Yearly Traffic Safety Analysis

110 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Calhoun County recorded 110 total crashes, a 4.3% decrease from the 115 crashes reported in 2024. Despite the overall decline in collisions, the number of fatalities increased from one in the prior period to three in the current period. This resulted in a doubling of fatal crashes from one to two year-over-year.

110

▼ -4.3%was 115

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

35

▲ 16.7%was 30

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) 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

Overall traffic crashes in Calhoun County saw a slight decline in 2025, falling by 4.3% from 115 to 110 incidents compared to the previous year. However, the severity of these crashes increased, with total injuries rising by 16.7% from 30 to 35 and fatalities tripling 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→%

34

Motorists Injured

Prior: 30↑13.3%

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 significantly between the two periods. In 2025, the peak days for crashes were Wednesday and Saturday, each with 18 incidents, a change from the prior period's peak on Friday (22 crashes). The most frequent crash hour also moved from the evening (9 p.m. with 11 crashes in 2024) to the morning commute (7 a.m. with 11 crashes 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 worsened in 2025 compared to 2024, with the number of fatal crashes doubling from one to two and the fatal crash rate increasing from 0.87% to 1.82%. While the count of serious injury crashes remained stable at three, crashes resulting in minor injuries increased from 10 to 14. Consequently, the proportion of crashes with no injuries decreased from 77.4% in 2024 to 73.6% in 2025.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.8%
↑100.0%prior 1
Serious Injury3serious injury crashes2.7%
→0.0%prior 3
Minor Injury14minor injury crashes12.7%
↑40.0%prior 10
Possible Injury10possible injury crashes9.1%
↓-16.7%prior 12
No Injury81no injury crashes73.6%
↓-9.0%prior 89

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 top contributing factor in both periods, with counts increasing slightly from 35 incidents in 2024 to 37 in 2025. A notable shift occurred with 'Driving too fast for conditions,' which saw its count increase from 3 to 10 crashes, becoming the second-leading factor in the current period. Conversely, crashes attributed to 'Ran off road - left' decreased in count, from 11 in the prior year to 4 in the current year.

Officer-Reported Primary Contributing Cause

Animal37 (33.6%)↑5.7%prior 35
Driving too fast for conditions10 (9.1%)
Lost Control8 (7.3%)→0.0%prior 8
Ran off road - straight7 (6.4%)→0.0%prior 7
Made improper turn5 (4.5%)
Operating vehicle in an reckless, erratic, careless, negligent manner4 (3.6%)
FTYROW: From driveway4 (3.6%)
Ran off road - left4 (3.6%)↓-63.6%prior 11
FTYROW: Making left turn4 (3.6%)
FTYROW: From stop sign3 (2.7%)

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

Road & Environmental Conditions

Crashes occurring in adverse weather saw a notable increase, with collisions in snow or blowing snow conditions more than doubling from 6 in 2024 to 14 in 2025. Correspondingly, crashes on snow or ice-covered road surfaces increased from 19 to 21. In contrast, crashes in dark, unlighted conditions decreased by more than half, from 29 incidents in the prior period to 14 in the current period.

Weather

Clear45 (55.6%)
↓-10.0%prior 50
Cloudy18 (22.2%)
↓-18.2%prior 22
Blowing Snow7 (8.6%)
Snow7 (8.6%)
↑40.0%prior 5
Fog, smoke, smog1 (1.2%)
Severe Winds1 (1.2%)
Sleet, hail1 (1.2%)
Freezing rain/drizzle1 (1.2%)

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

Lighting

Daylight55 (67.9%)
↑5.8%prior 52
Dark - roadway not lighted14 (17.3%)
↓-51.7%prior 29
Dawn6 (7.4%)
Dusk3 (3.7%)
Dark - unknown roadway lighting2 (2.5%)
Dark - roadway lighted1 (1.2%)

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

Road Surface

Dry53 (65.4%)
↓-7.0%prior 57
Snow14 (17.3%)
↑75.0%prior 8
Ice/frost7 (8.6%)
↓-36.4%prior 11
Wet4 (4.9%)
↓-63.6%prior 11
Gravel2 (2.5%)
Slush1 (1.2%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both years, though their counts decreased slightly in 2025. The age demographics of persons involved in crashes showed a shift towards older age groups, with the number of individuals aged 65 and older increasing from 27 to 37. Conversely, involvement decreased for younger groups, with the 16-20 age group dropping from 31 to 19 persons and the 26-34 group falling from 32 to 24.

Top Vehicle Makes (155 vehicles)

1
CHEV24 (15.5%)
↓-4.0%prior 25
2
FORD24 (15.5%)
↓-17.2%prior 29
3
CHRY8 (5.2%)
↑33.3%prior 6
4
DODG7 (4.5%)
↓-36.4%prior 11
5
HOND7 (4.5%)
6
TOYT6 (3.9%)
7
FREIGHTLINER6 (3.9%)
8
CHEVROLET5 (3.2%)
↓-37.5%prior 8
9
GMC5 (3.2%)
↓-28.6%prior 7
10
JEEP5 (3.2%)
↓-16.7%prior 6

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

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

Sex Distribution (85 persons with recorded sex)

Male59 (69.4%)
↓-1.7%prior 60
Female26 (30.6%)
↓-31.6%prior 38

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 10, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 110
  • Total persons involved: 161
  • Total vehicles involved: 155

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 10, 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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Calhoun County, IA Crash Report — 2025 | ThatCarHitMe.com