Yearly Traffic Safety Analysis

633 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Clinton County, total traffic crashes remained nearly stable, with 633 incidents in 2023 compared to 636 in 2022, a decrease of less than 1%. While overall crash volume was consistent, the most notable year-over-year change was a significant reduction in traffic fatalities, which fell from 9 in 2022 to 5 in 2023. Total injuries also declined from 232 to 214.

633

▼ -0.5%was 636

Total Crash Events

5

▼ -44.4%was 9

Persons Killed

214

▼ -7.8%was 232

Persons Injured

5

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Clinton County show a stable volume of incidents year-over-year, with a minor decrease of three crashes from 636 to 633. However, the severity of these crashes lessened, evidenced by a 44.4% decrease in fatalities (from 9 to 5) and a 7.8% decrease in total injuries (from 232 to 214).

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 9↓-55.6%

0

Other Killed

Prior: 0→0.0%

7

Pedestrians Injured

Prior: 5↑40.0%

6

Cyclists Injured

Prior: 3↑100.0%

200

Motorists Injured

Prior: 223↓-10.3%

1

Other Injured

Prior: 1→0.0%

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 timing of crashes showed some shifts between the two periods. In 2023, Thursday was the peak day for crashes with 117 incidents, a change from 2022 when Tuesday saw the most crashes at 106. The peak hour for collisions, however, remained consistent, with the 4 p.m. hour recording the highest number of crashes in both years (56 incidents).

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

The severity of crashes showed mixed changes year-over-year. While the number of fatal crashes remained identical at 5, the number of resulting fatalities dropped from 9 to 5. The proportion of crashes involving serious injuries increased slightly from 2.4% (15 crashes) in 2022 to 2.7% (17 crashes) in 2023. Conversely, crashes resulting in minor injuries decreased from 76 to 69, and the share of no-injury crashes rose slightly from 68.2% to 69.0%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.8%
→0.0%prior 5
Serious Injury17serious injury crashes2.7%
↑13.3%prior 15
Minor Injury69minor injury crashes10.9%
↓-9.2%prior 76
Possible Injury105possible injury crashes16.6%
↓-0.9%prior 106
No Injury437no injury crashes69%
↑0.7%prior 434

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 an animal remained the top contributing factor in both periods, with the count increasing from 108 in 2022 to 121 in 2023. "Lost Control" also saw an increase in crash count, rising from 47 to 55 incidents. In contrast, crashes attributed to failure to yield from a stop sign decreased from 54 to 45, and incidents of running a stop sign fell from 45 to 38. The number of crashes due to following too closely was unchanged at 39.

Officer-Reported Primary Contributing Cause

Animal121 (19.1%)↑12.0%prior 108
Lost Control55 (8.7%)↑17.0%prior 47
FTYROW: From stop sign45 (7.1%)↓-16.7%prior 54
Followed too close39 (6.2%)→0.0%prior 39
Ran Stop Sign38 (6%)↓-15.6%prior 45
Other (explain in narrative): Other29 (4.6%)↓-32.6%prior 43
Ran off road - left25 (3.9%)↑47.1%prior 17
Driving too fast for conditions19 (3%)↓-24.0%prior 25
Ran off road - straight18 (2.8%)↓-35.7%prior 28
Ran Traffic Signal18 (2.8%)↑12.5%prior 16

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

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with most incidents in both periods occurring in daylight and on dry roads. In 2023, the proportion of crashes in clear weather decreased slightly to 59.2% from 63.7% in 2022. Correspondingly, there was an increase in crashes reported during snow, which rose from 18 incidents in 2022 to 30 in 2023, while crashes in rainy conditions decreased from 31 to 20.

Weather

Clear375 (71.3%)
↓-7.4%prior 405
Cloudy79 (15.0%)
↑8.2%prior 73
Snow30 (5.7%)
↑66.7%prior 18
Rain20 (3.8%)
↓-35.5%prior 31
Freezing rain/drizzle15 (2.9%)
↑66.7%prior 9
Fog, smoke, smog5 (1.0%)
↓-28.6%prior 7
Other (explain in narrative)1 (0.2%)
Blowing Snow1 (0.2%)

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

Lighting

Daylight342 (64.3%)
↑0.6%prior 340
Dark - roadway not lighted90 (16.9%)
↑1.1%prior 89
Dark - roadway lighted65 (12.2%)
↓-22.6%prior 84
Dusk20 (3.8%)
↓-9.1%prior 22
Dawn10 (1.9%)
↓-37.5%prior 16
Dark - unknown roadway lighting5 (0.9%)

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

Road Surface

Dry401 (76.1%)
↓-3.4%prior 415
Wet57 (10.8%)
↓-9.5%prior 63
Snow35 (6.6%)
↑16.7%prior 30
Ice/frost16 (3.0%)
↓-36.0%prior 25
Gravel13 (2.5%)
↓-7.1%prior 14
Slush3 (0.6%)
Mud, dirt1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes were consistent, with Ford and Chevrolet vehicles being the most common in both years. The number of Ford vehicles in crashes decreased from 182 to 160, while Chevrolet vehicles remained stable. A notable demographic shift occurred in the age of persons involved in crashes; the 65+ age group became the largest cohort in 2023 with 199 individuals, an increase from 182 in 2022. Meanwhile, the 26-34 age group saw its involvement decrease from 218 to 193 individuals.

Top Vehicle Makes (1,019 vehicles)

1
CHEV160 (15.7%)
↑11.1%prior 144
2
FORD160 (15.7%)
↓-12.1%prior 182
3
CHEVROLET61 (6%)
↓-18.7%prior 75
4
GMC54 (5.3%)
↓-10.0%prior 60
5
TOYT51 (5%)
↑24.4%prior 41
6
JEEP41 (4%)
↑2.5%prior 40
7
DODG37 (3.6%)
↑5.7%prior 35
8
TOYO36 (3.5%)
↑50.0%prior 24
9
NISS35 (3.4%)
↑6.1%prior 33
10
BUIC28 (2.7%)
↓-12.5%prior 32

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

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

Sex Distribution (916 persons with recorded sex)

Male517 (56.4%)
→0.0%prior 517
Female399 (43.6%)
↓-1.0%prior 403

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: 633
  • Total persons involved: 1,420
  • Total vehicles involved: 1,019

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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