Yearly Traffic Safety Analysis

158 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Union County, total traffic crashes increased by 22.5% from 129 in 2020 to 158 in 2021. Despite the rise in total incidents, the most significant year-over-year change was a positive one: traffic fatalities dropped from 3 in the prior period to zero in the current period. However, the number of crashes attributed to collisions with animals quadrupled, becoming the leading contributing factor in 2021.

158

22.5%was 129

Total Crash Events

0

-100.0%was 3

Persons Killed

59

9.3%was 54

Persons Injured

0

-100.0%was 3

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Union County shows an increase in traffic incidents year-over-year. Total crashes rose from 129 in 2020 to 158 in 2021, representing a 22.5% increase. The number of people injured also saw a slight uptick, growing 9.3% from 54 to 59.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 3-100.0%

1

Pedestrians Injured

Prior: 2-50.0%

1

Cyclists Injured

Prior: 0%

57

Motorists Injured

Prior: 529.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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 2021, the peak day for crashes was Tuesday with 29 incidents, a change from Thursday (25 incidents) in 2020. The busiest hour also moved later in the day, from noon (12 crashes) in 2020 to the 3 p.m. hour (17 crashes) in 2021, reflecting a higher concentration of incidents during the afternoon commute.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, their overall severity decreased in 2021. There were no fatal crashes, a significant improvement from the 3 fatal incidents recorded in 2020. However, the count of serious injury crashes doubled from 3 to 6. Crashes resulting in possible injuries decreased from 29 to 22, while no-injury crashes increased from 80 to 114, comprising 72.2% of all incidents in 2021 compared to 62.0% in the prior year.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes3.8%
100.0%prior 3
Minor Injury16minor injury crashes10.1%
14.3%prior 14
Possible Injury22possible injury crashes13.9%
-24.1%prior 29
No Injury114no injury crashes72.2%
42.5%prior 80

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals became the leading contributing factor in 2021, with the count of these incidents increasing 300% from 7 to 28. 'Failure to yield from a stop sign' remained a top cause, growing from 12 crashes in 2020 to 19 in 2021. 'Followed too close' also increased in count from 11 to 16 incidents. Notably, crashes attributed to 'Driving too fast for conditions' saw a seven-fold increase, rising from 1 to 8 incidents year-over-year.

Officer-Reported Primary Contributing Cause

Animal28 (17.7%)300.0%prior 7
FTYROW: From stop sign19 (12%)58.3%prior 12
Followed too close16 (10.1%)45.5%prior 11
Other (explain in narrative): Other12 (7.6%)50.0%prior 8
Ran off road - straight9 (5.7%)28.6%prior 7
Driving too fast for conditions8 (5.1%)
FTYROW: Making left turn7 (4.4%)-30.0%prior 10
Ran off road - left7 (4.4%)-30.0%prior 10
Lost Control7 (4.4%)-22.2%prior 9
Ran Stop Sign5 (3.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While most crashes in both years occurred during daylight on dry, clear roads, there was a notable increase in incidents under adverse conditions in 2021. The number of crashes on dark, unlighted roadways more than doubled from 12 to 29. Similarly, crashes on snowy roads increased from 5 to 12, and incidents reported during snowy weather rose from 4 to 7.

Weather

Clear106 (73.1%)
15.2%prior 92
Cloudy21 (14.5%)
5.0%prior 20
Rain9 (6.2%)
Snow7 (4.8%)
Fog, smoke, smog1 (0.7%)
Blowing Snow1 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight94 (65.7%)
-1.1%prior 95
Dark - roadway not lighted29 (20.3%)
141.7%prior 12
Dark - roadway lighted14 (9.8%)
27.3%prior 11
Dusk3 (2.1%)
Dawn2 (1.4%)
Dark - unknown roadway lighting1 (0.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry106 (73.1%)
3.9%prior 102
Wet13 (9.0%)
62.5%prior 8
Snow12 (8.3%)
140.0%prior 5
Gravel9 (6.2%)
Ice/frost5 (3.4%)
0.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the most common vehicle makes involved in crashes across both years, with the count of Chevrolet vehicles increasing from 54 to 74. The age demographics of people involved in crashes also shifted. The 16-20 age group saw a decrease from 55 to 43 individuals, while involvement increased for the 21-25 age group (from 26 to 43 people) and the 26-34 age group (from 34 to 53 people).

Top Vehicle Makes (262 vehicles)

1
FORD45 (17.2%)
-6.3%prior 48
2
CHEV44 (16.8%)
25.7%prior 35
3
CHEVROLET30 (11.5%)
57.9%prior 19
4
DODGE12 (4.6%)
5
JEEP11 (4.2%)
-8.3%prior 12
6
DODG11 (4.2%)
0.0%prior 11
7
GMC11 (4.2%)
-15.4%prior 13
8
BUIC9 (3.4%)
80.0%prior 5
9
CHRY9 (3.4%)
10
NISS6 (2.3%)
-14.3%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (215 persons with recorded sex)

Male123 (57.2%)
0.8%prior 122
Female92 (42.8%)
8.2%prior 85

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 158
  • Total persons involved: 339
  • Total vehicles involved: 262

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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Union County, IA Crash Report — 2021 | ThatCarHitMe.com