Yearly Traffic Safety Analysis

352 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Boone County recorded 352 total crashes, a 4.8% increase from the 336 crashes documented in 2024. While the number of fatalities decreased from 3 to 2, the total number of individuals injured in these collisions rose by 32.7%, from 107 in the prior year to 142 in the current period.

352

▲ 4.8%was 336

Total Crash Events

2

▼ -33.3%was 3

Persons Killed

142

▲ 32.7%was 107

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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Boone County saw a slight increase in 2025, rising by 4.8% from 336 to 352 incidents compared to the previous year. Although fatalities decreased from 3 to 2, the number of persons injured in these crashes increased by 32.7%.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 3↓-33.3%

2

Cyclists Injured

Prior: 2→0.0%

140

Motorists Injured

Prior: 104↑34.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · 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 a notable shift between the two periods. While Friday was the peak day for crashes in 2024 with 62 incidents, Tuesday became the peak day in 2025 with the same number of crashes. More significantly, the peak hour for collisions moved from the 5 p.m. evening commute in 2024 (29 crashes) to the 7 a.m. morning commute in 2025 (37 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes worsened in 2025, with a higher proportion of collisions resulting in injury. The share of crashes involving serious injuries grew from 3.9% to 4.5%, and minor injury crashes increased their share from 10.7% to 15.1%. Consequently, the proportion of crashes with no reported injuries decreased from 73.5% in 2024 to 69.6% in 2025, even as the number of fatal crashes remained stable at two events.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
→0.0%prior 2
Serious Injury16serious injury crashes4.5%
↑23.1%prior 13
Minor Injury53minor injury crashes15.1%
↑47.2%prior 36
Possible Injury36possible injury crashes10.2%
↓-5.3%prior 38
No Injury245no injury crashes69.6%
↓-0.8%prior 247

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, with the count increasing from 93 to 99 incidents. Failure to yield the right-of-way at a stop sign saw a significant increase, rising by 32.1% from 28 to 37 crashes. The number of incidents where a driver ran a stop sign also grew from 11 in 2024 to 19 in 2025, while crashes attributed to following too closely increased from 13 to 20.

Officer-Reported Primary Contributing Cause

Animal99 (28.1%)↑6.5%prior 93
FTYROW: From stop sign37 (10.5%)↑32.1%prior 28
Followed too close20 (5.7%)↑53.8%prior 13
Ran off road - left20 (5.7%)↓-9.1%prior 22
Ran Stop Sign19 (5.4%)↑72.7%prior 11
Lost Control15 (4.3%)↓-11.8%prior 17
Driving too fast for conditions14 (4%)↑7.7%prior 13
Ran off road - straight9 (2.6%)→0.0%prior 9
FTYROW: Making left turn9 (2.6%)↑12.5%prior 8
Operating vehicle in an reckless, erratic, careless, negligent manner9 (2.6%)↓-18.2%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both 2025 and 2024 occurred in clear weather on dry roads, with these proportions remaining stable year-over-year. However, there was a noticeable increase in crashes occurring on icy or frosty surfaces, which rose from 17 incidents in 2024 to 24 in 2025. Crashes in dark conditions, both on lighted and unlighted roadways, also increased from a combined 52 incidents in the prior year to 63 in the current year.

Weather

Clear199 (71.8%)
↑7.6%prior 185
Cloudy49 (17.7%)
↑14.0%prior 43
Rain8 (2.9%)
↑33.3%prior 6
Snow7 (2.5%)
↓-22.2%prior 9
Severe Winds6 (2.2%)
Blowing Snow3 (1.1%)
Other (explain in narrative)2 (0.7%)
Fog, smoke, smog2 (0.7%)
Freezing rain/drizzle1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight188 (68.1%)
↑0.5%prior 187
Dark - roadway not lighted42 (15.2%)
↑16.7%prior 36
Dark - roadway lighted21 (7.6%)
↑31.3%prior 16
Dawn12 (4.3%)
↑20.0%prior 10
Dusk12 (4.3%)
→0.0%prior 12
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry205 (73.7%)
↑3.5%prior 198
Ice/frost24 (8.6%)
↑41.2%prior 17
Wet23 (8.3%)
↑15.0%prior 20
Snow15 (5.4%)
↑7.1%prior 14
Gravel9 (3.2%)
↑28.6%prior 7
Mud, dirt1 (0.4%)
Slush1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of vehicles involved shows a shift in the top makes, with Ford taking the lead from Chevrolet in 2025; its involvement increased from 88 to 109 vehicles while Chevrolet's decreased from 106 to 88. Regarding the demographics of people involved in crashes, the 16-20 age group saw its representation increase from 14.0% to 15.5% of all persons involved. The 65 and older age group's share also increased slightly from 13.3% to 14.3%.

Top Vehicle Makes (554 vehicles)

1
FORD109 (19.7%)
↑23.9%prior 88
2
CHEV88 (15.9%)
↓-17.0%prior 106
3
NISS27 (4.9%)
↑92.9%prior 14
4
TOYO27 (4.9%)
↑107.7%prior 13
5
JEEP26 (4.7%)
↑36.8%prior 19
6
KIA24 (4.3%)
↑26.3%prior 19
7
DODG22 (4%)
↓-15.4%prior 26
8
HOND20 (3.6%)
↑25.0%prior 16
9
TOYT19 (3.4%)
↑26.7%prior 15
10
GMC16 (2.9%)
↓-36.0%prior 25

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (309 persons with recorded sex)

Male183 (59.2%)
↑0.5%prior 182
Female126 (40.8%)
↓-3.8%prior 131

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 352
  • Total persons involved: 575
  • Total vehicles involved: 554

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: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2025-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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