Yearly Traffic Safety Analysis

109 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Decatur County, total traffic crashes decreased from 117 in 2024 to 109 in 2025, a 6.8% reduction. During this period, the number of people killed in crashes fell from 3 to 1. The most notable shift was a decrease in fatal and serious injury crashes, alongside a change in the top vehicle make involved in collisions.

109

▼ -6.8%was 117

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

44

▼ -6.4%was 47

Persons Injured

1

▼ -50.0%was 2

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

Trend Summary

Overall crash trends in Decatur County were favorable year-over-year. Total crashes declined by 6.8%, from 117 to 109. Similarly, total injuries saw a slight decrease from 47 to 44, while fatalities dropped from 3 in the prior period to 1 in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

42

Motorists Injured

Prior: 45↓-6.7%

1

Other Injured

Prior: 1→0.0%

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

While Friday remained the peak day for crashes in both periods, the peak hour shifted from the evening to the morning. In 2025, the highest number of crashes occurred during the 8 a.m. hour (10 crashes), a change from 2024 when the 6 p.m. hour was the peak with 11 crashes. November was the month with the most crashes in both years, though the count fell from 21 to 16.

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 compared to the prior year. The number of fatal crashes fell from 2 to 1, and serious injury crashes dropped from 7 to 4. Conversely, crashes resulting in minor injuries increased from 13 to 19. The proportion of crashes with no injuries remained stable, accounting for 67.0% of incidents in 2025 compared to 67.5% in 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.9%
↓-50.0%prior 2
Serious Injury4serious injury crashes3.7%
↓-42.9%prior 7
Minor Injury19minor injury crashes17.4%
↑46.2%prior 13
Possible Injury12possible injury crashes11%
↓-25.0%prior 16
No Injury73no injury crashes67%
↓-7.6%prior 79

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 years, though the count decreased slightly from 46 to 43. The second most common factor, losing control, also saw a decline from 13 incidents to 10. Notably, crashes attributed to running a stop sign saw a significant drop in count from 5 to 1, while incidents involving driver distraction from an interior source increased from 3 to 5.

Officer-Reported Primary Contributing Cause

Animal43 (39.4%)↓-6.5%prior 46
Lost Control10 (9.2%)↓-23.1%prior 13
Ran off road - left7 (6.4%)↑40.0%prior 5
Ran off road - straight6 (5.5%)↑20.0%prior 5
Driver Distraction: Other interior distraction5 (4.6%)
Followed too close4 (3.7%)
FTYROW: From stop sign4 (3.7%)↓-20.0%prior 5
Driver Distraction: Reaching for object(s)/fallen object(s)3 (2.8%)
Cargo/equipment loss or shift2 (1.8%)
Driver Distraction: Exterior distraction2 (1.8%)

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

Road & Environmental Conditions

Year-over-year data shows a decrease in crashes occurring under adverse conditions. Crashes on wet road surfaces fell from 15 to 7, and incidents during rainfall dropped from 7 to 1. Additionally, crashes in darkness on unlit roadways decreased from 21 to 15, while crashes in daylight increased from 44 to 51.

Weather

Clear49 (71.0%)
↓-2.0%prior 50
Cloudy15 (21.7%)
↑7.1%prior 14
Blowing Snow2 (2.9%)
Fog, smoke, smog1 (1.4%)
Freezing rain/drizzle1 (1.4%)
Rain1 (1.4%)
↓-85.7%prior 7

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

Lighting

Daylight51 (69.9%)
↑15.9%prior 44
Dark - roadway not lighted15 (20.5%)
↓-28.6%prior 21
Dawn4 (5.5%)
Dusk1 (1.4%)
↓-80.0%prior 5
Dark - unknown roadway lighting1 (1.4%)
Dark - roadway lighted1 (1.4%)

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

Road Surface

Dry54 (77.1%)
↑5.9%prior 51
Wet7 (10.0%)
↓-53.3%prior 15
Gravel4 (5.7%)
Snow3 (4.3%)
Ice/frost1 (1.4%)
Slush1 (1.4%)

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

Vehicles & Demographics

The most common vehicle make involved in crashes shifted, with Ford taking the top spot with 29 vehicles, an increase from 16 in the prior year. Chevrolet, previously the top make with 44 vehicles, saw its involvement decrease to 22. Among persons involved in crashes, there was a notable increase in the 16-20 age group (from 14 to 25 individuals) and a significant decrease in the 35-44 age group (from 36 to 18 individuals).

Top Vehicle Makes (143 vehicles)

1
FORD29 (20.3%)
↑81.3%prior 16
2
CHEVROLET12 (8.4%)
↓-47.8%prior 23
3
FREIGHTLINER10 (7%)
4
CHEV10 (7%)
↓-52.4%prior 21
5
DODG5 (3.5%)
→0.0%prior 5
6
JEEP5 (3.5%)
7
HOND4 (2.8%)
8
NISS4 (2.8%)
↓-20.0%prior 5
9
VOLK4 (2.8%)
10
NISSAN4 (2.8%)

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

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

Sex Distribution (59 persons with recorded sex)

Male36 (61.0%)
↓-18.2%prior 44
Female23 (39.0%)
↑35.3%prior 17

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: 109
  • Total persons involved: 154
  • Total vehicles involved: 143

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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