Yearly Traffic Safety Analysis

81 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Keokuk County recorded 81 total crashes, a 12.0% decrease from the 92 crashes reported in 2021. While overall crashes and the number of injuries both declined, the count of crashes involving a driver under the influence of alcohol increased by 75%, rising from 4 incidents in 2021 to 7 in 2022.

81

▼ -12.0%was 92

Total Crash Events

0

Persons Killed

29

▼ -21.6%was 37

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

Crash trends in Keokuk County showed a year-over-year decline. Total crashes decreased by 12.0%, from 92 in 2021 to 81 in 2022. Similarly, the number of people injured in these incidents fell by 21.6%, from 37 to 29, while fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

29

Motorists Injured

Prior: 37↓-21.6%

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 Keokuk County shifted between 2021 and 2022. The peak hour for crashes remained stable at 6 p.m. in both years, with 9 incidents recorded in that hour for each period. However, the peak day for crashes moved from Friday (19 crashes) in 2021 to a tie between Thursday and Saturday (14 crashes each) 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

Crash severity saw minor shifts year-over-year, with zero fatal crashes recorded in both 2021 and 2022. The number of serious injury crashes was unchanged at 5 incidents in both periods. The proportion of crashes resulting in any injury (serious, minor, or possible) increased slightly from 29.3% of all crashes in 2021 to 30.8% in 2022, even as the absolute number of crashes and injuries decreased.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes6.2%
→0.0%prior 5
Minor Injury10minor injury crashes12.3%
↑25.0%prior 8
Possible Injury10possible injury crashes12.3%
↓-28.6%prior 14
No Injury56no injury crashes69.1%
↓-13.8%prior 65

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 an animal remained the top contributing factor in both periods, accounting for 28 crashes in 2022 compared to 29 in 2021. The count of crashes attributed to 'Lost Control' increased by 60%, from 5 to 8 incidents, and 'Followed too close' incidents rose from 3 to 5. Conversely, crashes where 'Ran Stop Sign' was a factor decreased in count from 7 to 3, and incidents involving 'Driving too fast for conditions' fell from 6 to 3.

Officer-Reported Primary Contributing Cause

Animal28 (34.6%)↓-3.4%prior 29
Lost Control8 (9.9%)↑60.0%prior 5
Followed too close5 (6.2%)
Ran off road - straight5 (6.2%)→0.0%prior 5
Driver Distraction: Other interior distraction4 (4.9%)↓-20.0%prior 5
Other (explain in narrative): Other4 (4.9%)
Swerving/Evasive Action3 (3.7%)
Driving too fast for conditions3 (3.7%)↓-50.0%prior 6
Ran Stop Sign3 (3.7%)↓-57.1%prior 7
Made improper turn2 (2.5%)

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

Road & Environmental Conditions

The proportion of crashes occurring on dry road surfaces increased from 42.4% in 2021 to 54.3% in 2022. Correspondingly, the number of crashes on adverse surfaces like wet, snow, or ice dropped from 24 incidents in 2021 to 12 incidents in 2022. The distribution of crashes by lighting conditions showed a minor shift, with the share of crashes in daylight decreasing from 47.8% to 43.2%, while the share of crashes in unlighted dark conditions increased from 14.1% to 18.5%.

Weather

Clear39 (69.6%)
↓-9.3%prior 43
Cloudy14 (25.0%)
→0.0%prior 14
Rain3 (5.4%)

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

Lighting

Daylight35 (62.5%)
↓-20.5%prior 44
Dark - roadway not lighted15 (26.8%)
↑15.4%prior 13
Dark - roadway lighted5 (8.9%)
Dawn1 (1.8%)

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

Road Surface

Dry44 (78.6%)
↑12.8%prior 39
Wet5 (8.9%)
↓-44.4%prior 9
Ice/frost4 (7.1%)
Gravel1 (1.8%)
Slush1 (1.8%)
Snow1 (1.8%)
↓-85.7%prior 7

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

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Chevrolet, Ford, and Dodge leading in both years, though the total count for each decreased in 2022. The age distribution of persons involved in crashes shifted, with an increase in the 26-34 age group (from 28 to 35 people) and the 55-64 age group (from 20 to 28 people). Conversely, involvement of the 16-20 age group decreased from 24 people in 2021 to 18 in 2022.

Top Vehicle Makes (112 vehicles)

1
CHEV21 (18.8%)
↑31.3%prior 16
2
FORD16 (14.3%)
↓-30.4%prior 23
3
DODG6 (5.4%)
↓-14.3%prior 7
4
TOYO5 (4.5%)
5
DODGE5 (4.5%)
↓-16.7%prior 6
6
CHEVROLET5 (4.5%)
↓-66.7%prior 15
7
JEEP4 (3.6%)
8
CADI3 (2.7%)
9
KENWORTH3 (2.7%)
10
RAM3 (2.7%)

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

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

Sex Distribution (109 persons with recorded sex)

Male76 (69.7%)
↑15.2%prior 66
Female33 (30.3%)
↓-15.4%prior 39

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: 81
  • Total persons involved: 168
  • Total vehicles involved: 112

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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