Yearly Traffic Safety Analysis

45 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Wayne County recorded 45 total crashes, a 30.8% decrease from the 65 crashes reported in 2024. The most significant year-over-year change was the reduction in traffic fatalities, which fell from 3 in the prior period to 0 in the current period. Total injuries also saw a decrease from 19 to 14.

45

▼ -30.8%was 65

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

14

▼ -26.3%was 19

Persons Injured

0

▼ -100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 safety trends in Wayne County improved year-over-year. Total crashes declined by 30.8%, from 65 in 2024 to 45 in 2025. This downward trend was also reflected in crash outcomes, with total injuries falling from 19 to 14 and fatalities dropping from 3 to 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 3↓-100.0%

0

Other Killed

Prior: 0→0.0%

13

Motorists Injured

Prior: 18↓-27.8%

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 shifted between the two periods. In 2025, the highest number of crashes occurred on Wednesdays (9 crashes), a change from 2024 when Saturday was the peak day with 13 crashes. The peak hour for collisions also moved later into the evening, from 6 PM in the prior period (8 crashes) to 8 PM in the current period (5 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

Crash severity improved significantly in 2025, with fatal crashes dropping to zero from two in the previous year. The proportion of crashes resulting in serious injuries also decreased, falling from 10.8% of total crashes (7 incidents) in 2024 to 4.4% (2 incidents) in 2025. While the overall share of crashes involving any injury was similar across both periods, minor injury crashes increased from 2 to 6, while possible injury crashes decreased from 10 to 5.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.4%
↓-71.4%prior 7
Minor Injury6minor injury crashes13.3%
↑200.0%prior 2
Possible Injury5possible injury crashes11.1%
↓-50.0%prior 10
No Injury32no injury crashes71.1%
↓-27.3%prior 44

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 leading contributing factor in both periods, though the count decreased from 16 crashes in 2024 to 14 in 2025. The number of crashes attributed to 'Ran off road - straight' also declined from 6 to 4. Conversely, crashes related to 'FTYROW: From stop sign' and 'Lost Control' both increased, from 1 to 3 incidents each. Notably, 'Driver Distraction: Manual operation of an electronic communication device', which was a factor in 3 crashes in 2024, was not among the top listed factors in 2025.

Officer-Reported Primary Contributing Cause

Animal14 (31.1%)↓-12.5%prior 16
Ran off road - straight4 (8.9%)↓-33.3%prior 6
FTYROW: From stop sign3 (6.7%)
Lost Control3 (6.7%)
Followed too close3 (6.7%)
FTYROW: Making left turn2 (4.4%)
Driver Distraction: Other interior distraction2 (4.4%)
Operating vehicle in an reckless, erratic, careless, negligent manner2 (4.4%)
Other (explain in narrative): Other2 (4.4%)
FTYROW: At uncontrolled intersection1 (2.2%)

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

Road & Environmental Conditions

Crashes in both periods predominantly occurred in clear weather and on dry roads, with the proportions remaining stable year-over-year. The most notable shift was in lighting conditions. While the share of crashes in daylight was similar, incidents on dark, unlighted roadways saw a proportional decrease, accounting for 12.3% of crashes in 2024 but only 4.4% in 2025.

Weather

Clear30 (93.8%)
↓-25.0%prior 40
Blowing sand, soil, dirt1 (3.1%)
Cloudy1 (3.1%)
↓-80.0%prior 5

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

Lighting

Daylight26 (81.3%)
↓-25.7%prior 35
Dark - roadway not lighted2 (6.3%)
↓-75.0%prior 8
Dusk2 (6.3%)
Dark - roadway lighted1 (3.1%)
Dawn1 (3.1%)

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

Road Surface

Dry28 (87.5%)
↓-30.0%prior 40
Gravel2 (6.3%)
Ice/frost1 (3.1%)
Wet1 (3.1%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both periods, though their counts decreased from 25 and 18 vehicles in 2024 to 16 and 7 in 2025, respectively. A significant demographic shift occurred among persons involved in crashes; the 16-20 age group's involvement dropped from 19 individuals to 5. In contrast, the 26-34 age group was the most represented in 2025 with 15 individuals, and the 65+ age group remained high with 13 individuals involved.

Top Vehicle Makes (64 vehicles)

1
FORD16 (25%)
↓-36.0%prior 25
2
CHEV5 (7.8%)
↓-58.3%prior 12
3
NISS5 (7.8%)
4
TOYT4 (6.3%)
5
HONDA3 (4.7%)
6
JEEP3 (4.7%)
7
CHEVROLET2 (3.1%)
↓-66.7%prior 6
8
PONT2 (3.1%)
9
FRHT2 (3.1%)
10
DODG2 (3.1%)
↓-75.0%prior 8

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

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

Sex Distribution (34 persons with recorded sex)

Male27 (79.4%)
↓-12.9%prior 31
Female7 (20.6%)
↓-61.1%prior 18

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: 45
  • Total persons involved: 65
  • Total vehicles involved: 64

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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