Yearly Traffic Safety Analysis

614 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Clinton County, total crashes decreased slightly from 633 in 2023 to 614 in 2024, a 3.0% reduction. Despite this overall drop in incidents, the number of fatalities rose from 5 to 7. A notable shift occurred in crashes involving a driver under the influence (DUI), which increased by 34.3% from 35 incidents in 2023 to 47 in 2024.

614

▼ -3.0%was 633

Total Crash Events

7

▲ 40.0%was 5

Persons Killed

183

▼ -14.5%was 214

Persons Injured

4

▼ -20.0%was 5

Fatal Crash Events

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Clinton County saw a modest year-over-year decline, falling by 3.0% from 633 in 2023 to 614 in 2024. While the total number of crashes decreased, the number of people killed in those crashes increased from 5 to 7. Conversely, the total number of injuries reported dropped by 14.5%, from 214 to 183.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

7

Motorists Killed

Prior: 4↑75.0%

0

Other Killed

Prior: 0→0.0%

7

Pedestrians Injured

Prior: 7→0.0%

6

Cyclists Injured

Prior: 6→0.0%

169

Motorists Injured

Prior: 200↓-15.5%

1

Other Injured

Prior: 1→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. The day with the most crashes moved from Thursday (117 crashes) in 2023 to Wednesday (101 crashes) in 2024. Similarly, the peak hour for collisions shifted slightly earlier, from 4 p.m. in the prior year (56 crashes) to 3 p.m. in the current year (52 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, with the fatal crash rate decreasing from 0.79 per 100 crashes in 2023 to 0.65 in 2024. Despite a lower fatal crash rate, total fatalities increased from 5 to 7. The proportion of crashes resulting in serious injuries grew from 2.7% to 3.4%, while the share of crashes with no injuries increased from 69.0% to 73.3% of all incidents.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.7%
↓-20.0%prior 5
Serious Injury21serious injury crashes3.4%
↑23.5%prior 17
Minor Injury59minor injury crashes9.6%
↓-14.5%prior 69
Possible Injury80possible injury crashes13%
↓-23.8%prior 105
No Injury450no injury crashes73.3%
↑3.0%prior 437

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, with the count increasing from 121 in 2023 to 131 in 2024. The ranking of other top factors shifted, with 'Failure to yield from a stop sign' moving up to the second-ranked cause after its count rose from 45 to 52. Conversely, 'Lost Control' incidents decreased in count from 55 to 41, dropping from the second to the third-ranked factor. 'Followed too close' incidents saw a notable reduction in count, falling from 39 to 25.

Officer-Reported Primary Contributing Cause

Animal131 (21.3%)↑8.3%prior 121
FTYROW: From stop sign52 (8.5%)↑15.6%prior 45
Lost Control41 (6.7%)↓-25.5%prior 55
Ran off road - left38 (6.2%)↑52.0%prior 25
Ran Stop Sign35 (5.7%)↓-7.9%prior 38
Other (explain in narrative): Other31 (5%)↑6.9%prior 29
Ran off road - straight30 (4.9%)↑66.7%prior 18
Driving too fast for conditions28 (4.6%)↑47.4%prior 19
Followed too close25 (4.1%)↓-35.9%prior 39
FTYROW: Making left turn20 (3.3%)↑42.9%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather and daylight conditions remained proportionally stable across both years, constituting the majority of incidents. However, there was a notable shift in crashes related to road surface conditions. The proportion of crashes occurring on dry roads decreased from 63.3% of all crashes in 2023 to 58.3% in 2024. Concurrently, the share of crashes on roads with ice or frost increased from 2.5% to 4.9% of the total.

Weather

Clear370 (74.4%)
↓-1.3%prior 375
Cloudy68 (13.7%)
↓-13.9%prior 79
Rain27 (5.4%)
↑35.0%prior 20
Snow23 (4.6%)
↓-23.3%prior 30
Fog, smoke, smog5 (1.0%)
→0.0%prior 5
Blowing Snow2 (0.4%)
Freezing rain/drizzle1 (0.2%)
↓-93.3%prior 15
Severe Winds1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight328 (65.0%)
↓-4.1%prior 342
Dark - roadway lighted69 (13.7%)
↑6.2%prior 65
Dark - roadway not lighted64 (12.7%)
↓-28.9%prior 90
Dusk20 (4.0%)
→0.0%prior 20
Dawn12 (2.4%)
↑20.0%prior 10
Dark - unknown roadway lighting12 (2.4%)
↑140.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry358 (72.0%)
↓-10.7%prior 401
Wet62 (12.5%)
↑8.8%prior 57
Ice/frost30 (6.0%)
↑87.5%prior 16
Snow23 (4.6%)
↓-34.3%prior 35
Gravel16 (3.2%)
↑23.1%prior 13
Slush7 (1.4%)
Water (standing or moving)1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Chevrolet and Ford vehicles collectively accounting for the top two spots in both years. The number of Ford vehicles involved increased from 160 to 172, while the total number of Chevrolet vehicles decreased from 221 to 202. Analysis of persons involved shows a slight shift in age demographics, with the 65+ age group's representation increasing from 16.0% of the total in 2023 to 17.3% in 2024.

Top Vehicle Makes (967 vehicles)

1
FORD172 (17.8%)
↑7.5%prior 160
2
CHEV148 (15.3%)
↓-7.5%prior 160
3
CHEVROLET54 (5.6%)
↓-11.5%prior 61
4
GMC43 (4.4%)
↓-20.4%prior 54
5
JEEP34 (3.5%)
↓-17.1%prior 41
6
TOYO33 (3.4%)
↓-8.3%prior 36
7
DODG31 (3.2%)
↓-16.2%prior 37
8
TOYT29 (3%)
↓-43.1%prior 51
9
NISS29 (3%)
↓-17.1%prior 35
10
CHRY29 (3%)
↑107.1%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (576 persons with recorded sex)

Male343 (59.5%)
↓-33.7%prior 517
Female233 (40.5%)
↓-41.6%prior 399

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 614
  • Total persons involved: 1,008
  • Total vehicles involved: 967

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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