Yearly Traffic Safety Analysis

278 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Henry County, total traffic crashes decreased from 293 in 2024 to 278 in 2025, a 5.1% reduction. While overall crashes and injuries declined, the number of fatalities increased from 3 to 4. A notable shift occurred in contributing factors, where crashes attributed to 'Ran off road - straight' increased by 185.7%, from 7 incidents in the prior year to 20 in the current year.

278

▼ -5.1%was 293

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

57

▼ -21.9%was 73

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

Year-over-year data for Henry County indicates a downward trend in overall traffic incidents. Total crashes fell by 5.1%, from 293 in 2024 to 278 in 2025. Similarly, the number of people injured in these crashes decreased by 21.9% from 73 to 57, although fatalities saw a slight increase from 3 to 4.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 3↑33.3%

1

Cyclists Injured

Prior: 2↓-50.0%

56

Motorists Injured

Prior: 70↓-20.0%

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 in Henry County showed some shifts between the two periods. The peak day for collisions moved from Friday (61 crashes) in 2024 to Monday (48 crashes) in 2025. While the 6 p.m. hour remained the peak time for crashes in both years, the number of incidents during that hour decreased from 28 to 23. Monthly trends showed a significant increase in crashes during March, which doubled from 9 to 18 year-over-year.

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

The severity of crashes shifted year-over-year. The number of fatal crashes increased from 3 in 2024 to 4 in 2025, with the fatal crash rate rising from 1.02 to 1.44 per 100 crashes. Conversely, crashes resulting in any level of injury decreased, with their share of total crashes falling from 22.2% to 17.6%. This was driven by a drop in both serious injury crashes (from 9 to 5) and possible injury crashes (from 35 to 24). The number of no-injury crashes remained constant at 225, but their proportion of all crashes increased from 76.8% to 80.9%.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.4%
↑33.3%prior 3
Serious Injury5serious injury crashes1.8%
↓-44.4%prior 9
Minor Injury20minor injury crashes7.2%
↓-4.8%prior 21
Possible Injury24possible injury crashes8.6%
↓-31.4%prior 35
No Injury225no injury crashes80.9%
→0.0%prior 225

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 involving an 'Animal' remained the most common contributing factor in both periods, though the count decreased from 114 in 2024 to 95 in 2025. A significant year-over-year change was observed for crashes attributed to 'Ran off road - straight', which increased in count by 185.7% from 7 to 20 incidents, becoming the second-leading factor in 2025. The count for 'Ran Stop Sign' also increased from 10 to 15, while 'Lost Control' incidents saw a slight decrease from 22 to 19.

Officer-Reported Primary Contributing Cause

Animal95 (34.2%)↓-16.7%prior 114
Ran off road - straight20 (7.2%)↑185.7%prior 7
Lost Control19 (6.8%)↓-13.6%prior 22
FTYROW: From stop sign15 (5.4%)→0.0%prior 15
Ran Stop Sign15 (5.4%)↑50.0%prior 10
Other (explain in narrative): Other11 (4%)↑37.5%prior 8
Driving too fast for conditions10 (3.6%)↑25.0%prior 8
Driver Distraction: Other interior distraction9 (3.2%)↑28.6%prior 7
Operating vehicle in an reckless, erratic, careless, negligent manner7 (2.5%)↓-30.0%prior 10
Made improper turn7 (2.5%)→0.0%prior 7

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 across different environmental conditions showed some year-over-year changes. The proportion of crashes occurring on dry road surfaces increased from 45.4% in 2024 to 55.4% in 2025, while crashes on adverse surfaces like snow, wet, or ice decreased from 13.3% to 9.7% of the total. Similarly, crashes during adverse weather conditions (including rain, snow, and fog) represented a smaller share of the total, falling from 18.8% to 14.0%. The distribution of crashes by lighting conditions remained consistent, with about 20.5% of crashes occurring in dark conditions in both years.

Weather

Clear147 (78.6%)
↑8.1%prior 136
Cloudy24 (12.8%)
↓-4.0%prior 25
Snow6 (3.2%)
↓-40.0%prior 10
Rain4 (2.1%)
↓-63.6%prior 11
Fog, smoke, smog3 (1.6%)
↓-57.1%prior 7
Freezing rain/drizzle1 (0.5%)
Other (explain in narrative)1 (0.5%)
Blowing Snow1 (0.5%)

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

Lighting

Daylight124 (64.2%)
↓-1.6%prior 126
Dark - roadway not lighted36 (18.7%)
↓-5.3%prior 38
Dark - roadway lighted14 (7.3%)
↑7.7%prior 13
Dawn7 (3.6%)
↓-30.0%prior 10
Dark - unknown roadway lighting7 (3.6%)
↓-22.2%prior 9
Dusk5 (2.6%)

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

Road Surface

Dry154 (81.9%)
↑15.8%prior 133
Snow11 (5.9%)
↓-15.4%prior 13
Wet8 (4.3%)
↓-60.0%prior 20
Ice/frost7 (3.7%)
↑16.7%prior 6
Gravel7 (3.7%)
↓-58.8%prior 17
Slush1 (0.5%)

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

Vehicles & Demographics

An analysis of vehicles and persons involved shows shifts in both make and age demographics. The top vehicle makes involved in crashes remained Chevrolet and Ford, though both saw a reduction in counts from the prior year. The involvement of Toyota vehicles, however, increased from 27 in 2024 to 41 in 2025. Regarding the age of persons involved, there was a significant decrease in the 65+ age group, which fell from 86 individuals in 2024 to 64 in 2025. The number of individuals in the 16-20 age group remained unchanged at 49.

Top Vehicle Makes (395 vehicles)

1
CHEV54 (13.7%)
↓-14.3%prior 63
2
FORD46 (11.6%)
↓-19.3%prior 57
3
GMC27 (6.8%)
↑12.5%prior 24
4
TOYT25 (6.3%)
↑47.1%prior 17
5
CHEVROLET19 (4.8%)
↑18.8%prior 16
6
KIA17 (4.3%)
↑41.7%prior 12
7
TOYOTA16 (4.1%)
↑60.0%prior 10
8
HOND14 (3.5%)
↓-6.7%prior 15
9
BUIC13 (3.3%)
↑116.7%prior 6
10
DODG13 (3.3%)
↓-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 (221 persons with recorded sex)

Male135 (61.1%)
↑6.3%prior 127
Female86 (38.9%)
↑11.7%prior 77

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: 278
  • Total persons involved: 405
  • Total vehicles involved: 395

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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