Yearly Traffic Safety Analysis

146 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Union County recorded 146 total crashes, a 3.5% increase from the 141 crashes reported in 2023. While the overall crash volume saw a slight rise, the most notable shift was a significant decrease in traffic fatalities, which fell from 6 in the prior period to 1 in the current period. Conversely, crashes involving driving under the influence (DUI) increased from 3 to 10 year-over-year.

146

▲ 3.5%was 141

Total Crash Events

1

▼ -83.3%was 6

Persons Killed

41

▼ -25.5%was 55

Persons Injured

1

▼ -66.7%was 3

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Union County show a slight increase in total incidents, rising from 141 in 2023 to 146 in 2024. Despite this increase in overall collisions, the outcomes were less severe, as the number of people injured decreased from 55 to 41 and total fatalities fell from 6 to 1.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 6↓-83.3%

41

Motorists Injured

Prior: 55↓-25.5%

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 temporal patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Friday with 32 incidents, a change from 2023 when Monday and Wednesday shared the highest frequency with 24 crashes each. The peak hour for collisions also moved slightly earlier in the day, from 3 p.m. (14 crashes) in the prior year to a tie between 1 p.m. and 2 p.m. (14 crashes each) in the current year.

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

The severity of crashes was lower in 2024 compared to the previous year. Fatal crashes decreased from 3 incidents (2.1% of all crashes) in 2023 to 1 incident (0.7% of all crashes) in 2024. While the count of serious injury crashes increased from 2 to 4, crashes involving possible injuries saw a significant drop from 29 to 11. As a result, the proportion of crashes with no reported injuries increased from 68.1% to 77.4% of all incidents.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
↓-66.7%prior 3
Serious Injury4serious injury crashes2.7%
↑100.0%prior 2
Minor Injury17minor injury crashes11.6%
↑54.5%prior 11
Possible Injury11possible injury crashes7.5%
↓-62.1%prior 29
No Injury113no injury crashes77.4%
↑17.7%prior 96

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

The leading contributing factors showed some changes year-over-year. Collisions involving an animal remained a primary cause but the count of such incidents decreased from 25 in 2023 to 20 in 2024. A significant increase was observed in crashes attributed to 'driving too fast for conditions,' which rose from 4 incidents to 13. In contrast, crashes caused by 'followed too close' saw a substantial reduction, falling from 11 in the prior year to just 2 in the current year.

Officer-Reported Primary Contributing Cause

Animal20 (13.7%)↓-20.0%prior 25
FTYROW: From stop sign17 (11.6%)↓-10.5%prior 19
Driving too fast for conditions13 (8.9%)
Driver Distraction: Other interior distraction8 (5.5%)↑14.3%prior 7
Operating vehicle in an reckless, erratic, careless, negligent manner8 (5.5%)↑33.3%prior 6
Lost Control6 (4.1%)
Other (explain in narrative): Other6 (4.1%)↓-40.0%prior 10
Ran off road - left6 (4.1%)→0.0%prior 6
Made improper turn5 (3.4%)→0.0%prior 5
Swerving/Evasive Action4 (2.7%)

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

Road & Environmental Conditions

While most crashes in both periods occurred in clear weather and daylight, there was a notable increase in incidents related to adverse road conditions. Crashes on snowy road surfaces rose from 6 in 2023 to 19 in 2024, and collisions during snowfall increased from 2 to 9. Despite an overall rise in total crashes, the number of incidents occurring on dry roads decreased from 103 to 94.

Weather

Clear101 (75.9%)
↑6.3%prior 95
Cloudy16 (12.0%)
↓-20.0%prior 20
Snow9 (6.8%)
Blowing Snow3 (2.3%)
Freezing rain/drizzle1 (0.8%)
Rain1 (0.8%)
Sleet, hail1 (0.8%)
Fog, smoke, smog1 (0.8%)

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

Lighting

Daylight101 (74.8%)
↑12.2%prior 90
Dark - roadway not lighted17 (12.6%)
↓-10.5%prior 19
Dark - roadway lighted12 (8.9%)
↑20.0%prior 10
Dawn3 (2.2%)
Dusk1 (0.7%)
Dark - unknown roadway lighting1 (0.7%)

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

Road Surface

Dry94 (70.7%)
↓-8.7%prior 103
Snow19 (14.3%)
↑216.7%prior 6
Wet9 (6.8%)
↑50.0%prior 6
Gravel8 (6.0%)
→0.0%prior 8
Ice/frost3 (2.3%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet and Ford vehicles accounting for the highest numbers in both years. A significant demographic shift occurred among persons involved in crashes, particularly in the 16-20 age group, which saw its count decrease from 68 individuals in 2023 to 32 in 2024. In contrast, the 55-64 age group saw an increase in representation, from 31 individuals in the prior year to 36 in the current year.

Top Vehicle Makes (246 vehicles)

1
FORD49 (19.9%)
↑4.3%prior 47
2
CHEV48 (19.5%)
↓-11.1%prior 54
3
GMC16 (6.5%)
↑14.3%prior 14
4
CHEVROLET13 (5.3%)
↑30.0%prior 10
5
DODG12 (4.9%)
↑9.1%prior 11
6
JEEP9 (3.7%)
↓-18.2%prior 11
7
KIA7 (2.8%)
8
TOYT7 (2.8%)
↑16.7%prior 6
9
DODGE6 (2.4%)
↑20.0%prior 5
10
NISS6 (2.4%)
↑20.0%prior 5

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

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

Sex Distribution (161 persons with recorded sex)

Male101 (62.7%)
↓-10.6%prior 113
Female60 (37.3%)
↓-38.8%prior 98

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: 146
  • Total persons involved: 252
  • Total vehicles involved: 246

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

ThatCarHitMe.com · An Injuria.ai Company