Yearly Traffic Safety Analysis

298 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Hardin County, total traffic crashes increased by 15.1% from 259 incidents in 2023 to 298 in 2024. This rise was accompanied by an increase in both injuries and fatalities. The most significant year-over-year change was the recording of four traffic-related fatalities in 2024, whereas none were reported in the prior year.

298

▲ 15.1%was 259

Total Crash Events

4

Persons Killed

85

▲ 28.8%was 66

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Hardin County worsened year-over-year, with total crashes rising from 259 to 298. The number of people injured in these incidents increased by 28.8%, from 66 in 2023 to 85 in 2024. Most notably, fatalities rose from zero to four during the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 0→%

84

Motorists Injured

Prior: 66↑27.3%

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 showed a distinct shift between the two periods. The peak day for collisions moved from Thursday (59 crashes) in 2023 to Tuesday (58 crashes) in 2024. A more pronounced change occurred in the peak hour, which shifted from the 7 AM morning commute (22 crashes) in the prior year to the 3 PM afternoon hour (28 crashes) in the current period.

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

Crash severity increased significantly in 2024, with three fatal crashes accounting for 1% of all incidents, compared to zero fatal crashes in 2023. The proportion of crashes resulting in serious injuries decreased from 4.6% to 1.7% year-over-year. However, the share of minor injury crashes more than doubled, increasing from 5.0% to 11.4% of all collisions.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1%
Serious Injury5serious injury crashes1.7%
↓-58.3%prior 12
Minor Injury34minor injury crashes11.4%
↑161.5%prior 13
Possible Injury32possible injury crashes10.7%
↓-5.9%prior 34
No Injury224no injury crashes75.2%
↑12.0%prior 200

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 primary contributing factor, with the count of such incidents increasing by 30.1% from 83 in 2023 to 108 in 2024. There was a notable increase in crashes attributed to drivers running stop signs, which jumped from 2 incidents to 13. Conversely, crashes due to a driver losing control saw a sharp 77.3% decrease in count, falling from 22 incidents to 5.

Officer-Reported Primary Contributing Cause

Animal108 (36.2%)↑30.1%prior 83
Other (explain in narrative): Other20 (6.7%)↑5.3%prior 19
FTYROW: From stop sign17 (5.7%)↑88.9%prior 9
Driver Distraction: Other interior distraction15 (5%)↑200.0%prior 5
Followed too close14 (4.7%)↑16.7%prior 12
Ran Stop Sign13 (4.4%)
Driving too fast for conditions13 (4.4%)↓-23.5%prior 17
Ran off road - straight13 (4.4%)↑30.0%prior 10
Driver Distraction: Inattentive/lost in thought8 (2.7%)
Ran off road - left8 (2.7%)↓-11.1%prior 9

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

Road & Environmental Conditions

The majority of crashes in both years occurred during daylight hours and on dry roads. The proportion of collisions happening in daylight increased from 47.1% in 2023 to 50.7% in 2024. Crashes on adverse road surfaces like ice, snow, or wet pavement became slightly less frequent, accounting for 13.1% of incidents in 2024 compared to 15.8% in the prior year.

Weather

Clear156 (72.9%)
↑15.6%prior 135
Cloudy33 (15.4%)
→0.0%prior 33
Fog, smoke, smog8 (3.7%)
Freezing rain/drizzle5 (2.3%)
Blowing Snow4 (1.9%)
↓-20.0%prior 5
Rain3 (1.4%)
↓-50.0%prior 6
Snow3 (1.4%)
↓-62.5%prior 8
Other (explain in narrative)1 (0.5%)
Severe Winds1 (0.5%)

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

Lighting

Daylight151 (69.6%)
↑23.8%prior 122
Dark - roadway not lighted44 (20.3%)
↓-17.0%prior 53
Dark - roadway lighted12 (5.5%)
↑20.0%prior 10
Dawn5 (2.3%)
→0.0%prior 5
Dusk4 (1.8%)
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry166 (76.9%)
↑9.9%prior 151
Wet16 (7.4%)
↑23.1%prior 13
Gravel11 (5.1%)
Ice/frost10 (4.6%)
↓-47.4%prior 19
Snow10 (4.6%)
↑66.7%prior 6
Slush3 (1.4%)

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

Vehicles & Demographics

The ranking of top vehicle makes involved in crashes changed, with Chevrolet (100 vehicles) surpassing Ford (66 vehicles) in 2024, a reversal from 2023 when Ford was the most common make with 81 vehicles. Regarding the age of persons involved, there was a significant drop in the 35-44 age group, from 103 individuals in 2023 to 68 in 2024. In contrast, the number of persons aged 65 and older involved in crashes rose from 55 to 66.

Top Vehicle Makes (417 vehicles)

1
CHEV77 (18.5%)
↑37.5%prior 56
2
FORD66 (15.8%)
↓-18.5%prior 81
3
GMC23 (5.5%)
↑130.0%prior 10
4
CHEVROLET23 (5.5%)
↑76.9%prior 13
5
DODG19 (4.6%)
↑5.6%prior 18
6
JEEP19 (4.6%)
↑46.2%prior 13
7
NISS17 (4.1%)
↑70.0%prior 10
8
HOND12 (2.9%)
↑50.0%prior 8
9
KIA10 (2.4%)
10
BUIC9 (2.2%)
↓-25.0%prior 12

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

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

Sex Distribution (215 persons with recorded sex)

Male137 (63.7%)
↓-28.6%prior 192
Female78 (36.3%)
↓-40.5%prior 131

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: 298
  • Total persons involved: 430
  • Total vehicles involved: 417

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

ThatCarHitMe.com · An Injuria.ai Company