Yearly Traffic Safety Analysis

314 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Buena Vista County recorded 314 total crashes, a 6.0% decrease from the 334 crashes reported in 2024. Despite the overall decline in collisions, the number of fatal crashes doubled from 2 to 4, and total fatalities increased from 3 to 4. The most significant change among contributing factors was a 40.8% decrease in crashes involving animals, which fell from 71 incidents in 2024 to 42 in 2025.

314

▼ -6.0%was 334

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

108

▲ 2.9%was 105

Persons Injured

4

▲ 100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 Buena Vista County decreased by 6.0% in 2025 compared to the previous year, with 314 incidents versus 334 in 2024. While the total number of crashes declined, the number of people injured saw a slight increase of 2.9% from 105 to 108, and fatalities rose from 3 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 3↑33.3%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

4

Cyclists Injured

Prior: 1↑300.0%

101

Motorists Injured

Prior: 103↓-1.9%

2

Other Injured

Prior: 0→%

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 in Buena Vista County showed some shifts between 2024 and 2025. The peak day for crashes moved from Friday (57 incidents) in 2024 to Thursday (54 incidents) in 2025. The 3 p.m. hour remained the single hour with the most crashes in both years, accounting for 31 incidents in 2024 and 29 in 2025. While crashes on Thursday increased from 52 to 54, collisions on Friday saw a notable drop from 57 to 45.

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 the number of fatal crashes doubling from 2 to 4 year-over-year. This caused the fatal crash rate to increase from 0.6% of all incidents in 2024 to 1.3% in 2025. Conversely, crashes resulting in serious injuries decreased from 10 in 2024 to 6 in 2025, a drop from 3.0% to 1.9% of the total. The proportion of crashes with no injuries declined from 72.2% to 70.4%, while crashes involving possible injuries slightly increased from 44 to 46 incidents.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.3%
↑100.0%prior 2
Serious Injury6serious injury crashes1.9%
↓-40.0%prior 10
Minor Injury37minor injury crashes11.8%
→0.0%prior 37
Possible Injury46possible injury crashes14.6%
↑4.5%prior 44
No Injury221no injury crashes70.4%
↓-8.3%prior 241

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

Crashes involving an animal remained the leading contributing factor in both periods, though the count decreased by 40.8% from 71 incidents in 2024 to 42 in 2025. Failure to yield from a stop sign became the second-most common factor in 2025 with 25 incidents, up from 24 incidents the prior year when it was ranked third. 'Driving too fast for conditions' fell to the third rank, with its count holding steady at 23 crashes compared to 24 in 2024. The count for 'Followed too close' quadrupled from 4 incidents in 2024 to 16 in 2025.

Officer-Reported Primary Contributing Cause

Animal42 (13.4%)↓-40.8%prior 71
FTYROW: From stop sign25 (8%)↑4.2%prior 24
Driving too fast for conditions23 (7.3%)↓-4.2%prior 24
Lost Control18 (5.7%)↑12.5%prior 16
Ran off road - left18 (5.7%)↑5.9%prior 17
Followed too close16 (5.1%)
Made improper turn13 (4.1%)↓-13.3%prior 15
Other (explain in narrative): Other13 (4.1%)↑18.2%prior 11
Operating vehicle in an reckless, erratic, careless, negligent manner13 (4.1%)↑85.7%prior 7
Driver Distraction: Other interior distraction12 (3.8%)↓-14.3%prior 14

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 favorable conditions, with most incidents happening in daylight (183 and 185, respectively) and on dry roads (204 and 211). Clear weather was reported in 218 crashes in 2025, compared to 213 in 2024. However, there was a shift in adverse winter conditions: crashes on snow-covered roads increased from 12 to 29, while incidents on icy or frosty surfaces decreased from 20 to 12.

Weather

Clear218 (77.6%)
↑2.3%prior 213
Cloudy30 (10.7%)
↑15.4%prior 26
Snow12 (4.3%)
↑100.0%prior 6
Rain7 (2.5%)
↓-41.7%prior 12
Fog, smoke, smog7 (2.5%)
↓-30.0%prior 10
Severe Winds3 (1.1%)
Freezing rain/drizzle2 (0.7%)
↓-60.0%prior 5
Blowing Snow2 (0.7%)

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

Lighting

Daylight183 (64.4%)
↓-1.1%prior 185
Dark - roadway not lighted55 (19.4%)
↓-1.8%prior 56
Dark - roadway lighted29 (10.2%)
↑7.4%prior 27
Dusk9 (3.2%)
→0.0%prior 9
Dawn6 (2.1%)
↑20.0%prior 5
Dark - unknown roadway lighting2 (0.7%)

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

Road Surface

Dry204 (72.3%)
↓-3.3%prior 211
Snow29 (10.3%)
↑141.7%prior 12
Wet23 (8.2%)
↓-14.8%prior 27
Gravel13 (4.6%)
↑116.7%prior 6
Ice/frost12 (4.3%)
↓-40.0%prior 20
Water (standing or moving)1 (0.4%)

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

Vehicles & Demographics

The ranking of top vehicle makes involved in crashes shifted between 2024 and 2025. Chevrolet became the most frequent make with 96 vehicles, up from 76 in the prior year, overtaking Ford, which saw its involvement decrease from 91 to 78 vehicles. Regarding persons involved, there was an increase in younger age groups, with the 16-20 group growing from 67 to 78 individuals and the 26-34 group increasing from 73 to 81. Conversely, involvement for the 35-44 and 45-54 age groups decreased.

Top Vehicle Makes (506 vehicles)

1
CHEV96 (19%)
↑26.3%prior 76
2
FORD78 (15.4%)
↓-14.3%prior 91
3
GMC33 (6.5%)
↑37.5%prior 24
4
DODG26 (5.1%)
↓-21.2%prior 33
5
NISS26 (5.1%)
↑30.0%prior 20
6
JEEP24 (4.7%)
↑26.3%prior 19
7
TOYO17 (3.4%)
↑13.3%prior 15
8
HOND17 (3.4%)
↓-15.0%prior 20
9
TOYT16 (3.2%)
↓-15.8%prior 19
10
CHEVROLET16 (3.2%)
↓-36.0%prior 25

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

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

Sex Distribution (319 persons with recorded sex)

Male186 (58.3%)
↓-4.1%prior 194
Female133 (41.7%)
↑16.7%prior 114

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: 314
  • Total persons involved: 529
  • Total vehicles involved: 506

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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