Yearly Traffic Safety Analysis

190 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Appanoose County recorded 190 total crashes, a decrease of 8.7% from the 208 crashes documented in 2024. While overall crashes declined, the most significant year-over-year shift was the emergence of traffic fatalities, with two deaths occurring in 2025 compared to none in the prior year. The total number of injuries increased slightly from 60 in 2024 to 65 in 2025.

190

▼ -8.7%was 208

Total Crash Events

2

Persons Killed

65

▲ 8.3%was 60

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

The overall trend in crashes in Appanoose County is downward, with total collisions falling by 8.7% from 208 in 2024 to 190 in 2025. Despite this decrease in crash volume, the outcomes were more severe. The number of people injured rose by 8.3% from 60 to 65, and the county registered two fatalities in 2025 after having none in the previous year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

1

Cyclists Injured

Prior: 0→%

64

Motorists Injured

Prior: 60↑6.7%

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 year-over-year. The most frequent day for collisions moved from Monday in 2024 (36 crashes) to Friday in 2025 (34 crashes). A similar change occurred with the peak hour, which shifted from 7 p.m. in 2024 (16 crashes) to the 5 p.m. commute hour in 2025 (20 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

Crash severity notably increased in 2025, with two fatal crashes recorded, representing 1.1% of all incidents, compared to zero fatal crashes in 2024. While the count of serious injury crashes fell from 6 to 3 and minor injury crashes dropped from 22 to 14, the number of crashes involving possible injuries rose significantly from 19 in 2024 to 31 in 2025.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
Serious Injury3serious injury crashes1.6%
↓-50.0%prior 6
Minor Injury14minor injury crashes7.4%
↓-36.4%prior 22
Possible Injury31possible injury crashes16.3%
↑63.2%prior 19
No Injury140no injury crashes73.7%
↓-13.0%prior 161

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 animals remained the leading contributing factor in both periods, although the count of such incidents decreased by 10.7% from 75 in 2024 to 67 in 2025. 'Failure to yield from a stop sign' became the second-most cited factor in 2025, with its incident count increasing from 10 to 13. Conversely, crashes attributed to 'Driving too fast for conditions' saw a significant reduction, falling from 14 incidents in 2024 to 8 in 2025.

Officer-Reported Primary Contributing Cause

Animal67 (35.3%)↓-10.7%prior 75
FTYROW: From stop sign13 (6.8%)↑30.0%prior 10
Lost Control10 (5.3%)↑25.0%prior 8
Driving too fast for conditions8 (4.2%)↓-42.9%prior 14
Ran off road - left8 (4.2%)↑14.3%prior 7
Driver Distraction: Inattentive/lost in thought7 (3.7%)
Followed too close6 (3.2%)↓-14.3%prior 7
Other (explain in narrative): Other6 (3.2%)↓-40.0%prior 10
Operating vehicle in an reckless, erratic, careless, negligent manner5 (2.6%)
FTYROW: From driveway5 (2.6%)

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 conditions under which crashes occurred saw some shifts year-over-year. Crashes on wet roads decreased from 18 incidents in 2024 to 6 in 2025, and collisions during rain fell from 11 to 3. Despite an overall drop in total crashes, incidents on dry roads increased slightly from 103 to 107. The number of crashes occurring on roads with snow or ice was unchanged, with 11 incidents in both periods.

Weather

Clear98 (75.4%)
↓-7.5%prior 106
Cloudy24 (18.5%)
↑33.3%prior 18
Rain3 (2.3%)
↓-72.7%prior 11
Snow3 (2.3%)
Freezing rain/drizzle2 (1.5%)

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

Lighting

Daylight85 (63.4%)
↓-14.1%prior 99
Dark - roadway not lighted27 (20.1%)
↓-3.6%prior 28
Dark - roadway lighted14 (10.4%)
↑40.0%prior 10
Dusk4 (3.0%)
Dark - unknown roadway lighting3 (2.2%)
Dawn1 (0.7%)

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

Road Surface

Dry107 (82.3%)
↑3.9%prior 103
Snow6 (4.6%)
↓-14.3%prior 7
Wet6 (4.6%)
↓-66.7%prior 18
Ice/frost5 (3.8%)
Gravel4 (3.1%)
↓-50.0%prior 8
Mud, dirt1 (0.8%)
Slush1 (0.8%)

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 during both years. The number of Chevrolets in collisions decreased from a combined 87 (CHEV and CHEVROLET) in 2024 to 73 in 2025, while Fords increased from 52 to 56. Analyzing the ages of people involved, the 45-54 age group saw a notable increase from 31 individuals in 2024 to 45 in 2025. In contrast, the 16-20 age group saw its involvement decrease from 56 to 46 persons.

Top Vehicle Makes (279 vehicles)

1
CHEV62 (22.2%)
↓-8.8%prior 68
2
FORD56 (20.1%)
↑7.7%prior 52
3
DODG20 (7.2%)
↑17.6%prior 17
4
TOYT15 (5.4%)
↑25.0%prior 12
5
JEEP14 (5%)
↑55.6%prior 9
6
CHEVROLET11 (3.9%)
↓-42.1%prior 19
7
GMC11 (3.9%)
↓-38.9%prior 18
8
RAM9 (3.2%)
9
BUIC8 (2.9%)
↓-27.3%prior 11
10
CHRY8 (2.9%)
↑33.3%prior 6

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

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

Sex Distribution (143 persons with recorded sex)

Male90 (62.9%)
↓-6.3%prior 96
Female53 (37.1%)
↓-1.9%prior 54

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: 190
  • Total persons involved: 295
  • Total vehicles involved: 279

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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