Yearly Traffic Safety Analysis

236 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Washington County, traffic crashes decreased from 256 in 2024 to 236 in 2025, a 7.8% reduction. During this period, the number of people injured fell from 110 to 78. The most significant year-over-year change was the reduction in traffic fatalities, which dropped from 8 in the prior period to 1 in the current period.

236

▼ -7.8%was 256

Total Crash Events

1

▼ -87.5%was 8

Persons Killed

78

▼ -29.1%was 110

Persons Injured

1

▼ -80.0%was 5

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, Washington County experienced a downward trend in traffic collisions, with total crashes falling by 7.8% from 256 in 2024 to 236 in 2025. This represents a net decrease of 20 crashes. The number of resulting injuries also decreased by 29.1%, from 110 to 78, and fatalities fell from 8 to 1.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 8↓-87.5%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

2

Cyclists Injured

Prior: 0→%

74

Motorists Injured

Prior: 108↓-31.5%

1

Other Injured

Prior: 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 showed some shifts between the two periods. The peak day for crashes moved from Monday (49 crashes) in 2024 to Wednesday (42 crashes) in 2025. Similarly, the single hour with the most crashes shifted from the 3 p.m. hour in the prior period (21 crashes) to the 4 p.m. hour in the current period (23 crashes). The afternoon commute remains the time with the highest concentration of collisions in both years.

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 significantly year-over-year. The number of fatal crashes fell from 5 in 2024 to 1 in 2025, and the corresponding number of fatalities dropped from 8 to 1. The proportion of crashes resulting in any injury also declined, from 33.2% of all crashes in the prior period to 27.1% in the current period. Conversely, the share of crashes with no reported injuries increased from 64.8% to 72.5%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-80.0%prior 5
Serious Injury13serious injury crashes5.5%
→0.0%prior 13
Minor Injury22minor injury crashes9.3%
↓-38.9%prior 36
Possible Injury29possible injury crashes12.3%
↓-19.4%prior 36
No Injury171no injury crashes72.5%
↑3.0%prior 166

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 showed some shifts in rank and volume year-over-year. Collisions involving an 'Animal' remained the top factor in both periods, with a nearly identical count of 34 crashes in 2025 compared to 33 in 2024. 'Ran off road - left' and 'Lost Control' both saw notable increases in count, each rising from 14 crashes to 20 crashes. In contrast, crashes attributed to 'Followed too close' decreased from 17 to 13, and incidents of 'Ran Stop Sign' dropped from 12 to 5.

Officer-Reported Primary Contributing Cause

Animal34 (14.4%)↑3.0%prior 33
Ran off road - left20 (8.5%)↑42.9%prior 14
FTYROW: From stop sign20 (8.5%)↑5.3%prior 19
Lost Control20 (8.5%)↑42.9%prior 14
Driver Distraction: Other interior distraction19 (8.1%)↑26.7%prior 15
Followed too close13 (5.5%)↓-23.5%prior 17
Ran off road - straight12 (5.1%)↓-25.0%prior 16
Driving too fast for conditions12 (5.1%)→0.0%prior 12
Other (explain in narrative): Other11 (4.7%)↑22.2%prior 9
FTYROW: Making left turn7 (3%)↑16.7%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

The majority of crashes in both periods occurred in clear weather and daylight conditions. In 2025, 61.0% of crashes happened in clear weather, compared to 65.6% in 2024. The proportion of crashes on dry road surfaces decreased from 69.1% in the prior period to 64.0% in the current period. Correspondingly, the share of crashes on wet, snowy, or icy roads increased from 18.0% to 21.6%. Crashes in dark conditions made up a slightly smaller share of the total, falling from 24.2% to 22.0%.

Weather

Clear144 (68.6%)
↓-14.3%prior 168
Cloudy37 (17.6%)
↑12.1%prior 33
Snow11 (5.2%)
↑57.1%prior 7
Rain9 (4.3%)
Freezing rain/drizzle5 (2.4%)
↓-16.7%prior 6
Fog, smoke, smog2 (1.0%)
Blowing Snow2 (1.0%)
↓-80.0%prior 10

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

Lighting

Daylight148 (69.5%)
↓-6.3%prior 158
Dark - roadway not lighted31 (14.6%)
↓-29.5%prior 44
Dark - roadway lighted19 (8.9%)
↑5.6%prior 18
Dusk7 (3.3%)
→0.0%prior 7
Dawn6 (2.8%)
↑20.0%prior 5
Dark - unknown roadway lighting2 (0.9%)

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

Road Surface

Dry151 (71.6%)
↓-14.7%prior 177
Wet20 (9.5%)
↑53.8%prior 13
Snow15 (7.1%)
→0.0%prior 15
Ice/frost15 (7.1%)
↓-11.8%prior 17
Gravel8 (3.8%)
→0.0%prior 8
Slush1 (0.5%)
Mud, dirt1 (0.5%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year: Chevrolet, Ford, and Toyota. However, the number of Chevrolet vehicles in crashes decreased from 93 to 67, and Fords decreased from 63 to 59. Examining the age of people involved in crashes, there was an increase in the 16-20 age group, from 48 individuals in 2024 to 53 in 2025. Conversely, the number of individuals aged 65 and older involved in crashes saw a notable decrease from 67 to 54.

Top Vehicle Makes (370 vehicles)

1
FORD59 (15.9%)
↓-6.3%prior 63
2
CHEV55 (14.9%)
↓-20.3%prior 69
3
TOYO20 (5.4%)
↑33.3%prior 15
4
TOYT18 (4.9%)
↓-21.7%prior 23
5
JEEP17 (4.6%)
→0.0%prior 17
6
DODG16 (4.3%)
↓-20.0%prior 20
7
GMC14 (3.8%)
↓-6.7%prior 15
8
HOND13 (3.5%)
↓-27.8%prior 18
9
CHEVROLET12 (3.2%)
↓-50.0%prior 24
10
BUIC12 (3.2%)
↑20.0%prior 10

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

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

Sex Distribution (238 persons with recorded sex)

Male150 (63.0%)
↑9.5%prior 137
Female88 (37.0%)
↓-17.0%prior 106

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: 236
  • Total persons involved: 389
  • Total vehicles involved: 370

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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