Yearly Traffic Safety Analysis

138 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, UNION County recorded 138 vehicle crashes, a decrease from the 158 crashes reported in 2021. This represents a 12.7% year-over-year reduction in total collisions. Alongside the overall decline, crashes involving a driver under the influence of alcohol decreased by 50%, from 8 incidents in 2021 to 4 in 2022.

138

▼ -12.7%was 158

Total Crash Events

0

Persons Killed

42

▼ -28.8%was 59

Persons Injured

0

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic collisions in UNION County saw a downward trend from 2021 to 2022. The total number of crashes fell by 12.7%, from 158 to 138. Similarly, the number of people injured in these incidents decreased by 28.8%, from 59 in 2021 to 42 in 2022. There were no fatalities recorded in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

42

Motorists Injured

Prior: 57↓-26.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in UNION County showed a notable shift between 2021 and 2022. While Tuesday remained the most common day for crashes in both years (29 in 2021, 31 in 2022), the peak hour for incidents changed significantly. In 2021, the most crashes occurred at 3 p.m. with 17 incidents, but in 2022, the peak shifted to the morning rush hour at 7 a.m., which saw 14 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity outcomes improved from 2021 to 2022, with no fatal crashes reported in either year. The proportion of crashes resulting in an injury of any kind decreased, falling from 27.8% of all incidents in 2021 to 22.4% in 2022. This was driven by a drop in crashes with possible injuries, which fell from 22 incidents in 2021 to 12 in 2022.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes3.6%
↓-16.7%prior 6
Minor Injury14minor injury crashes10.1%
↓-12.5%prior 16
Possible Injury12possible injury crashes8.7%
↓-45.5%prior 22
No Injury107no injury crashes77.5%
↓-6.1%prior 114

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained the leading contributing factor in both periods, with counts of 28 in 2021 and 25 in 2022. 'Failure to Yield Right of Way: From stop sign' saw a significant 47.4% decrease in count, falling from 19 incidents in 2021 to 10 in 2022, though it remained the second-ranked factor. Crashes attributed to 'Followed too close' also declined sharply, dropping by 62.5% from 16 incidents to 6, and falling from the third-ranked factor in 2021.

Officer-Reported Primary Contributing Cause

Animal25 (18.1%)↓-10.7%prior 28
FTYROW: From stop sign10 (7.2%)↓-47.4%prior 19
Ran off road - left8 (5.8%)↑14.3%prior 7
Driving too fast for conditions7 (5.1%)↓-12.5%prior 8
Lost Control6 (4.3%)↓-14.3%prior 7
Followed too close6 (4.3%)↓-62.5%prior 16
Made improper turn6 (4.3%)
Driver Distraction: Other interior distraction5 (3.6%)
FTYROW: At uncontrolled intersection5 (3.6%)
Ran off road - straight5 (3.6%)↓-44.4%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The environmental conditions under which crashes occurred were largely consistent year-over-year. In both 2022 and 2021, the majority of incidents happened in clear weather and during daylight hours. Crashes on dry road surfaces were most common in both periods, though the number of incidents on snowy roads was halved, decreasing from 12 in 2021 to 6 in 2022.

Weather

Clear98 (73.7%)
↓-7.5%prior 106
Cloudy21 (15.8%)
→0.0%prior 21
Rain8 (6.0%)
↓-11.1%prior 9
Snow3 (2.3%)
↓-57.1%prior 7
Blowing Snow2 (1.5%)
Fog, smoke, smog1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight86 (64.7%)
↓-8.5%prior 94
Dark - roadway not lighted29 (21.8%)
→0.0%prior 29
Dark - roadway lighted9 (6.8%)
↓-35.7%prior 14
Dawn8 (6.0%)
Dark - unknown roadway lighting1 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry106 (79.7%)
→0.0%prior 106
Wet12 (9.0%)
↓-7.7%prior 13
Gravel8 (6.0%)
↓-11.1%prior 9
Snow6 (4.5%)
↓-50.0%prior 12
Ice/frost1 (0.8%)
↓-80.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top makes of vehicles involved in crashes saw a minor shift in ranking, with 'CHEV' (53 vehicles) becoming more frequent than 'FORD' (37 vehicles) in 2022, reversing the order from 2021. An analysis of persons involved in crashes reveals a significant change in age demographics; the 16-20 age group became the most frequently involved group in 2022 with 64 individuals, up from 43 in the prior year. Conversely, the 26-34 age group, which was highly represented in 2021 with 53 individuals, saw its involvement decrease to 22 in 2022.

Top Vehicle Makes (222 vehicles)

1
CHEV53 (23.9%)
↑20.5%prior 44
2
FORD37 (16.7%)
↓-17.8%prior 45
3
DODG17 (7.7%)
↑54.5%prior 11
4
DODGE11 (5%)
↓-8.3%prior 12
5
CHEVROLET8 (3.6%)
↓-73.3%prior 30
6
CHRY6 (2.7%)
↓-33.3%prior 9
7
TOYO6 (2.7%)
↑20.0%prior 5
8
BUIC5 (2.3%)
↓-44.4%prior 9
9
KIA5 (2.3%)
10
JEEP5 (2.3%)
↓-54.5%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (197 persons with recorded sex)

Male116 (58.9%)
↓-5.7%prior 123
Female81 (41.1%)
↓-12.0%prior 92

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 138
  • Total persons involved: 283
  • Total vehicles involved: 222

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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