Yearly Traffic Safety Analysis

75 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Mitchell County, total traffic crashes decreased by 25% from 100 in 2024 to 75 in 2025. This downward trend was accompanied by a 27.5% reduction in injuries, from 40 to 29, while fatalities remained unchanged at one death in each period. A notable year-over-year shift was the change in the most common time for crashes, which moved from the afternoon commute in 2024 to mid-morning in 2025.

75

▼ -25.0%was 100

Total Crash Events

1

Persons Killed

29

▼ -27.5%was 40

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 safety metrics in Mitchell County showed a general improvement from 2024 to 2025. Total crashes fell by 25%, dropping from 100 to 75. The number of people injured in these incidents also declined by 27.5% from 40 to 29. However, the number of fatalities held steady, with one person killed in a crash in both years.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

28

Motorists Injured

Prior: 39↓-28.2%

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 timing of crashes shifted between the two periods. In 2025, Wednesday was the peak day for crashes with 20 incidents, and the 10 a.m. hour was the most frequent time with 11 crashes. This contrasts with 2024, when Monday was the peak day with 24 crashes and the 3 p.m. hour was the peak time with 9 incidents, indicating a move from an afternoon peak to a morning peak year-over-year.

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 showed a mixed profile year-over-year. While the total number of crashes decreased, the fatal crash rate increased slightly from 1.0% of all crashes in 2024 to 1.3% in 2025, with one fatal crash recorded in each year. The proportion of crashes involving any level of injury (Serious, Minor, or Possible) saw a slight increase, rising from 30% of all incidents in 2024 to 33.3% in 2025. Crashes resulting in no injuries decreased from 69% to 65.3% of the total.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.3%
→0.0%prior 1
Serious Injury2serious injury crashes2.7%
→0.0%prior 2
Minor Injury8minor injury crashes10.7%
↓-50.0%prior 16
Possible Injury15possible injury crashes20%
↑25.0%prior 12
No Injury49no injury crashes65.3%
↓-29.0%prior 69

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 changed between 2024 and 2025. In 2025, 'Ran off road - straight' and 'Lost Control' were the top factors, each cited in 9 crashes. This is a shift from 2024, when 'Failure to yield right-of-way from a stop sign' was the primary factor with 12 crashes. Incidents involving failure to yield from a stop sign decreased by 50% to 6 crashes in 2025. Conversely, crashes attributed to 'Lost Control' increased from 7 in the prior year to 9 in the current year.

Officer-Reported Primary Contributing Cause

Ran off road - straight9 (12%)→0.0%prior 9
Lost Control9 (12%)↑28.6%prior 7
FTYROW: At uncontrolled intersection8 (10.7%)↑14.3%prior 7
Animal7 (9.3%)→0.0%prior 7
FTYROW: From stop sign6 (8%)↓-50.0%prior 12
Ran off road - left6 (8%)↓-33.3%prior 9
Other (explain in narrative): Other5 (6.7%)
FTYROW: From yield sign3 (4%)
Improper Backing3 (4%)
Driver Distraction: Other interior distraction3 (4%)

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

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in clear weather (57.3% in 2025 vs. 61% in 2024) and on dry roads (62.7% in 2025 vs. 62% in 2024). However, there was a notable increase in crashes happening in adverse winter conditions. Crashes in snowy weather increased from 2 to 6, and incidents on snow-covered road surfaces grew from 8 to 11 between 2024 and 2025.

Weather

Clear43 (61.4%)
↓-29.5%prior 61
Cloudy13 (18.6%)
↓-23.5%prior 17
Snow6 (8.6%)
Severe Winds3 (4.3%)
Blowing Snow3 (4.3%)
Rain2 (2.9%)

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

Lighting

Daylight55 (78.6%)
↓-19.1%prior 68
Dark - roadway not lighted10 (14.3%)
↓-28.6%prior 14
Dark - roadway lighted3 (4.3%)
↓-57.1%prior 7
Dusk2 (2.9%)

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

Road Surface

Dry47 (67.1%)
↓-24.2%prior 62
Snow11 (15.7%)
↑37.5%prior 8
Wet4 (5.7%)
↓-63.6%prior 11
Ice/frost3 (4.3%)
↓-62.5%prior 8
Gravel3 (4.3%)
Slush2 (2.9%)

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

Vehicles & Demographics

The demographics of persons involved in crashes shifted between periods. In 2025, the 65+ age group was the most represented cohort with 24 individuals (19.5% of total), a change from 2024 when the 16-20 age group was largest with 31 individuals (18.2%). Regarding vehicle makes, Chevrolet and Ford were the top two most frequently involved makes in both years, with their counts decreasing from 32 to 21 and 28 to 20, respectively. GMC vehicles became the third most common make in 2025, replacing Dodge from the top three in the prior year.

Top Vehicle Makes (119 vehicles)

1
CHEV21 (17.6%)
↓-34.4%prior 32
2
FORD20 (16.8%)
↓-28.6%prior 28
3
GMC7 (5.9%)
↓-22.2%prior 9
4
CHEVROLET7 (5.9%)
↑40.0%prior 5
5
CHRY6 (5%)
6
JEEP5 (4.2%)
↓-37.5%prior 8
7
HOND4 (3.4%)
8
DODG4 (3.4%)
↓-55.6%prior 9
9
DODGE4 (3.4%)
↓-50.0%prior 8
10
TOYOTA4 (3.4%)

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

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

Sex Distribution (74 persons with recorded sex)

Male53 (71.6%)
↓-13.1%prior 61
Female21 (28.4%)
↓-53.3%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: 75
  • Total persons involved: 123
  • Total vehicles involved: 119

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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