Yearly Traffic Safety Analysis

353 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Mahaska County recorded 353 total crashes, a 3.8% decrease from the 367 crashes reported in 2024. While overall crashes and injuries saw a slight decline, the most significant year-over-year change was a substantial increase in crashes involving a driver under the influence (DUI), which rose from 8 in 2024 to 24 in 2025.

353

▼ -3.8%was 367

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

105

▼ -4.5%was 110

Persons Injured

0

▼ -100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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

The overall trend in traffic crashes in Mahaska County shows a modest year-over-year decline. Total crashes decreased by 3.8%, from 367 in 2024 to 353 in 2025. Similarly, the number of people injured fell from 110 to 105, and fatalities dropped from two to zero during the same period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 2↓-100.0%

0

Other Killed

Prior: 0→0.0%

3

Cyclists Injured

Prior: 1↑200.0%

100

Motorists Injured

Prior: 100→0.0%

2

Other Injured

Prior: 5↓-60.0%

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

Temporal patterns for crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2025 (57 crashes) and 2024 (67 crashes), and the 5 p.m. hour was the peak hour in both periods (35 and 38 crashes, respectively). While the peak times did not shift, crashes on Mondays saw a notable decrease from 65 in 2024 to 54 in 2025.

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

Crash severity improved in 2025, with fatal crashes dropping from one in 2024 to zero. The number of serious injury crashes also decreased slightly from 13 to 11. While minor injury crashes fell from 35 to 28, crashes resulting in a possible injury increased from 35 in 2024 to 49 in 2025.

Outcome by Severity (Crash Events)

Serious Injury11serious injury crashes3.1%
↓-15.4%prior 13
Minor Injury28minor injury crashes7.9%
↓-20.0%prior 35
Possible Injury49possible injury crashes13.9%
↑40.0%prior 35
No Injury265no injury crashes75.1%
↓-6.4%prior 283

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 involving an animal remained the leading contributing factor in both periods, though the count decreased from 102 in 2024 to 87 in 2025. Crashes attributed to 'Followed too close' increased in count from 37 to 46, becoming the second-most common factor. Conversely, incidents where a driver 'Ran Stop Sign' saw a significant drop, falling from 25 in 2024 to 14 in 2025.

Officer-Reported Primary Contributing Cause

Animal87 (24.6%)↓-14.7%prior 102
Followed too close46 (13%)↑24.3%prior 37
Lost Control18 (5.1%)↑50.0%prior 12
Operating vehicle in an reckless, erratic, careless, negligent manner15 (4.2%)↑66.7%prior 9
Driving too fast for conditions15 (4.2%)→0.0%prior 15
FTYROW: From stop sign15 (4.2%)↑36.4%prior 11
Ran Stop Sign14 (4%)↓-44.0%prior 25
FTYROW: Making left turn13 (3.7%)↑85.7%prior 7
Other (explain in narrative): Other12 (3.4%)↓-14.3%prior 14
Other (explain in narrative): No improper action11 (3.1%)↑57.1%prior 7

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 periods occurred in clear weather and on dry roads. The most significant shift was in lighting conditions, where crashes on dark, unlit roadways increased from 27 in 2024 to 43 in 2025. Incidents during adverse weather conditions saw a general decline, with crashes in the rain falling from 12 to 8 and crashes in the snow decreasing from 12 to 6.

Weather

Clear195 (70.9%)
↑3.7%prior 188
Cloudy55 (20.0%)
↑27.9%prior 43
Rain8 (2.9%)
↓-33.3%prior 12
Fog, smoke, smog6 (2.2%)
Snow6 (2.2%)
↓-50.0%prior 12
Severe Winds2 (0.7%)
Blowing Snow2 (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

Daylight198 (71.7%)
↑1.0%prior 196
Dark - roadway not lighted43 (15.6%)
↑59.3%prior 27
Dark - roadway lighted28 (10.1%)
↑21.7%prior 23
Dawn3 (1.1%)
Dusk3 (1.1%)
↓-80.0%prior 15
Dark - unknown roadway lighting1 (0.4%)
↓-83.3%prior 6

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

Road Surface

Dry221 (80.1%)
↑6.8%prior 207
Wet18 (6.5%)
↓-14.3%prior 21
Snow15 (5.4%)
→0.0%prior 15
Gravel15 (5.4%)
↑50.0%prior 10
Ice/frost5 (1.8%)
↓-54.5%prior 11
Other (explain in narrative)1 (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

Chevrolet and Ford vehicles were the most frequently involved in crashes in both years, with Chevrolet (115 vehicles) overtaking Ford (107 vehicles) for the top spot in 2025. Regarding driver demographics, the number of persons aged 21-25 involved in crashes decreased from 71 to 56, while those in the 35-44 age group increased from 74 to 83. Sport utility vehicles remained the most common vehicle type involved, though their count fell from 194 in 2024 to 181 in 2025.

Top Vehicle Makes (557 vehicles)

1
CHEV115 (20.6%)
↑2.7%prior 112
2
FORD107 (19.2%)
↓-9.3%prior 118
3
JEEP30 (5.4%)
↑20.0%prior 25
4
GMC24 (4.3%)
↑50.0%prior 16
5
DODG23 (4.1%)
↓-20.7%prior 29
6
TOYT20 (3.6%)
↓-41.2%prior 34
7
CHEVROLET19 (3.4%)
↓-13.6%prior 22
8
BUIC16 (2.9%)
↑33.3%prior 12
9
NR14 (2.5%)
↑75.0%prior 8
10
NISS12 (2.2%)
↓-20.0%prior 15

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

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

Sex Distribution (337 persons with recorded sex)

Male197 (58.5%)
↓-7.9%prior 214
Female140 (41.5%)
↓-0.7%prior 141

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: 353
  • Total persons involved: 581
  • Total vehicles involved: 557

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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