16.7%prior 6
Freezing rain/drizzle3 (1.2%)
↓-62.5%prior 8
Rain3 (1.2%)
↓-66.7%prior 9
Severe Winds1 (0.4%)
Blowing sand, soil, dirt1 (0.4%)

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

Lighting

Daylight169 (65.3%)
↓-6.1%prior 180
Dark - roadway not lighted66 (25.5%)
↑6.5%prior 62
Dark - roadway lighted11 (4.2%)
↓-35.3%prior 17
Dawn8 (3.1%)
↓-27.3%prior 11
Dusk3 (1.2%)
↓-75.0%prior 12
Dark - unknown roadway lighting2 (0.8%)

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

Road Surface

Dry152 (59.6%)
↓-16.0%prior 181
Snow46 (18.0%)
↑64.3%prior 28
Ice/frost22 (8.6%)
↓-37.1%prior 35
Gravel16 (6.3%)
↑60.0%prior 10
Wet14 (5.5%)
↓-44.0%prior 25
Slush3 (1.2%)
Sand1 (0.4%)
Other (explain in narrative)1 (0.4%)

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 were consistent year-over-year, with Ford and Chevrolet vehicles accounting for the highest numbers in both periods. Analysis of driver and passenger age demographics reveals that while the 35-44 age group was the largest involved cohort in both years, the 26-34 age group saw a notable increase in involvement, rising from 69 persons in 2024 to 88 in 2025. Other age groups remained relatively stable.

Top Vehicle Makes (530 vehicles)

1
FORD82 (15.5%)
↓-3.5%prior 85
2
CHEV61 (11.5%)
↓-10.3%prior 68
3
FREIGHTLINER36 (6.8%)
→0.0%prior 36
4
TOYO30 (5.7%)
↑50.0%prior 20
5
JEEP26 (4.9%)
↑100.0%prior 13
6
DODG26 (4.9%)
↑23.8%prior 21
7
CHEVROLET19 (3.6%)
↓-9.5%prior 21
8
RAM14 (2.6%)
↑55.6%prior 9
9
HOND13 (2.5%)
↓-23.5%prior 17
10
GMC13 (2.5%)
↓-31.6%prior 19

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

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

Sex Distribution (284 persons with recorded sex)

Male208 (73.2%)
↑2.5%prior 203
Female76 (26.8%)
↓-21.6%prior 97

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: 385
  • Total persons involved: 542
  • Total vehicles involved: 530

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

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