Yearly Traffic Safety Analysis

157 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Grundy County, a total of 157 crashes were recorded in 2025, representing an 18.7% decrease from the 193 crashes in 2024. Total injuries also declined from 45 to 41, with no fatalities reported in either period. The most significant year-over-year change was a 66.7% reduction in crashes involving a driver under the influence of alcohol, which fell from 6 incidents to 2.

157

▼ -18.7%was 193

Total Crash Events

0

Persons Killed

41

▼ -8.9%was 45

Persons Injured

0

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

Overall traffic crash trends in Grundy County are declining year-over-year. The total number of crashes fell by 36, from 193 in 2024 to 157 in 2025. This downward trend was also reflected in a slight decrease in total injuries, from 45 to 41, while fatalities remained at zero for both years.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

40

Motorists Injured

Prior: 44↓-9.1%

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. The peak day for collisions moved from Friday (31 crashes) in 2024 to Tuesday (29 crashes) in 2025. Similarly, the peak hour for crashes changed from the 9 p.m. hour in the prior year (14 crashes) to the 1 p.m. hour in the current year (15 crashes), indicating a move from evening to midday crash occurrences.

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

Fatal crashes remained at zero for both 2024 and 2025. The number of serious injury crashes decreased from 6 to 4 year-over-year. The proportion of crashes resulting in possible injuries dropped from 8.3% of all crashes in 2024 to 3.8% in 2025, while the share of crashes with no injuries increased from 78.2% to 81.5%.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes2.5%
↓-33.3%prior 6
Minor Injury19minor injury crashes12.1%
↓-5.0%prior 20
Possible Injury6possible injury crashes3.8%
↓-62.5%prior 16
No Injury128no injury crashes81.5%
↓-15.2%prior 151

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 years, though the count of such incidents decreased from 86 in 2024 to 67 in 2025. "Lost Control" became the second most-cited factor in 2025 with 15 crashes, up from 12 in the prior year. Crashes attributed to a driver running off the road straight decreased notably, from 13 incidents in 2024 to 5 in 2025.

Officer-Reported Primary Contributing Cause

Animal67 (42.7%)↓-22.1%prior 86
Lost Control15 (9.6%)↑25.0%prior 12
Ran off road - left12 (7.6%)↓-20.0%prior 15
FTYROW: From stop sign8 (5.1%)→0.0%prior 8
Driving too fast for conditions6 (3.8%)↑20.0%prior 5
Other (explain in narrative): Other6 (3.8%)
Ran Stop Sign5 (3.2%)
Ran off road - straight5 (3.2%)↓-61.5%prior 13
Driver Distraction: Other interior distraction3 (1.9%)↓-50.0%prior 6
Followed too close3 (1.9%)↓-50.0%prior 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

There was a notable decrease in crashes occurring under adverse conditions year-over-year. Collisions on roads with ice or frost fell from 14 to 3, and crashes in unlighted dark conditions dropped from 41 to 14. Crashes attributed to snowy weather also decreased from 10 to 2, while the number of incidents on dry roads in daylight remained relatively consistent.

Weather

Clear64 (68.1%)
↓-12.3%prior 73
Cloudy18 (19.1%)
↓-21.7%prior 23
Rain5 (5.3%)
Severe Winds4 (4.3%)
Snow2 (2.1%)
↓-80.0%prior 10
Blowing Snow1 (1.1%)

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

Lighting

Daylight68 (71.6%)
↑4.6%prior 65
Dark - roadway not lighted14 (14.7%)
↓-65.9%prior 41
Dawn5 (5.3%)
Dark - roadway lighted4 (4.2%)
↓-55.6%prior 9
Dusk3 (3.2%)
Dark - unknown roadway lighting1 (1.1%)

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

Road Surface

Dry68 (72.3%)
↓-12.8%prior 78
Gravel8 (8.5%)
↑14.3%prior 7
Snow8 (8.5%)
↓-11.1%prior 9
Wet7 (7.4%)
↓-22.2%prior 9
Ice/frost3 (3.2%)
↓-78.6%prior 14

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 periods, with their counts decreasing from 56 to 38 and 45 to 31, respectively. The age demographics of persons involved in crashes also shifted. The number of individuals aged 16-20 decreased from 41 to 28, while the count for the 65+ age group increased from 26 to 39.

Top Vehicle Makes (208 vehicles)

1
FORD38 (18.3%)
↓-32.1%prior 56
2
CHEV31 (14.9%)
↓-31.1%prior 45
3
TOYO16 (7.7%)
↑23.1%prior 13
4
JEEP11 (5.3%)
↓-21.4%prior 14
5
NISS11 (5.3%)
6
DODG10 (4.8%)
↑25.0%prior 8
7
HOND7 (3.4%)
→0.0%prior 7
8
TOYT6 (2.9%)
9
DODGE5 (2.4%)
10
CHRY5 (2.4%)
↓-28.6%prior 7

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

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

Sex Distribution (101 persons with recorded sex)

Male69 (68.3%)
↓-18.8%prior 85
Female32 (31.7%)
↓-17.9%prior 39

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: 157
  • Total persons involved: 220
  • Total vehicles involved: 208

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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