Yearly Traffic Safety Analysis

186 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Franklin County, total traffic crashes decreased by 7.5% from 201 in the prior year to 186 in the current year. Despite the overall reduction in crashes, the number of fatalities doubled from one to two. The most significant change was a 100% increase in the count of crashes attributed to vehicles running off the road to the left, which rose from 9 to 18 incidents.

186

▼ -7.5%was 201

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

52

Persons Injured

2

▲ 100.0%was 1

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

Overall traffic crashes in Franklin County showed a downward trend, decreasing from 201 to 186 year-over-year. However, the severity of outcomes worsened, with total fatalities increasing from one to two. The total number of injuries remained unchanged at 52 for both periods.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

1

Cyclists Injured

Prior: 1→0.0%

51

Motorists Injured

Prior: 49↑4.1%

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 shifted year-over-year. The peak day for crashes moved from Monday and Friday (33 crashes each) in the prior period to Thursday (31 crashes) in the current period. Similarly, the peak hour for collisions changed from 6 a.m. in the previous year (16 crashes) to 12 p.m. in the current year (16 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 trends varied between the two periods. The number of fatal crashes increased from one to two, raising the fatal crash share from 0.5% to 1.1% of all incidents. Conversely, the count of serious injury crashes decreased from five to two. While the total number of injuries was stable at 52, there was a shift in their distribution, with minor injury crashes increasing from 11 to 16.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
↑100.0%prior 1
Serious Injury2serious injury crashes1.1%
↓-60.0%prior 5
Minor Injury16minor injury crashes8.6%
↑45.5%prior 11
Possible Injury20possible injury crashes10.8%
↓-13.0%prior 23
No Injury146no injury crashes78.5%
↓-9.3%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 with animals remained the leading contributing factor in both periods, though the count of such incidents decreased by 27% from 62 to 45. The most notable year-over-year change was a 100% increase in the count of crashes where the driver 'Ran off road - left,' which grew from 9 to 18 incidents. 'Followed too close' also saw an increase in count from 6 to 9 crashes.

Officer-Reported Primary Contributing Cause

Animal45 (24.2%)↓-27.4%prior 62
Other (explain in narrative): Other20 (10.8%)↓-9.1%prior 22
Ran off road - left18 (9.7%)↑100.0%prior 9
Driving too fast for conditions10 (5.4%)↑25.0%prior 8
Followed too close9 (4.8%)↑50.0%prior 6
Ran off road - straight9 (4.8%)→0.0%prior 9
Lost Control7 (3.8%)↓-22.2%prior 9
Driver Distraction: Other interior distraction7 (3.8%)↓-12.5%prior 8
Improper Backing6 (3.2%)
FTYROW: From stop sign6 (3.2%)↓-14.3%prior 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

Crash conditions remained broadly similar year-over-year, with 'Clear' weather and 'Dry' road surfaces being the most common circumstances in both periods. The proportion of crashes occurring in daylight increased, accounting for 55.4% of incidents in the current year compared to 47.3% in the prior year. Crashes on roads with 'Ice/frost' increased in count from 8 to 12, and collisions during 'Snow' or 'Blowing Snow' conditions rose from 8 to 13.

Weather

Clear102 (68.0%)
↓-4.7%prior 107
Cloudy22 (14.7%)
↑4.8%prior 21
Snow7 (4.7%)
↑16.7%prior 6
Blowing Snow6 (4.0%)
Rain5 (3.3%)
Fog, smoke, smog2 (1.3%)
Freezing rain/drizzle2 (1.3%)
Severe Winds2 (1.3%)
Sleet, hail1 (0.7%)
Other (explain in narrative)1 (0.7%)

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

Lighting

Daylight103 (66.9%)
↑8.4%prior 95
Dark - roadway not lighted20 (13.0%)
↓-20.0%prior 25
Dark - roadway lighted19 (12.3%)
→0.0%prior 19
Dawn5 (3.2%)
↓-37.5%prior 8
Dusk4 (2.6%)
Dark - unknown roadway lighting3 (1.9%)
↓-40.0%prior 5

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

Road Surface

Dry105 (70.0%)
↓-2.8%prior 108
Wet15 (10.0%)
↑36.4%prior 11
Ice/frost12 (8.0%)
↑50.0%prior 8
Snow11 (7.3%)
↑10.0%prior 10
Slush3 (2.0%)
Gravel3 (2.0%)
↓-66.7%prior 9
Other (explain in narrative)1 (0.7%)

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 makes in both years, though both saw a decrease in total crash involvement. The number of persons aged 21-25 involved in crashes more than doubled from 17 to 38. The number of males involved in crashes increased from 97 to 118, while female involvement decreased from 67 to 47.

Top Vehicle Makes (282 vehicles)

1
CHEV41 (14.5%)
↓-19.6%prior 51
2
FORD35 (12.4%)
↓-16.7%prior 42
3
CHEVROLET20 (7.1%)
↓-13.0%prior 23
4
FREIGHTLINER14 (5%)
5
TOYT12 (4.3%)
→0.0%prior 12
6
GMC11 (3.9%)
↓-15.4%prior 13
7
JEEP11 (3.9%)
↓-35.3%prior 17
8
DODGE10 (3.5%)
↑42.9%prior 7
9
DODG9 (3.2%)
↓-50.0%prior 18
10
BUIC8 (2.8%)
→0.0%prior 8

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

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

Sex Distribution (165 persons with recorded sex)

Male118 (71.5%)
↑21.6%prior 97
Female47 (28.5%)
↓-29.9%prior 67

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: 186
  • Total persons involved: 292
  • Total vehicles involved: 282

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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Franklin County, IA Crash Report — 2025 | ThatCarHitMe.com