Yearly Traffic Safety Analysis

269 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Jackson County, total traffic crashes remained relatively stable, with 269 incidents in 2025 compared to 272 in 2024, a decrease of 1.1%. While total injuries fell 23.2% from 82 to 63, the number of fatalities increased from 3 to 4. The single most notable year-over-year shift was an 18.5% increase in the count of crashes attributed to animals, which rose from 108 to 128 incidents.

269

▼ -1.1%was 272

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

63

▼ -23.2%was 82

Persons Injured

4

▲ 33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

The overall trend in crash volume was stable year-over-year, with a minor decrease of 1.1% from 272 crashes in 2024 to 269 in 2025. Despite the steady number of incidents, outcomes shifted, as total fatalities rose from 3 to 4. Concurrently, the number of people injured in crashes declined significantly from 82 to 63.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 3↑33.3%

2

Pedestrians Injured

Prior: 2→0.0%

61

Motorists Injured

Prior: 77↓-20.8%

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 shifted between the two periods. The peak day for collisions moved from Tuesday (55 crashes) in 2024 to Saturday (47 crashes) in 2025. The peak hour also occurred earlier in the evening, shifting from 9 p.m. in the prior year (23 crashes) to 6 p.m. in the current year (32 crashes).

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

Year-over-year data shows a shift toward more severe outcomes in crashes, even as the total number of injuries declined. The count of fatal crashes increased from 3 to 4, and serious injury crashes rose from 6 to 10. In contrast, crashes resulting in minor or possible injuries decreased from a combined 59 incidents to 41. The proportion of collisions with no reported injuries increased from 75.0% to 79.6%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.5%
↑33.3%prior 3
Serious Injury10serious injury crashes3.7%
↑66.7%prior 6
Minor Injury19minor injury crashes7.1%
↓-32.1%prior 28
Possible Injury22possible injury crashes8.2%
↓-29.0%prior 31
No Injury214no injury crashes79.6%
↑4.9%prior 204

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 were the leading contributing factor in both periods and grew significantly, with the count of incidents rising from 108 to 128, an 18.5% increase. This factor's share of all crashes increased from 39.7% in 2024 to 47.6% in 2025. The second-leading factor, 'Lost Control,' remained stable with 24 incidents compared to 25 in the prior year.

Officer-Reported Primary Contributing Cause

Animal128 (47.6%)↑18.5%prior 108
Lost Control24 (8.9%)↓-4.0%prior 25
Other (explain in narrative): Other13 (4.8%)↓-13.3%prior 15
Ran off road - left11 (4.1%)↓-21.4%prior 14
Driver Distraction: Other interior distraction10 (3.7%)↑11.1%prior 9
FTYROW: From stop sign8 (3%)↓-11.1%prior 9
Driving too fast for conditions7 (2.6%)↓-22.2%prior 9
Ran Stop Sign7 (2.6%)↑16.7%prior 6
Ran off road - straight5 (1.9%)↓-50.0%prior 10
Driver Distraction: Exterior distraction5 (1.9%)

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

Road & Environmental Conditions

Compared to the prior year, a larger proportion of crashes in the current period occurred in favorable conditions. Incidents on wet road surfaces decreased from 20 to 7, and crashes in cloudy weather fell from 35 to 18. Crashes on dry roads remained consistent at 126 (up from 125), while collisions in clear weather increased from 106 to 121.

Weather

Clear121 (82.3%)
↑14.2%prior 106
Cloudy18 (12.2%)
↓-48.6%prior 35
Snow4 (2.7%)
↓-42.9%prior 7
Other (explain in narrative)2 (1.4%)
Fog, smoke, smog1 (0.7%)
Rain1 (0.7%)
↓-92.3%prior 13

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

Lighting

Daylight107 (68.2%)
↓-6.1%prior 114
Dark - roadway not lighted24 (15.3%)
↓-29.4%prior 34
Dark - roadway lighted10 (6.4%)
↓-33.3%prior 15
Dawn6 (3.8%)
Dusk5 (3.2%)
→0.0%prior 5
Dark - unknown roadway lighting5 (3.2%)
↓-44.4%prior 9

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

Road Surface

Dry126 (85.7%)
↑0.8%prior 125
Wet7 (4.8%)
↓-65.0%prior 20
Snow6 (4.1%)
↓-33.3%prior 9
Gravel4 (2.7%)
↓-20.0%prior 5
Ice/frost3 (2.0%)
↓-72.7%prior 11
Slush1 (0.7%)

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

Vehicles & Demographics

The representation of different age groups involved in crashes shifted year-over-year. The number of persons aged 16-20 involved in crashes decreased from 53 to 38, while those aged 21-25 increased from 29 to 37. The top vehicle makes involved in collisions, Ford and Chevrolet, both saw their counts increase compared to the prior year.

Top Vehicle Makes (366 vehicles)

1
FORD68 (18.6%)
↑7.9%prior 63
2
CHEV62 (16.9%)
↑14.8%prior 54
3
CHEVROLET22 (6%)
↑22.2%prior 18
4
GMC21 (5.7%)
↓-12.5%prior 24
5
JEEP17 (4.6%)
↓-15.0%prior 20
6
TOYT16 (4.4%)
↑14.3%prior 14
7
DODG16 (4.4%)
↓-20.0%prior 20
8
NISS13 (3.6%)
↑30.0%prior 10
9
BUIC12 (3.3%)
↑50.0%prior 8
10
SUBA9 (2.5%)

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

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

Sex Distribution (147 persons with recorded sex)

Male96 (65.3%)
↓-6.8%prior 103
Female51 (34.7%)
↓-26.1%prior 69

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: 269
  • Total persons involved: 378
  • 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: 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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