Yearly Traffic Safety Analysis

65 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Wayne County, total traffic crashes increased from 61 in 2023 to 65 in 2024, a rise of 6.6%. While total injuries saw a slight decrease, the most significant year-over-year change was the emergence of traffic fatalities. The county recorded three fatalities in two separate crashes during 2024, compared to zero fatalities in the prior year.

65

▲ 6.6%was 61

Total Crash Events

3

Persons Killed

19

▼ -9.5%was 21

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (3) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Wayne County indicates a rising trend in both volume and severity. Overall crashes increased by 6.6% from 61 in 2023 to 65 in 2024. Critically, this period saw the introduction of fatal crashes, with three fatalities recorded in 2024 where none had occurred in the previous year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 0→%

18

Motorists Injured

Prior: 21↓-14.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2024, the peak day for crashes was Saturday with 13 incidents, a change from Friday, which was the peak day in 2023 with 15 incidents. The peak hour also moved from late morning (11 a.m.) in 2023 to the evening at 6 p.m. in 2024, which saw 8 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity notably worsened in 2024 compared to 2023. The county experienced two fatal crashes, accounting for 3.1% of all incidents, after having zero fatal crashes in the prior year. The share of serious injury crashes also increased, rising from 3.3% of total crashes in 2023 to 10.8% in 2024, even as the total number of injuries slightly decreased from 21 to 19.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes3.1%
Serious Injury7serious injury crashes10.8%
↑250.0%prior 2
Minor Injury2minor injury crashes3.1%
↓-75.0%prior 8
Possible Injury10possible injury crashes15.4%
↑42.9%prior 7
No Injury44no injury crashes67.7%
→0.0%prior 44

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, though the count decreased slightly from 17 crashes in 2023 to 16 in 2024. The number of crashes attributed to 'Ran off road - straight' decreased from 10 to 6. A notable change was the drop in 'Lost Control' incidents from 8 in 2023 to just 1 in 2024, while crashes involving 'Driver Distraction: Manual operation of an electronic communication device' appeared as a factor in 2024 with 3 incidents.

Officer-Reported Primary Contributing Cause

Animal16 (24.6%)↓-5.9%prior 17
Ran off road - straight6 (9.2%)↓-40.0%prior 10
Driver Distraction: Manual operation of an electronic communication device3 (4.6%)
Followed too close3 (4.6%)
FTYROW: At uncontrolled intersection3 (4.6%)
Other (explain in narrative): Other3 (4.6%)
Ran Stop Sign3 (4.6%)
Failed to keep in proper lane2 (3.1%)
Driver Distraction: Exterior distraction2 (3.1%)
Improper Backing2 (3.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes under adverse conditions saw a general decrease in 2024 compared to 2023. Incidents occurring in dark, unlighted conditions were halved, dropping from 16 crashes in 2023 to 8 in 2024. Similarly, crashes on gravel roads decreased from 8 to 3. In both years, the majority of crashes occurred in daylight on dry roads.

Weather

Clear40 (80.0%)
↓-4.8%prior 42
Cloudy5 (10.0%)
→0.0%prior 5
Other (explain in narrative)2 (4.0%)
Rain2 (4.0%)
Severe Winds1 (2.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight35 (70.0%)
↑9.4%prior 32
Dark - roadway not lighted8 (16.0%)
↓-50.0%prior 16
Dark - roadway lighted4 (8.0%)
Dawn2 (4.0%)
Dusk1 (2.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry40 (80.0%)
↑14.3%prior 35
Wet4 (8.0%)
↓-20.0%prior 5
Gravel3 (6.0%)
↓-62.5%prior 8
Ice/frost2 (4.0%)
Snow1 (2.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Ford was the most common vehicle make involved in crashes in both years, with its count increasing from 17 in 2023 to 25 in 2024. Reviewing the age of persons involved, the 16-20 age group remained one of the most represented groups in both periods. However, the involvement of the 26-34 age group decreased from 21 individuals in 2023 to 14 in 2024, while the 35-44 age group's involvement doubled from 7 to 14.

Top Vehicle Makes (95 vehicles)

1
FORD25 (26.3%)
↑47.1%prior 17
2
CHEV12 (12.6%)
↓-25.0%prior 16
3
DODG8 (8.4%)
4
CHEVROLET6 (6.3%)
5
GMC5 (5.3%)
6
CHRY5 (5.3%)
7
BUIC4 (4.2%)
8
RAM3 (3.2%)
9
JEEP2 (2.1%)
10
NISSAN2 (2.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (49 persons with recorded sex)

Male31 (63.3%)
↓-40.4%prior 52
Female18 (36.7%)
↓-43.8%prior 32

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 65
  • Total persons involved: 98
  • Total vehicles involved: 95

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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Wayne County, IA Crash Report — 2024 | ThatCarHitMe.com