Yearly Traffic Safety Analysis

336 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Boone County recorded 336 total crashes, a 5.3% increase from the 319 crashes documented in 2023. Despite the rise in total collisions, the number of fatalities saw a significant decrease, falling from 7 in the prior year to 3 in the current period. The total number of injuries also declined from 126 in 2023 to 107 in 2024.

336

▲ 5.3%was 319

Total Crash Events

3

▼ -57.1%was 7

Persons Killed

107

▼ -15.1%was 126

Persons Injured

2

▼ -66.7%was 6

Fatal Crash Events

Note: "Persons Killed" (3) 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

Crash volume in Boone County increased year-over-year, with total incidents rising from 319 in 2023 to 336 in 2024, a 5.3% increase. However, the severity of these crashes trended downward, as total fatalities decreased from 7 to 3 and total injuries fell from 126 to 107.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 7↓-57.1%

1

Pedestrians Injured

Prior: 1→0.0%

2

Cyclists Injured

Prior: 1↑100.0%

104

Motorists Injured

Prior: 124↓-16.1%

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 shifted between the two periods. In 2024, Friday became the peak day for crashes with 62 incidents, a change from the prior year's peak on Monday, which saw 56 incidents. The peak hour also moved from the morning commute to the evening, with 5 PM recording the most crashes (29) in 2024, compared to 7 AM (26) in 2023.

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

Year-over-year data shows a decrease in crash severity. The share of fatal crashes dropped from 1.9% of all incidents in 2023 to 0.6% in 2024. Similarly, the proportion of crashes resulting in any level of injury (serious, minor, or possible) declined from 31.0% to 25.9%. Consequently, the share of property-damage-only crashes without injuries increased from 67.1% to 73.5% of all incidents.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
↓-66.7%prior 6
Serious Injury13serious injury crashes3.9%
→0.0%prior 13
Minor Injury36minor injury crashes10.7%
↓-23.4%prior 47
Possible Injury38possible injury crashes11.3%
↓-2.6%prior 39
No Injury247no injury crashes73.5%
↑15.4%prior 214

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, accounting for 93 crashes in both 2024 and 2023. While the top factor's count was stable, its share of total crashes fell from 29.2% to 27.7%. Several other factors saw notable shifts in count: crashes involving a vehicle running off the road to the left increased from 16 to 22, while incidents attributed to 'Lost Control' decreased from 24 to 17. Crashes linked to reckless or negligent driving more than doubled, rising from 5 to 11 incidents.

Officer-Reported Primary Contributing Cause

Animal93 (27.7%)→0.0%prior 93
FTYROW: From stop sign28 (8.3%)↓-6.7%prior 30
Ran off road - left22 (6.5%)↑37.5%prior 16
Lost Control17 (5.1%)↓-29.2%prior 24
Other (explain in narrative): Other15 (4.5%)↑50.0%prior 10
Followed too close13 (3.9%)→0.0%prior 13
Driver Distraction: Other interior distraction13 (3.9%)↑62.5%prior 8
Driving too fast for conditions13 (3.9%)→0.0%prior 13
FTYROW: At uncontrolled intersection11 (3.3%)↑10.0%prior 10
Ran Stop Sign11 (3.3%)↓-21.4%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

The distribution of crashes across environmental conditions remained broadly similar year-over-year. In 2024, 55.1% of crashes occurred in clear weather, down from a 57.4% share in 2023. Crashes in dark conditions (lighted or unlighted) decreased from 64 incidents in 2023 to 55 in 2024. The share of crashes on adverse road surfaces like wet or icy pavement was stable, accounting for approximately 16% of all incidents in both periods.

Weather

Clear185 (71.7%)
↑1.1%prior 183
Cloudy43 (16.7%)
↓-21.8%prior 55
Snow9 (3.5%)
↑12.5%prior 8
Rain6 (2.3%)
↓-33.3%prior 9
Freezing rain/drizzle4 (1.6%)
Blowing Snow3 (1.2%)
Other (explain in narrative)3 (1.2%)
Sleet, hail2 (0.8%)
Fog, smoke, smog2 (0.8%)
↓-66.7%prior 6
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

Daylight187 (70.8%)
↑1.6%prior 184
Dark - roadway not lighted36 (13.6%)
↓-25.0%prior 48
Dark - roadway lighted16 (6.1%)
↑23.1%prior 13
Dusk12 (4.5%)
↑50.0%prior 8
Dawn10 (3.8%)
↑25.0%prior 8
Dark - unknown roadway lighting3 (1.1%)

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

Road Surface

Dry198 (76.4%)
↓-3.4%prior 205
Wet20 (7.7%)
↓-9.1%prior 22
Ice/frost17 (6.6%)
↑21.4%prior 14
Snow14 (5.4%)
↑16.7%prior 12
Gravel7 (2.7%)
→0.0%prior 7
Slush2 (0.8%)
Other (explain in narrative)1 (0.4%)

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

Vehicles & Demographics

Chevrolet and Ford remained the top two vehicle makes involved in crashes in both periods, with Chevrolet's count increasing from 89 to 106 vehicles. The top five rankings shifted, with Dodge (26 vehicles) and GMC (25 vehicles) entering the top group in 2024. The total number of persons involved in crashes decreased from 685 to 541, a change which included significant reductions in the number of individuals from the 26-34 age group (from 123 to 84) and the 65+ age group (from 106 to 72).

Top Vehicle Makes (519 vehicles)

1
CHEV106 (20.4%)
↑19.1%prior 89
2
FORD88 (17%)
→0.0%prior 88
3
DODG26 (5%)
↑62.5%prior 16
4
GMC25 (4.8%)
↑150.0%prior 10
5
KIA19 (3.7%)
↑90.0%prior 10
6
JEEP19 (3.7%)
↑35.7%prior 14
7
HOND16 (3.1%)
↑77.8%prior 9
8
TOYT15 (2.9%)
↓-25.0%prior 20
9
NISS14 (2.7%)
↓-26.3%prior 19
10
CHEVROLET13 (2.5%)
↓-13.3%prior 15

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 (313 persons with recorded sex)

Male182 (58.1%)
↓-32.1%prior 268
Female131 (41.9%)
↓-24.7%prior 174

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: 336
  • Total persons involved: 541
  • Total vehicles involved: 519

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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