Yearly Traffic Safety Analysis

286 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Clayton County recorded 286 total crashes, a 3.1% decrease from the 295 crashes documented in 2022. Despite the overall reduction in collisions, the number of fatalities increased from two in the prior year to three in the current period. Total injuries saw a notable decline, dropping from 73 to 61.

286

▼ -3.1%was 295

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

61

▼ -16.4%was 73

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crash trends in Clayton County were mixed year-over-year. While total crashes decreased by 3.1% from 295 to 286, and injuries fell by 16.4%, the number of fatalities rose from two to three. This indicates a decrease in overall crash frequency but an increase in the severity of the deadliest incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 2↑50.0%

1

Pedestrians Injured

Prior: 0→%

60

Motorists Injured

Prior: 73↓-17.8%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The most frequent day for crashes moved from Friday in 2022, with 56 incidents, to Sunday in 2023, with 50 incidents. The peak hour for collisions also shifted slightly earlier, from 6 p.m. in the prior year (25 crashes) to 5 p.m. in the current year (25 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened slightly in 2023 compared to 2022. The number of fatal crashes increased from two to three, raising the fatal crash rate from 0.68 to 1.05 per 100 crashes. The count of serious injury crashes decreased from eight to seven, and possible injury crashes fell from 24 to 22. The proportion of crashes resulting in no injuries remained stable at approximately 79% in both years.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1%
↑50.0%prior 2
Serious Injury7serious injury crashes2.4%
↓-12.5%prior 8
Minor Injury27minor injury crashes9.4%
→0.0%prior 27
Possible Injury22possible injury crashes7.7%
↓-8.3%prior 24
No Injury227no injury crashes79.4%
↓-3.0%prior 234

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals were the leading contributing factor in both years, though the count of these incidents decreased from 146 in 2022 to 126 in 2023. The second and third most common factors, "Lost Control" and "Ran off road - left," both saw an increase in their incident counts. Crashes attributed to losing control rose from 26 to 29, while those involving running off the road to the left increased from 18 to 25.

Officer-Reported Primary Contributing Cause

Animal126 (44.1%)↓-13.7%prior 146
Lost Control29 (10.1%)↑11.5%prior 26
Ran off road - left25 (8.7%)↑38.9%prior 18
Other (explain in narrative): Other15 (5.2%)↑25.0%prior 12
Driving too fast for conditions13 (4.5%)↑44.4%prior 9
Ran off road - straight10 (3.5%)↓-16.7%prior 12
Driver Distraction: Other interior distraction6 (2.1%)→0.0%prior 6
Driver Distraction: Inattentive/lost in thought5 (1.7%)
FTYROW: From stop sign4 (1.4%)↓-50.0%prior 8
Made improper turn4 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes predominantly occurred in clear weather and daylight conditions in both 2023 and 2022, with little change in their proportions. However, there was a significant shift in road surface conditions, as crashes on icy or frosty roads more than doubled, increasing from four in 2022 to 11 in 2023. In contrast, crashes on wet surfaces saw a decrease from 19 incidents to 13.

Weather

Clear115 (69.7%)
↑6.5%prior 108
Cloudy25 (15.2%)
↑4.2%prior 24
Snow12 (7.3%)
↑20.0%prior 10
Rain5 (3.0%)
↓-37.5%prior 8
Freezing rain/drizzle3 (1.8%)
Fog, smoke, smog2 (1.2%)
Blowing Snow2 (1.2%)
Other (explain in narrative)1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight118 (69.4%)
↑4.4%prior 113
Dark - roadway not lighted35 (20.6%)
↑9.4%prior 32
Dark - roadway lighted10 (5.9%)
↑66.7%prior 6
Dawn4 (2.4%)
Dusk2 (1.2%)
Dark - unknown roadway lighting1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry113 (67.3%)
↑13.0%prior 100
Gravel16 (9.5%)
→0.0%prior 16
Wet13 (7.7%)
↓-31.6%prior 19
Snow13 (7.7%)
↓-18.8%prior 16
Ice/frost11 (6.5%)
Slush1 (0.6%)
Other (explain in narrative)1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The primary vehicle makes involved in crashes, Chevrolet and Ford, remained the top two in both 2023 and 2022, showing consistency in vehicle involvement. An analysis of the age of persons involved in crashes reveals a shift in demographics. The number of individuals in the 55-64 age group increased from 73 to 89 year-over-year, while the 65+ age group saw a decrease from 98 to 82.

Top Vehicle Makes (358 vehicles)

1
CHEV68 (19%)
↓-10.5%prior 76
2
FORD61 (17%)
↓-12.9%prior 70
3
CHEVROLET31 (8.7%)
↑158.3%prior 12
4
DODG21 (5.9%)
↑16.7%prior 18
5
GMC18 (5%)
↓-21.7%prior 23
6
JEEP17 (4.7%)
↑6.3%prior 16
7
TOYT11 (3.1%)
↑22.2%prior 9
8
DODGE9 (2.5%)
↓-25.0%prior 12
9
CHRY9 (2.5%)
10
HOND6 (1.7%)
↓-40.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (330 persons with recorded sex)

Male195 (59.1%)
↓-2.0%prior 199
Female135 (40.9%)
↓-9.4%prior 149

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 286
  • Total persons involved: 561
  • Total vehicles involved: 358

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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