Yearly Traffic Safety Analysis

132 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, O'Brien County recorded 132 total crashes, an 8.3% decrease from the 144 crashes reported in 2023. Despite the overall reduction in collisions, the most notable year-over-year shift was the appearance of fatal crashes, with two incidents resulting in two fatalities in 2024, compared to none in the prior year.

132

▼ -8.3%was 144

Total Crash Events

2

Persons Killed

68

▲ 13.3%was 60

Persons Injured

2

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 shows a decrease in the total number of crashes in O'Brien County, falling from 144 in 2023 to 132 in 2024. However, the severity of these incidents increased, with total injuries rising by 13.3% from 60 to 68, and total fatalities increasing from zero to two.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

2

Cyclists Injured

Prior: 0→%

66

Motorists Injured

Prior: 57↑15.8%

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 between the two periods. In 2024, the peak day for crashes was Friday with 27 incidents, a change from Tuesday, which saw 31 crashes in 2023. The peak hour also moved from the 3 p.m. hour in the prior year (20 crashes) to the 5 p.m. hour in the current year (13 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

Crash severity worsened in 2024 compared to 2023, with the fatal crash rate increasing from 0 to 1.52 per 100 crashes. The proportion of serious injury crashes also grew, accounting for 5.3% of all crashes in 2024, up from 3.5% in the previous year. Concurrently, the share of crashes involving only possible injuries decreased from 20.1% to 12.9%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.5%
Serious Injury7serious injury crashes5.3%
↑40.0%prior 5
Minor Injury19minor injury crashes14.4%
↑11.8%prior 17
Possible Injury17possible injury crashes12.9%
↓-41.4%prior 29
No Injury87no injury crashes65.9%
↓-6.5%prior 93

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

Failure to yield from a stop sign was the leading contributing factor in both years, with its count decreasing from 17 crashes in 2023 to 15 in 2024. Crashes attributed to 'Lost Control' experienced a significant reduction, dropping from 10 incidents to just 2, an 80% decrease in count. In contrast, 'Followed too close' incidents increased from 11 to 13, and 'Ran Stop Sign' crashes rose from 6 to 8.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign15 (11.4%)↓-11.8%prior 17
Followed too close13 (9.8%)↑18.2%prior 11
Ran Stop Sign8 (6.1%)↑33.3%prior 6
Animal8 (6.1%)↓-11.1%prior 9
Driving too fast for conditions8 (6.1%)↓-33.3%prior 12
Ran off road - left8 (6.1%)↑33.3%prior 6
FTYROW: At uncontrolled intersection7 (5.3%)↓-22.2%prior 9
Ran off road - straight7 (5.3%)
Other (explain in narrative): Other6 (4.5%)↓-14.3%prior 7
Improper Backing5 (3.8%)

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

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in clear weather and during daylight hours. The proportion of crashes on dry road surfaces increased from 63.2% in 2023 to 72.7% in 2024. Conversely, crashes on snowy roads represented a smaller share of the total, decreasing from 9.7% to 5.3%.

Weather

Clear88 (69.8%)
↓-5.4%prior 93
Cloudy26 (20.6%)
↓-3.7%prior 27
Snow5 (4.0%)
→0.0%prior 5
Fog, smoke, smog3 (2.4%)
↓-40.0%prior 5
Rain3 (2.4%)
Freezing rain/drizzle1 (0.8%)

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

Lighting

Daylight91 (71.7%)
↓-13.3%prior 105
Dark - roadway not lighted17 (13.4%)
↑21.4%prior 14
Dark - roadway lighted12 (9.4%)
↓-14.3%prior 14
Dusk5 (3.9%)
Dawn2 (1.6%)

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

Road Surface

Dry96 (76.2%)
↑5.5%prior 91
Ice/frost11 (8.7%)
↓-8.3%prior 12
Wet9 (7.1%)
↓-18.2%prior 11
Snow7 (5.6%)
↓-50.0%prior 14
Gravel3 (2.4%)
↓-57.1%prior 7

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved makes in both years, with Ford (47 crashes) overtaking Chevrolet (37 crashes) as the top make in 2024. The 16-20 age group was the most represented among people involved in crashes in both periods, though their count decreased from 53 to 44. The number of individuals in the 65+ age group involved in crashes saw a notable drop from 51 in 2023 to 32 in 2024.

Top Vehicle Makes (227 vehicles)

1
FORD47 (20.7%)
↓-2.1%prior 48
2
CHEV37 (16.3%)
↓-24.5%prior 49
3
DODG17 (7.5%)
↑41.7%prior 12
4
JEEP13 (5.7%)
↑8.3%prior 12
5
CHEVROLET10 (4.4%)
↓-37.5%prior 16
6
GMC9 (4%)
↓-40.0%prior 15
7
BUIC5 (2.2%)
↓-28.6%prior 7
8
FREIGHTLINER5 (2.2%)
→0.0%prior 5
9
CHRY5 (2.2%)
10
RAM5 (2.2%)

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

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

Sex Distribution (148 persons with recorded sex)

Male91 (61.5%)
↓-33.6%prior 137
Female57 (38.5%)
↓-36.7%prior 90

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: 132
  • Total persons involved: 246
  • Total vehicles involved: 227

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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