Yearly Traffic Safety Analysis

254 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Harrison County, total traffic crashes decreased by 9.6%, from 281 incidents in 2024 to 254 in 2025. Despite the overall reduction in crashes, the most significant change was the occurrence of 2 fatalities in 2025, compared to zero in the prior year. Additionally, the total number of people injured rose from 78 to 107.

254

▼ -9.6%was 281

Total Crash Events

2

Persons Killed

107

▲ 37.2%was 78

Persons Injured

2

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 crashes in Harrison County saw a downward trend, decreasing by 9.6% from 281 in 2024 to 254 in 2025. In contrast to the drop in total incidents, the number of people injured increased by 37.2% year-over-year, and the county recorded two fatalities in 2025 after having none in the previous year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

2

Cyclists Injured

Prior: 1↑100.0%

105

Motorists Injured

Prior: 76↑38.2%

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 some shifts between the two periods. Friday remained the peak day for crashes in both 2024 (53 crashes) and 2025 (47 crashes). However, the peak hour for incidents shifted from 4 PM in 2024, with 26 crashes, to 6 PM in 2025, with 19 crashes. This suggests a later concentration of crashes during the evening commute period in the current 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

Crash severity increased in 2025 compared to the prior year. The county recorded two fatal crashes, representing 0.8% of all incidents, after having zero in 2024. While the number of serious injury crashes decreased slightly from 16 to 14, the overall proportion of crashes resulting in an injury rose. Crashes involving minor injuries increased from 27 to 38, and possible injury crashes grew from 20 to 26.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
Serious Injury14serious injury crashes5.5%
↓-12.5%prior 16
Minor Injury38minor injury crashes15%
↑40.7%prior 27
Possible Injury26possible injury crashes10.2%
↑30.0%prior 20
No Injury174no injury crashes68.5%
↓-20.2%prior 218

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

The leading contributing factors for crashes remained consistent year-over-year, though their counts generally decreased. 'Animal' was the top factor in both periods, with its count dropping from 51 crashes in 2024 to 41 in 2025. Similarly, 'Lost Control' incidents decreased in count from 36 to 27. A notable change was the increase in crashes attributed to 'FTYROW: From stop sign,' which more than doubled in count from 6 to 13 incidents.

Officer-Reported Primary Contributing Cause

Animal41 (16.1%)↓-19.6%prior 51
Lost Control27 (10.6%)↓-25.0%prior 36
Ran off road - straight22 (8.7%)↓-12.0%prior 25
Ran off road - left22 (8.7%)↓-24.1%prior 29
Driving too fast for conditions17 (6.7%)→0.0%prior 17
Followed too close13 (5.1%)↓-40.9%prior 22
FTYROW: From stop sign13 (5.1%)↑116.7%prior 6
Driver Distraction: Other interior distraction13 (5.1%)↓-7.1%prior 14
Driver Distraction: Inattentive/lost in thought7 (2.8%)↓-22.2%prior 9
Other (explain in narrative): Other6 (2.4%)↓-25.0%prior 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

The distribution of crashes across different environmental conditions remained largely stable year-over-year. In both periods, a majority of crashes occurred in daylight (57.1% in 2025 vs. 53.7% in 2024) and on dry road surfaces (62.6% in 2025 vs. 61.9% in 2024). There was a notable decrease in crashes on roads with ice or frost, which fell from 23 incidents in 2024 to 12 in 2025. Conversely, crashes on snowy surfaces saw a slight increase from 16 to 19.

Weather

Clear156 (72.2%)
↓-6.6%prior 167
Cloudy23 (10.6%)
↓-25.8%prior 31
Snow13 (6.0%)
↑8.3%prior 12
Blowing Snow6 (2.8%)
Freezing rain/drizzle5 (2.3%)
↓-28.6%prior 7
Rain5 (2.3%)
↓-16.7%prior 6
Fog, smoke, smog4 (1.9%)
↓-33.3%prior 6
Severe Winds2 (0.9%)
Other (explain in narrative)1 (0.5%)
Sleet, hail1 (0.5%)

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

Lighting

Daylight145 (66.5%)
↓-4.0%prior 151
Dark - roadway not lighted51 (23.4%)
↓-5.6%prior 54
Dark - roadway lighted11 (5.0%)
↓-42.1%prior 19
Dusk5 (2.3%)
↓-16.7%prior 6
Dawn4 (1.8%)
↓-55.6%prior 9
Dark - unknown roadway lighting2 (0.9%)
↓-66.7%prior 6

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

Road Surface

Dry159 (73.6%)
↓-8.6%prior 174
Snow19 (8.8%)
↑18.8%prior 16
Wet15 (6.9%)
↑36.4%prior 11
Ice/frost12 (5.6%)
↓-47.8%prior 23
Gravel6 (2.8%)
↓-53.8%prior 13
Slush5 (2.3%)

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

Vehicles & Demographics

Analysis of vehicles and persons involved shows shifts in both make and age demographics. Chevrolet and Ford remained the top two vehicle makes involved in crashes, though both saw a reduction in counts from the prior year. Regarding persons involved, there was a notable increase in the 55-64 age group, which grew from 38 individuals in 2024 to 58 in 2025, making it the most represented age bracket. Conversely, the number of people involved from the 26-34 and 35-44 age groups decreased.

Top Vehicle Makes (361 vehicles)

1
FORD51 (14.1%)
↓-21.5%prior 65
2
CHEV40 (11.1%)
↓-14.9%prior 47
3
CHEVROLET28 (7.8%)
↑21.7%prior 23
4
JEEP13 (3.6%)
↓-35.0%prior 20
5
HONDA11 (3%)
↑37.5%prior 8
6
TOYOTA10 (2.8%)
→0.0%prior 10
7
DODG9 (2.5%)
↓-55.0%prior 20
8
DODGE9 (2.5%)
↓-10.0%prior 10
9
FREIGHTLINER9 (2.5%)
↑28.6%prior 7
10
GMC8 (2.2%)
↓-42.9%prior 14

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

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

Sex Distribution (213 persons with recorded sex)

Male142 (66.7%)
↓-10.7%prior 159
Female71 (33.3%)
↓-19.3%prior 88

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: 254
  • Total persons involved: 381
  • Total vehicles involved: 361

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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