Yearly Traffic Safety Analysis

305 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Buchanan County, total traffic crashes increased from 282 in 2023 to 305 in 2024, an 8.2% rise. Despite this increase in overall incidents, the number of resulting injuries and fatalities saw a notable decrease. The total number of people injured fell by 29.4% from 109 to 77, and DUI-related crashes dropped from 14 to 5, a 64.3% decrease year-over-year.

305

▲ 8.2%was 282

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

77

▼ -29.4%was 109

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 an increase in the total number of crashes, which rose by 8.2% from 282 to 305 year-over-year. However, the severity of these incidents trended downward, as total fatalities decreased from 2 to 1, and total injuries fell from 109 to 77.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

0

Other Killed

Prior: 0→0.0%

2

Cyclists Injured

Prior: 0→%

74

Motorists Injured

Prior: 109↓-32.1%

1

Other Injured

Prior: 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. While Thursday remained the peak day for crashes in both years (53 in 2023, 54 in 2024), the peak hour shifted earlier from 7 a.m. in the prior year to 6 a.m. in the current year. Notably, the number of crashes occurring on Tuesdays increased from 36 to 52 year-over-year.

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 decreased compared to the prior year. The fatal crash rate was halved, dropping from 0.71% to 0.33% of all crashes. The proportion of crashes resulting in any form of injury also declined, from 29.1% in 2023 to 20.3% in 2024, driven largely by a reduction in minor injury crashes, which fell from 40 to 23 incidents.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
↓-50.0%prior 2
Serious Injury9serious injury crashes3%
↑12.5%prior 8
Minor Injury23minor injury crashes7.5%
↓-42.5%prior 40
Possible Injury30possible injury crashes9.8%
↓-11.8%prior 34
No Injury242no injury crashes79.3%
↑22.2%prior 198

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 of such incidents increasing from 94 to 112. The ranking of the top factors remained relatively stable, with 'Ran off road - left' and 'Lost Control' following. A significant change was observed in crashes attributed to 'FTYROW: From stop sign', which more than doubled in count from 8 incidents in 2023 to 19 in 2024.

Officer-Reported Primary Contributing Cause

Animal112 (36.7%)↑19.1%prior 94
Ran off road - left21 (6.9%)↑5.0%prior 20
Lost Control20 (6.6%)↑17.6%prior 17
FTYROW: From stop sign19 (6.2%)↑137.5%prior 8
Driving too fast for conditions16 (5.2%)↑23.1%prior 13
Followed too close15 (4.9%)↑7.1%prior 14
Other (explain in narrative): Other13 (4.3%)↓-7.1%prior 14
Driver Distraction: Other interior distraction10 (3.3%)↑11.1%prior 9
Ran off road - straight10 (3.3%)↓-41.2%prior 17
FTYROW: Making left turn8 (2.6%)↓-27.3%prior 11

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 saw minor shifts year-over-year. The proportion of crashes occurring in clear weather decreased from 51.1% to 44.3% of all incidents, with a corresponding increase in crashes during cloudy conditions from 21 to 32. Similarly, crashes on dry road surfaces declined as a percentage of the total, while those on wet surfaces increased slightly from 16 to 19 incidents.

Weather

Clear135 (66.2%)
↓-6.3%prior 144
Cloudy32 (15.7%)
↑52.4%prior 21
Snow11 (5.4%)
↑10.0%prior 10
Rain8 (3.9%)
↑14.3%prior 7
Fog, smoke, smog6 (2.9%)
Freezing rain/drizzle4 (2.0%)
↓-66.7%prior 12
Severe Winds4 (2.0%)
Blowing Snow3 (1.5%)
Other (explain in narrative)1 (0.5%)

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

Lighting

Daylight139 (66.2%)
↑9.4%prior 127
Dark - roadway not lighted47 (22.4%)
↓-7.8%prior 51
Dark - roadway lighted13 (6.2%)
↑18.2%prior 11
Dusk5 (2.4%)
Dawn3 (1.4%)
↓-57.1%prior 7
Dark - unknown roadway lighting3 (1.4%)

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

Road Surface

Dry139 (67.8%)
↓-2.8%prior 143
Wet19 (9.3%)
↑18.8%prior 16
Ice/frost18 (8.8%)
↓-5.3%prior 19
Snow13 (6.3%)
↑44.4%prior 9
Gravel11 (5.4%)
↑37.5%prior 8
Slush3 (1.5%)
Mud, dirt2 (1.0%)

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

Vehicles & Demographics

Among vehicles involved in crashes, Ford and Chevrolet were tied as the most common makes in 2024, each with 72 vehicles, a shift from the prior year when Chevrolet led with 75. An analysis of persons involved shows a significant demographic trend: while the number of people in every adult age group over 20 decreased, the number of persons aged 16-20 involved in crashes increased from 58 to 69.

Top Vehicle Makes (414 vehicles)

1
FORD72 (17.4%)
↑10.8%prior 65
2
CHEV72 (17.4%)
↓-4.0%prior 75
3
GMC20 (4.8%)
↑81.8%prior 11
4
DODG16 (3.9%)
↓-38.5%prior 26
5
BUIC16 (3.9%)
↑77.8%prior 9
6
JEEP15 (3.6%)
↓-6.3%prior 16
7
TOYO14 (3.4%)
↑16.7%prior 12
8
FREIGHTLINER14 (3.4%)
↑75.0%prior 8
9
TOYT14 (3.4%)
↑27.3%prior 11
10
CHEVROLET13 (3.1%)
↑30.0%prior 10

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

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

Sex Distribution (228 persons with recorded sex)

Male140 (61.4%)
↓-40.7%prior 236
Female88 (38.6%)
↓-33.3%prior 132

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 10, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 305
  • Total persons involved: 431
  • Total vehicles involved: 414

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 10, 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