Yearly Traffic Safety Analysis

45 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Ringgold County recorded 45 total crashes, a 19.6% decrease from the 56 crashes reported in 2024. While total fatalities remained constant at one, total injuries fell from 19 to 11. A notable change was the decrease in crashes attributed to driving under the influence, which fell from 4 in the prior period to 1 in the current period.

45

▼ -19.6%was 56

Total Crash Events

1

Persons Killed

11

▼ -42.1%was 19

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

Overall, traffic crashes in Ringgold County saw a downward trend year-over-year, with total incidents decreasing by 19.6% from 56 in 2024 to 45 in 2025. This decline was accompanied by a 42.1% reduction in total injuries, which fell from 19 to 11. The number of fatalities remained unchanged, with one fatality recorded in each period.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 1→0.0%

11

Motorists Injured

Prior: 19↓-42.1%

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 temporal patterns of crashes showed a notable shift in the peak time of day. While Thursday remained the busiest day for crashes in both 2025 (11 crashes) and 2024 (10 crashes), the peak hour for collisions moved from 9 p.m. in the prior year to 8 a.m. in the current year. Crashes during the 8 a.m. hour increased from 2 to 5 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 number of fatal crashes remained stable at one in both 2025 and 2024, though the fatal crash rate increased from 1.79% to 2.22% due to the lower overall crash total. The proportion of crashes resulting in minor injuries decreased significantly, falling from 14.3% (8 crashes) in 2024 to 6.7% (3 crashes) in 2025. Crashes involving possible injuries rose from 4 to 5, increasing their share of total crashes from 7.1% to 11.1%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.2%
→0.0%prior 1
Serious Injury3serious injury crashes6.7%
↓-25.0%prior 4
Minor Injury3minor injury crashes6.7%
↓-62.5%prior 8
Possible Injury5possible injury crashes11.1%
↑25.0%prior 4
No Injury33no injury crashes73.3%
↓-15.4%prior 39

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 a leading contributing factor but saw a significant count-based decrease, dropping from 13 incidents in 2024 to 6 in 2025. 'Driver Distraction: Other interior distraction' became more prominent, with the crash count increasing from 3 to 5. Incidents of 'Ran off road - straight' were halved, decreasing from 6 crashes in the prior period to 3 in the current period.

Officer-Reported Primary Contributing Cause

Animal6 (13.3%)↓-53.8%prior 13
Driver Distraction: Other interior distraction5 (11.1%)
Ran off road - left4 (8.9%)
Ran off road - straight3 (6.7%)↓-50.0%prior 6
Followed too close3 (6.7%)
Other (explain in narrative): Other3 (6.7%)↓-62.5%prior 8
Lost Control2 (4.4%)
FTYROW: Making left turn2 (4.4%)
FTYROW: Other (explain in narrative)2 (4.4%)
Improper or erratic lane changing1 (2.2%)

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 number of crashes occurring on dry roads decreased from 37 to 30, while crashes on gravel roads quadrupled from 2 to 8 incidents year-over-year. Crashes in clear weather fell from 39 to 35, and incidents during snowy conditions dropped from 4 to 1. The number of crashes in daylight (30) and on unlighted dark roadways (10) remained identical to the prior year.

Weather

Clear35 (83.3%)
↓-10.3%prior 39
Cloudy5 (11.9%)
Rain1 (2.4%)
Snow1 (2.4%)

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

Lighting

Daylight30 (69.8%)
→0.0%prior 30
Dark - roadway not lighted10 (23.3%)
→0.0%prior 10
Dark - roadway lighted1 (2.3%)
Dawn1 (2.3%)
Dusk1 (2.3%)

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

Road Surface

Dry30 (71.4%)
↓-18.9%prior 37
Gravel8 (19.0%)
Wet3 (7.1%)
Ice/frost1 (2.4%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes saw a notable shift; the count for Ford vehicles decreased from 21 in 2024 to 7 in 2025. Chevrolet-branded vehicles (CHEV and CHEVROLET combined) were involved in 14 crashes, down from 18 in the prior year. The age distribution of persons involved remained relatively consistent, with the 16-20 and 26-34 age groups representing the largest cohorts in both periods.

Top Vehicle Makes (69 vehicles)

1
CHEV10 (14.5%)
↓-9.1%prior 11
2
GMC7 (10.1%)
↑16.7%prior 6
3
FORD7 (10.1%)
↓-66.7%prior 21
4
JEEP6 (8.7%)
↑20.0%prior 5
5
CHEVROLET4 (5.8%)
↓-42.9%prior 7
6
RAM4 (5.8%)
7
BUIC4 (5.8%)
8
DODG3 (4.3%)
9
TOYO3 (4.3%)
10
INTERNATIONA2 (2.9%)

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

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

Sex Distribution (47 persons with recorded sex)

Male30 (63.8%)
↑11.1%prior 27
Female17 (36.2%)
↓-22.7%prior 22

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: 45
  • Total persons involved: 71
  • Total vehicles involved: 69

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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