Yearly Traffic Safety Analysis

175 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Clarke County, total traffic crashes decreased by 15.1% from 206 in 2021 to 175 in 2022. During this period, the number of fatalities fell from 4 to 2, while the number of injuries remained unchanged at 46. One of the most notable shifts was a 75% increase in crashes involving a driver under the influence, which rose from 4 incidents in 2021 to 7 in 2022.

175

▼ -15.0%was 206

Total Crash Events

2

▼ -50.0%was 4

Persons Killed

46

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 in traffic collisions in Clarke County was downward year-over-year. Total crashes fell from 206 in 2021 to 175 in 2022, a 15.1% reduction. While the number of injuries was stable at 46 for both years, traffic fatalities were halved, decreasing from 4 to 2.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 4↓-50.0%

1

Pedestrians Injured

Prior: 0→%

45

Motorists Injured

Prior: 46↓-2.2%

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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Monday with 35 incidents, a change from Thursday (34 crashes) in the prior year. The peak hour also shifted slightly earlier, moving from 4 p.m. (19 crashes) in 2021 to 3 p.m. (17 crashes) in 2022.

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

While the total number of fatal crashes remained constant at 2 for both years, the fatality rate per 100 crashes increased from 0.97 to 1.14 due to the lower overall crash volume in 2022. The number of persons killed decreased from 4 to 2. Crashes resulting in serious injuries doubled, increasing from 3 in 2021 to 6 in 2022, while minor injury crashes fell from 21 to 12.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
→0.0%prior 2
Serious Injury6serious injury crashes3.4%
↑100.0%prior 3
Minor Injury12minor injury crashes6.9%
↓-42.9%prior 21
Possible Injury20possible injury crashes11.4%
↑25.0%prior 16
No Injury135no injury crashes77.1%
↓-17.7%prior 164

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 with animals remained the top contributing factor in both periods, though the count decreased from 49 crashes in 2021 to 38 in 2022. Losing control of the vehicle was the second-most cited factor in 2022 with 17 incidents, an increase from 15 incidents the previous year. Crashes attributed to following too closely also saw a slight increase, from 15 to 16 incidents year-over-year.

Officer-Reported Primary Contributing Cause

Animal38 (21.7%)↓-22.4%prior 49
Lost Control17 (9.7%)↑13.3%prior 15
Followed too close16 (9.1%)↑6.7%prior 15
Ran off road - straight13 (7.4%)↑30.0%prior 10
FTYROW: Making left turn11 (6.3%)↑37.5%prior 8
Other (explain in narrative): Other10 (5.7%)↑11.1%prior 9
FTYROW: From stop sign9 (5.1%)↓-18.2%prior 11
Driver Distraction: Other interior distraction9 (5.1%)↑12.5%prior 8
Driving too fast for conditions8 (4.6%)↑33.3%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner4 (2.3%)↓-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

Year-over-year, there was a shift in the conditions under which crashes occurred. While clear weather and dry roads were the most common conditions in both periods, their share of total crashes decreased in 2022. The proportion of crashes happening in the rain increased from 2.9% (6 crashes) in 2021 to 6.3% (11 crashes) in 2022. Similarly, crashes on wet roads rose from 9.2% (19 crashes) to 12% (21 crashes) of the total.

Weather

Clear90 (62.5%)
↓-23.7%prior 118
Cloudy26 (18.1%)
↑4.0%prior 25
Snow11 (7.6%)
↑10.0%prior 10
Rain11 (7.6%)
↑83.3%prior 6
Freezing rain/drizzle4 (2.8%)
Blowing Snow2 (1.4%)

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

Lighting

Daylight91 (63.2%)
↓-15.0%prior 107
Dark - roadway not lighted26 (18.1%)
↓-25.7%prior 35
Dark - roadway lighted18 (12.5%)
↑50.0%prior 12
Dawn6 (4.2%)
Dusk3 (2.1%)
↓-40.0%prior 5

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

Road Surface

Dry103 (71.0%)
↓-12.0%prior 117
Wet21 (14.5%)
↑10.5%prior 19
Snow11 (7.6%)
↓-15.4%prior 13
Gravel4 (2.8%)
↓-55.6%prior 9
Ice/frost3 (2.1%)
↓-40.0%prior 5
Slush3 (2.1%)

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

Vehicles & Demographics

The demographics of persons involved in crashes showed notable shifts. The number of individuals in the 16-20 age group fell sharply from 56 in 2021 to 27 in 2022. Conversely, involvement increased for the 26-34 age group (from 59 to 75 people) and the 65+ age group (from 29 to 43 people). Among vehicle makes involved in crashes, Ford and Chevrolet remained the most frequent in both years, though both saw a decrease in total counts from the prior year.

Top Vehicle Makes (267 vehicles)

1
FORD39 (14.6%)
↓-22.0%prior 50
2
CHEV32 (12%)
↓-8.6%prior 35
3
DODG20 (7.5%)
↑33.3%prior 15
4
CHEVROLET14 (5.2%)
↓-54.8%prior 31
5
BUIC10 (3.7%)
↑66.7%prior 6
6
CHRY9 (3.4%)
↑28.6%prior 7
7
RAM8 (3%)
8
TOYO8 (3%)
9
NR8 (3%)
↓-11.1%prior 9
10
FREIGHTLINER7 (2.6%)

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

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

Sex Distribution (240 persons with recorded sex)

Male152 (63.3%)
↓-6.7%prior 163
Female88 (36.7%)
↓-6.4%prior 94

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: 175
  • Total persons involved: 368
  • Total vehicles involved: 267

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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