Yearly Traffic Safety Analysis

308 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Clay County, total traffic crashes increased by 4.8%, rising from 294 in the prior year to 308 in the current period. This overall increase was accompanied by a rise in both injuries and fatalities. The most significant change was the doubling of traffic-related fatalities from one to two year-over-year.

308

▲ 4.8%was 294

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

94

▲ 14.6%was 82

Persons Injured

2

▲ 100.0%was 1

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Clay County shows an increase in traffic collisions compared to the previous year. Total crashes rose from 294 to 308, while the number of people injured increased from 82 to 94. Additionally, the number of fatalities recorded in crashes increased from one to two.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 1↑100.0%

3

Pedestrians Injured

Prior: 1↑200.0%

2

Cyclists Injured

Prior: 1↑100.0%

89

Motorists Injured

Prior: 80↑11.3%

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 timing of crashes shifted slightly between the two periods. The peak day for crashes moved from Friday (56 crashes) in the prior year to Wednesday (58 crashes) in the current year. The peak hour also shifted one hour later, from 5 p.m. in the prior period to 6 p.m. in the current period, with both peak hours recording 28 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 worsened year-over-year, with fatal crashes doubling from one to two. Consequently, the fatal crash rate increased from 0.34 to 0.65 per 100 crashes. The proportion of crashes resulting in a possible injury grew from 8.2% to 11.4% of all incidents, while the share of crashes with no injuries decreased from 77.6% to 74.7%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
↑100.0%prior 1
Serious Injury6serious injury crashes1.9%
↓-14.3%prior 7
Minor Injury35minor injury crashes11.4%
↑2.9%prior 34
Possible Injury35possible injury crashes11.4%
↑45.8%prior 24
No Injury230no injury crashes74.7%
↑0.9%prior 228

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 a count of 61 in the current year compared to 60 in the prior year. The number of crashes attributed to 'Driving too fast for conditions' increased by 37.5%, from 16 to 22 incidents. Crashes involving 'Improper Backing' saw a significant rise in count, increasing from 5 to 16 year-over-year.

Officer-Reported Primary Contributing Cause

Animal61 (19.8%)↑1.7%prior 60
Other (explain in narrative): Other38 (12.3%)→0.0%prior 38
Driving too fast for conditions22 (7.1%)↑37.5%prior 16
FTYROW: From stop sign20 (6.5%)↓-13.0%prior 23
Improper Backing16 (5.2%)↑220.0%prior 5
Ran Stop Sign14 (4.5%)↑7.7%prior 13
FTYROW: Making left turn12 (3.9%)↑33.3%prior 9
Followed too close11 (3.6%)↓-45.0%prior 20
Ran off road - left10 (3.2%)↓-33.3%prior 15
Lost Control9 (2.9%)↓-43.8%prior 16

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

Road & Environmental Conditions

Year-over-year, crashes occurring on dry roads increased from 167 to 181, and those on wet roads rose from 17 to 24. Conversely, crashes on roads with snow or ice decreased from a combined 41 incidents to 32. Similarly, collisions in clear weather increased from 167 to 186, while crashes during daylight hours rose from 185 to 193.

Weather

Clear186 (74.7%)
↑11.4%prior 167
Cloudy37 (14.9%)
↓-2.6%prior 38
Rain9 (3.6%)
↓-25.0%prior 12
Snow7 (2.8%)
↓-22.2%prior 9
Fog, smoke, smog4 (1.6%)
Blowing Snow3 (1.2%)
Freezing rain/drizzle2 (0.8%)
Severe Winds1 (0.4%)

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

Lighting

Daylight193 (76.0%)
↑4.3%prior 185
Dark - roadway not lighted26 (10.2%)
↑23.8%prior 21
Dark - roadway lighted21 (8.3%)
↓-4.5%prior 22
Dusk6 (2.4%)
Dawn5 (2.0%)
Dark - unknown roadway lighting3 (1.2%)
↓-40.0%prior 5

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

Road Surface

Dry181 (72.1%)
↑8.4%prior 167
Wet24 (9.6%)
↑41.2%prior 17
Ice/frost16 (6.4%)
↓-20.0%prior 20
Snow16 (6.4%)
↓-23.8%prior 21
Gravel12 (4.8%)
↑33.3%prior 9
Slush2 (0.8%)

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

Vehicles & Demographics

Ford (96 vehicles) and Chevrolet (85 vehicles) remained the top two vehicle makes involved in crashes, with their counts staying relatively stable compared to the prior year. Despite an increase in total crashes, the number of people involved in collisions decreased from 651 to 537. This decline was observed across most age groups, most notably for individuals aged 26-34 (from 97 to 69) and 35-44 (from 100 to 63).

Top Vehicle Makes (514 vehicles)

1
FORD96 (18.7%)
↑2.1%prior 94
2
CHEV85 (16.5%)
↓-5.6%prior 90
3
BUIC25 (4.9%)
↑31.6%prior 19
4
JEEP24 (4.7%)
↑9.1%prior 22
5
DODG23 (4.5%)
↓-17.9%prior 28
6
CHRY21 (4.1%)
↑16.7%prior 18
7
CHEVROLET20 (3.9%)
↑11.1%prior 18
8
TOYO17 (3.3%)
↓-19.0%prior 21
9
RAM16 (3.1%)
↑45.5%prior 11
10
GMC15 (2.9%)
↓-31.8%prior 22

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

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

Sex Distribution (311 persons with recorded sex)

Male183 (58.8%)
↓-22.8%prior 237
Female128 (41.2%)
↓-39.3%prior 211

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: 308
  • Total persons involved: 537
  • Total vehicles involved: 514

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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