Yearly Traffic Safety Analysis

108 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Page County, total traffic crashes decreased by 8.5%, from 118 in 2024 to 108 in 2025. Despite the overall reduction in collisions, the number of fatalities tripled from one to three, and total injuries rose from 39 to 46. The most significant shift in contributing factors was a 44% decrease in crashes involving animals, which fell from 25 incidents in the prior year to 14 in the current year.

108

▼ -8.5%was 118

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

46

▲ 17.9%was 39

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Traffic crashes in Page County showed a downward trend, decreasing from 118 in 2024 to 108 in 2025. However, the severity of these incidents worsened year-over-year. While total collisions fell by 8.5%, the number of people injured increased by 17.9% from 39 to 46, and fatalities increased from one to three.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

1

Cyclists Injured

Prior: 0→%

45

Motorists Injured

Prior: 37↑21.6%

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 shifted between the two periods. In 2025, the peak days for crashes were Monday and Saturday, each with 18 incidents. This contrasts with 2024, when Friday was the most frequent day for crashes with 29 incidents. The peak hour for collisions shifted slightly earlier, from 4 p.m. in the prior period (12 crashes) to 3 p.m. in the current period (12 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

While total crashes declined, their severity profile changed notably year-over-year. The number of fatal crashes increased from one in 2024 to three in 2025, raising the fatal crash rate from 0.85% to 2.78%. Crashes resulting in serious injuries decreased from four to one. Conversely, collisions involving possible injuries increased from 14 in 2024 to 18 in 2025, and those with minor injuries remained stable at 15 incidents in both periods.

Outcome by Severity (Crash Events)

Fatal3fatal crashes2.8%
↑200.0%prior 1
Serious Injury1serious injury crashes0.9%
↓-75.0%prior 4
Minor Injury15minor injury crashes13.9%
→0.0%prior 15
Possible Injury18possible injury crashes16.7%
↑28.6%prior 14
No Injury71no injury crashes65.7%
↓-15.5%prior 84

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

The leading contributing factors for crashes shifted between 2024 and 2025. Collisions involving an animal, while still the top factor in 2025, saw their count decrease by 44% from 25 to 14. 'Lost Control' incidents also fell from 13 to 8. In contrast, crashes attributed to 'Driving too fast for conditions' increased from 7 to 10, and 'Followed too close' incidents rose from 7 to 9. 'Ran Stop Sign' crashes saw a notable decrease from 9 incidents in 2024 to 5 in 2025.

Officer-Reported Primary Contributing Cause

Animal14 (13%)↓-44.0%prior 25
Driving too fast for conditions10 (9.3%)↑42.9%prior 7
Followed too close9 (8.3%)↑28.6%prior 7
Lost Control8 (7.4%)↓-38.5%prior 13
FTYROW: From driveway7 (6.5%)
Driver Distraction: Other interior distraction5 (4.6%)
Ran Stop Sign5 (4.6%)↓-44.4%prior 9
Made improper turn4 (3.7%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (3.7%)
Ran off road - left4 (3.7%)↓-50.0%prior 8

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

Road & Environmental Conditions

Year-over-year comparison shows a shift in crash conditions. While crashes on dry roads were stable (78 in 2024 vs. 80 in 2025), incidents on adverse road surfaces changed. The number of crashes on snowy or icy roads more than doubled, increasing from 7 combined incidents in 2024 to 13 in 2025. Correspondingly, crashes in snowy weather increased from 2 to 6. Collisions in daylight conditions remained nearly identical, with 71 in the prior period and 70 in the current period.

Weather

Clear75 (77.3%)
→0.0%prior 75
Cloudy12 (12.4%)
→0.0%prior 12
Snow6 (6.2%)
Blowing Snow1 (1.0%)
Fog, smoke, smog1 (1.0%)
Freezing rain/drizzle1 (1.0%)
Rain1 (1.0%)

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

Lighting

Daylight70 (72.9%)
↓-1.4%prior 71
Dark - roadway not lighted14 (14.6%)
↑27.3%prior 11
Dark - roadway lighted4 (4.2%)
↓-50.0%prior 8
Dawn3 (3.1%)
Dusk3 (3.1%)
Dark - unknown roadway lighting2 (2.1%)

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

Road Surface

Dry80 (81.6%)
↑2.6%prior 78
Snow8 (8.2%)
↑60.0%prior 5
Ice/frost5 (5.1%)
Gravel3 (3.1%)
↓-40.0%prior 5
Wet2 (2.0%)
↓-75.0%prior 8

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent year-over-year, with Ford (34 vehicles) and Chevrolet variants (38 vehicles combined) being the most common in 2025, similar to the prior period's counts of 35 for Ford and 46 for Chevrolet variants. An analysis of persons involved shows shifts among age groups. The number of people in the 26-34 age group involved in crashes increased from 25 to 30, and the 65+ group grew from 33 to 37. Conversely, involvement for the 35-44 age group decreased from 27 to 20.

Top Vehicle Makes (180 vehicles)

1
FORD34 (18.9%)
↓-2.9%prior 35
2
CHEV27 (15%)
↓-12.9%prior 31
3
CHEVROLET11 (6.1%)
↓-26.7%prior 15
4
DODG11 (6.1%)
↑22.2%prior 9
5
GMC8 (4.4%)
↑33.3%prior 6
6
JEEP8 (4.4%)
↓-27.3%prior 11
7
NISS7 (3.9%)
→0.0%prior 7
8
TOYT6 (3.3%)
9
CHRY5 (2.8%)
↓-28.6%prior 7
10
PETERBILT5 (2.8%)

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

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

Sex Distribution (96 persons with recorded sex)

Male50 (52.1%)
↓-18.0%prior 61
Female46 (47.9%)
↑2.2%prior 45

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: 108
  • Total persons involved: 190
  • Total vehicles involved: 180

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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