Yearly Traffic Safety Analysis

217 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, there were 217 total crashes, a slight decrease of 0.9% from 219 crashes in 2021. However, total fatalities saw a significant increase of 150%, rising from 2 in 2021 to 5 in 2022. This marks a concerning shift despite the overall stability in crash volume.

217

▼ -0.9%was 219

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

57

▼ -8.1%was 62

Persons Injured

5

▲ 400.0%was 1

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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

The overall trend for total crashes in the county remained relatively stable year-over-year, with a minor decrease of 2 crashes from 219 in 2021 to 217 in 2022. Despite this, total fatalities increased substantially by 150%, from 2 to 5, indicating a worsening outcome for crash severity. Total injuries decreased by 8.1%, from 62 to 57.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 2↑150.0%

1

Pedestrians Injured

Prior: 1→0.0%

56

Motorists Injured

Prior: 60↓-6.7%

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 peak day for crashes shifted from Friday in 2021 (53 crashes) to Monday in 2022 (42 crashes), while Friday crashes decreased to 28. The peak hour also shifted from 4 PM in 2021 (19 crashes) to 5 PM in 2022 (16 crashes). This indicates a change in the temporal distribution of crash occurrences.

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

The fatal crash rate significantly increased from 0.5% in 2021 to 2.3% in 2022, with the number of fatal crashes rising from 1 to 5. While serious injury crashes slightly decreased from 8 to 7, minor injury crashes saw a more substantial reduction from 25 to 14. The proportion of crashes resulting in no injury increased from 74.4% to 78.3%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes2.3%
↑400.0%prior 1
Serious Injury7serious injury crashes3.2%
↓-12.5%prior 8
Minor Injury14minor injury crashes6.5%
↓-44.0%prior 25
Possible Injury21possible injury crashes9.7%
↓-4.5%prior 22
No Injury170no injury crashes78.3%
↑4.3%prior 163

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

Animal-related crashes remained the most frequent contributing factor, decreasing slightly from 40 crashes in 2021 to 39 in 2022. Crashes attributed to 'Ran off road - straight' increased by 5 counts, from 26 to 31, while 'Lost Control' increased by 2 counts, from 28 to 30. Notably, 'Followed too close' increased from 8 to 13 crashes, whereas 'Driver Distraction: Other interior distraction' decreased from 10 to 5 crashes.

Officer-Reported Primary Contributing Cause

Animal39 (18%)↓-2.5%prior 40
Ran off road - straight31 (14.3%)↑19.2%prior 26
Lost Control30 (13.8%)↑7.1%prior 28
Driving too fast for conditions27 (12.4%)↑8.0%prior 25
Followed too close13 (6%)↑62.5%prior 8
Ran off road - left13 (6%)↑30.0%prior 10
Other (explain in narrative): Other6 (2.8%)↑20.0%prior 5
Driver Distraction: Other interior distraction5 (2.3%)↓-50.0%prior 10
Swerving/Evasive Action4 (1.8%)
Ran Stop Sign4 (1.8%)↓-20.0%prior 5

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

Road & Environmental Conditions

There was a notable shift in weather conditions, with crashes during 'Freezing rain/drizzle' decreasing significantly from 16 to 4, while 'Rain' related crashes increased from 10 to 16. Road surface conditions also changed, with 'Dry' surface crashes decreasing from 125 to 114, and 'Wet' surface crashes increasing substantially from 16 to 33. In terms of lighting, crashes occurring at 'Dusk' decreased from 11 to 4, while 'Dark - roadway not lighted' crashes saw a slight increase from 56 to 59.

Weather

Clear120 (65.2%)
↑8.1%prior 111
Cloudy26 (14.1%)
↓-18.8%prior 32
Rain16 (8.7%)
↑60.0%prior 10
Snow7 (3.8%)
↓-30.0%prior 10
Blowing Snow6 (3.3%)
↓-25.0%prior 8
Freezing rain/drizzle4 (2.2%)
↓-75.0%prior 16
Fog, smoke, smog4 (2.2%)
Severe Winds1 (0.5%)

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

Lighting

Daylight106 (57.6%)
↓-5.4%prior 112
Dark - roadway not lighted59 (32.1%)
↑5.4%prior 56
Dawn7 (3.8%)
Dark - roadway lighted6 (3.3%)
↑20.0%prior 5
Dusk4 (2.2%)
↓-63.6%prior 11
Dark - unknown roadway lighting2 (1.1%)

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

Road Surface

Dry114 (62.0%)
↓-8.8%prior 125
Wet33 (17.9%)
↑106.3%prior 16
Snow14 (7.6%)
↓-30.0%prior 20
Ice/frost12 (6.5%)
↓-45.5%prior 22
Gravel8 (4.3%)
↑33.3%prior 6
Slush3 (1.6%)

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

Vehicles & Demographics

The age distribution of persons involved in crashes saw shifts, with the 35-44 age group experiencing a significant increase from 54 to 97 persons, becoming the most represented group. Conversely, the 26-34 age group saw a decrease from 81 to 67 persons, and the 16-20 age group decreased from 33 to 22 persons. In terms of vehicle makes, Ford remained the most frequently involved make, though its count slightly decreased from 43 to 42, while Freightliner involvement increased from 19 to 27 vehicles.

Top Vehicle Makes (296 vehicles)

1
FORD42 (14.2%)
↓-2.3%prior 43
2
CHEV34 (11.5%)
↑41.7%prior 24
3
FREIGHTLINER27 (9.1%)
↑42.1%prior 19
4
CHEVROLET20 (6.8%)
↓-20.0%prior 25
5
NR12 (4.1%)
↑50.0%prior 8
6
TOYOTA10 (3.4%)
↓-9.1%prior 11
7
GMC9 (3%)
↑12.5%prior 8
8
VOLVO9 (3%)
↑28.6%prior 7
9
PETERBILT9 (3%)
→0.0%prior 9
10
DODG9 (3%)
→0.0%prior 9

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

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

Sex Distribution (266 persons with recorded sex)

Male192 (72.2%)
↓-2.0%prior 196
Female74 (27.8%)
↑19.4%prior 62

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: 217
  • Total persons involved: 418
  • Total vehicles involved: 296

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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