Yearly Traffic Safety Analysis

141 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Union County recorded 141 vehicle crashes, a 2.2% increase from the 138 crashes documented in 2022. The most significant year-over-year change was the increase in traffic fatalities, which rose from zero in the prior period to six in the current period. These fatalities occurred across three separate crash events in 2023.

141

▲ 2.2%was 138

Total Crash Events

6

Persons Killed

55

▲ 31.0%was 42

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The total number of crashes in Union County remained relatively stable, increasing by 2.2% from 138 in 2022 to 141 in 2023. However, the severity of these incidents worsened, as total injuries rose by 31% from 42 to 55, and total fatalities increased from zero to six.

Vulnerable Road User Casualties

6

Motorists Killed

Prior: 0→%

55

Motorists Injured

Prior: 42↑31.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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 2023, the peak days for crashes were Mondays and Wednesdays, each with 24 incidents, a change from 2022 when Tuesday was the peak day with 31 crashes. The peak hour also moved from the morning commute at 7 a.m. in 2022 (14 crashes) to the afternoon at 3 p.m. in 2023 (14 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased significantly in 2023 compared to 2022. The county recorded three fatal crashes resulting in six deaths, up from zero fatal crashes and zero deaths in the prior year. While the number of crashes classified as 'Serious Injury' decreased from 5 to 2, the count of 'Possible Injury' crashes more than doubled from 12 in 2022 to 29 in 2023. Consequently, the share of crashes with no injuries decreased from 77.5% to 68.1%.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.1%
Serious Injury2serious injury crashes1.4%
↓-60.0%prior 5
Minor Injury11minor injury crashes7.8%
↓-21.4%prior 14
Possible Injury29possible injury crashes20.6%
↑141.7%prior 12
No Injury96no injury crashes68.1%
↓-10.3%prior 107

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained the top contributing factor in both periods, with a stable count of 25 crashes. The second most common factor, 'Failure to yield from a stop sign,' saw its crash count increase by 90%, from 10 incidents in 2022 to 19 in 2023. Crashes attributed to 'Followed too close' also rose, from 6 to 11, an 83% increase in count, making it the third leading factor in the current period.

Officer-Reported Primary Contributing Cause

Animal25 (17.7%)→0.0%prior 25
FTYROW: From stop sign19 (13.5%)↑90.0%prior 10
Followed too close11 (7.8%)↑83.3%prior 6
Other (explain in narrative): Other10 (7.1%)
FTYROW: Making left turn7 (5%)
Ran off road - straight7 (5%)↑40.0%prior 5
Driver Distraction: Other interior distraction7 (5%)↑40.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner6 (4.3%)
Ran off road - left6 (4.3%)↓-25.0%prior 8
Made improper turn5 (3.5%)↓-16.7%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and on dry roads, with proportions remaining similar year-over-year. There was a notable shift in lighting conditions, with crashes in 'Dark - roadway not lighted' conditions decreasing from 29 incidents in 2022 to 19 in 2023. Crashes on adverse road surfaces like wet or snow-covered roads also saw a slight decrease from 19 incidents in 2022 to 16 in 2023.

Weather

Clear95 (75.4%)
↓-3.1%prior 98
Cloudy20 (15.9%)
↓-4.8%prior 21
Rain4 (3.2%)
↓-50.0%prior 8
Freezing rain/drizzle3 (2.4%)
Snow2 (1.6%)
Sleet, hail1 (0.8%)
Blowing Snow1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight90 (70.9%)
↑4.7%prior 86
Dark - roadway not lighted19 (15.0%)
↓-34.5%prior 29
Dark - roadway lighted10 (7.9%)
↑11.1%prior 9
Dusk4 (3.1%)
Dawn2 (1.6%)
↓-75.0%prior 8
Dark - unknown roadway lighting2 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry103 (81.1%)
↓-2.8%prior 106
Gravel8 (6.3%)
→0.0%prior 8
Snow6 (4.7%)
→0.0%prior 6
Wet6 (4.7%)
↓-50.0%prior 12
Slush4 (3.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Chevrolet and Ford continued to be the two most common vehicle makes involved in crashes, with counts of 54 and 47 respectively in 2023, up from 53 and 37 in the prior year. Analyzing the demographics of persons involved, the number of females increased from 81 to 98, while the number of males remained stable. The 65+ age group saw an increase in involvement, rising from 34 individuals in 2022 to 42 in 2023.

Top Vehicle Makes (232 vehicles)

1
CHEV54 (23.3%)
↑1.9%prior 53
2
FORD47 (20.3%)
↑27.0%prior 37
3
GMC14 (6%)
↑180.0%prior 5
4
JEEP11 (4.7%)
↑120.0%prior 5
5
DODG11 (4.7%)
↓-35.3%prior 17
6
CHEVROLET10 (4.3%)
↑25.0%prior 8
7
BUIC10 (4.3%)
↑100.0%prior 5
8
TOYT6 (2.6%)
9
CHRY6 (2.6%)
→0.0%prior 6
10
DODGE5 (2.2%)
↓-54.5%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (211 persons with recorded sex)

Male113 (53.6%)
↓-2.6%prior 116
Female98 (46.4%)
↑21.0%prior 81

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 141
  • Total persons involved: 326
  • Total vehicles involved: 232

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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