Yearly Traffic Safety Analysis

181 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Jefferson County recorded 181 total vehicle crashes, a 14.6% decrease from the 212 crashes recorded in 2024. Despite this overall reduction in collisions, the number of fatalities doubled from one to two year-over-year.

181

▼ -14.6%was 212

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

63

▼ -1.6%was 64

Persons Injured

2

▲ 100.0%was 1

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

Crash data for Jefferson County indicates a downward trend in the total number of collisions, which fell from 212 in 2024 to 181 in 2025. However, this trend in crash volume did not extend to crash severity. Fatalities increased from one to two, and the number of fatal crashes also doubled from one to two over the same period, while total injuries remained nearly unchanged at 63 compared to 64 in the prior year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 1↑100.0%

2

Pedestrians Injured

Prior: 3↓-33.3%

1

Cyclists Injured

Prior: 4↓-75.0%

60

Motorists Injured

Prior: 57↑5.3%

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 a shift year-over-year. The peak day for crashes moved from Saturday (35 incidents) in 2024 to Thursday (35 incidents) in 2025. Similarly, the single busiest hour for collisions shifted from 7 p.m. in the prior year (19 crashes) to 9 p.m. in the current year (17 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

While total crashes decreased, the severity of crashes worsened in 2025. The number of fatal crashes doubled from one to two, and the fatal crash rate increased from 0.5% to 1.1% of all crashes. The count of serious injury crashes declined from 13 to 10, while the proportion of minor and possible injury crashes remained relatively stable year-over-year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
↑100.0%prior 1
Serious Injury10serious injury crashes5.5%
↓-23.1%prior 13
Minor Injury21minor injury crashes11.6%
↓-8.7%prior 23
Possible Injury23possible injury crashes12.7%
↓-14.8%prior 27
No Injury125no injury crashes69.1%
↓-15.5%prior 148

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 animals remained the leading contributing factor in both periods, with counts increasing from 52 in 2024 to 59 in 2025. 'Lost Control' was the second-most cited factor in 2024 with 16 incidents but decreased to 13 incidents in 2025, tying with 'FTYROW: From stop sign' (which increased from 10 incidents). Incidents involving 'Ran Stop Sign' decreased from 11 to 7, while those attributed to 'Driving too fast for conditions' rose from 6 to 9.

Officer-Reported Primary Contributing Cause

Animal59 (32.6%)↑13.5%prior 52
FTYROW: From stop sign13 (7.2%)↑30.0%prior 10
Lost Control13 (7.2%)↓-18.8%prior 16
Ran off road - straight10 (5.5%)↓-16.7%prior 12
Driving too fast for conditions9 (5%)↑50.0%prior 6
Ran Stop Sign7 (3.9%)↓-36.4%prior 11
Ran off road - left7 (3.9%)↓-30.0%prior 10
Exceeded authorized speed6 (3.3%)↓-14.3%prior 7
Driver Distraction: Other interior distraction6 (3.3%)→0.0%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner6 (3.3%)→0.0%prior 6

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 remained broadly consistent between 2024 and 2025, with the majority of incidents in both years occurring in daylight on dry roads. In 2025, 59.1% of crashes happened on dry roads and 54.1% in clear weather, comparable to 62.7% and 55.2% respectively in the previous year. There was a slight decrease in the proportion of crashes occurring in daylight, from 52.8% in 2024 to 47.0% in 2025.

Weather

Clear98 (73.7%)
↓-16.2%prior 117
Cloudy25 (18.8%)
↓-13.8%prior 29
Snow6 (4.5%)
↑20.0%prior 5
Fog, smoke, smog2 (1.5%)
Freezing rain/drizzle1 (0.8%)
Severe Winds1 (0.8%)

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

Lighting

Daylight85 (62.5%)
↓-24.1%prior 112
Dark - roadway not lighted26 (19.1%)
↓-23.5%prior 34
Dawn10 (7.4%)
Dark - roadway lighted8 (5.9%)
↓-33.3%prior 12
Dusk5 (3.7%)
Dark - unknown roadway lighting2 (1.5%)

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

Road Surface

Dry107 (79.9%)
↓-19.5%prior 133
Snow10 (7.5%)
↑25.0%prior 8
Wet10 (7.5%)
↓-33.3%prior 15
Ice/frost4 (3.0%)
↓-20.0%prior 5
Gravel3 (2.2%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Ford and Chevrolet, maintained their top rankings from 2024 to 2025, although their total involvement decreased in line with the overall crash reduction. An analysis of driver and passenger age demographics shows a shift in involvement; the proportion of persons aged 16-20 involved in crashes increased from 9.2% in 2024 to 14.6% in 2025. Similarly, the 65+ age group's share grew from 15.8% to 19.8% over the same period.

Top Vehicle Makes (257 vehicles)

1
FORD31 (12.1%)
↓-40.4%prior 52
2
CHEV29 (11.3%)
↓-25.6%prior 39
3
TOYT20 (7.8%)
↑11.1%prior 18
4
TOYO18 (7%)
↓-21.7%prior 23
5
DODG15 (5.8%)
↓-21.1%prior 19
6
GMC13 (5.1%)
↓-7.1%prior 14
7
CHEVROLET10 (3.9%)
↓-16.7%prior 12
8
JEEP9 (3.5%)
↓-40.0%prior 15
9
RAM8 (3.1%)
↑60.0%prior 5
10
SUBA8 (3.1%)
↑33.3%prior 6

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

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

Sex Distribution (132 persons with recorded sex)

Male80 (60.6%)
↓-23.1%prior 104
Female52 (39.4%)
↓-35.0%prior 80

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: 181
  • Total persons involved: 267
  • Total vehicles involved: 257

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