Yearly Traffic Safety Analysis

160 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Chickasaw County recorded 160 total crashes, an 8% decrease from the 174 crashes recorded in 2024. The most significant year-over-year change was the reduction in crash severity. Total fatalities dropped from one in the prior period to zero in the current period, and the total number of injuries decreased by 38.8% from 49 to 30.

160

▼ -8.0%was 174

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

30

▼ -38.8%was 49

Persons Injured

0

▼ -100.0%was 1

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 crashes in Chickasaw County decreased by 8% from 2024 to 2025, falling from 174 to 160 incidents. This downward trend was also reflected in crash outcomes, with total injuries declining from 49 to 30 and fatalities dropping from one to zero.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

1

Cyclists Injured

Prior: 1→0.0%

28

Motorists Injured

Prior: 47↓-40.4%

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 some shifts between the two periods. While Monday remained the peak day for crashes in both 2025 (29 crashes) and 2024 (31 crashes), the peak hour for collisions moved from 5 p.m. in the prior year (14 crashes) to 9 p.m. in the current year (12 crashes). The month with the highest crash volume also changed, shifting from December (25 crashes) in 2024 to October (20 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 decreased notably from 2024 to 2025. The county recorded zero fatal crashes in the current period, down from one fatal crash in the prior year. The proportion of crashes resulting in any type of injury also fell, with serious injury crashes decreasing from 5 to 4, minor injury crashes from 16 to 13, and possible injury crashes dropping from 18 to 7. Consequently, the share of crashes with no injuries increased from 77% of all incidents in 2024 to 85% in 2025.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes2.5%
↓-20.0%prior 5
Minor Injury13minor injury crashes8.1%
↓-18.8%prior 16
Possible Injury7possible injury crashes4.4%
↓-61.1%prior 18
No Injury136no injury crashes85%
↑1.5%prior 134

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 periods, though the count decreased slightly from 66 crashes in 2024 to 63 in 2025. The second most common factor in 2025 was 'Lost Control,' which increased by 33% from 6 to 8 crashes year-over-year. In contrast, crashes attributed to 'Improper Backing' saw a substantial reduction, falling from 6 incidents in the prior period to just 1 in the current year. 'Failure to yield from a stop sign' also saw a minor decrease from 8 to 7 crashes.

Officer-Reported Primary Contributing Cause

Animal63 (39.4%)↓-4.5%prior 66
Lost Control8 (5%)↑33.3%prior 6
FTYROW: From stop sign7 (4.4%)↓-12.5%prior 8
Driver Distraction: Other interior distraction7 (4.4%)→0.0%prior 7
Other (explain in narrative): Other7 (4.4%)↑40.0%prior 5
Made improper turn6 (3.8%)↑20.0%prior 5
Driving too fast for conditions5 (3.1%)→0.0%prior 5
Ran off road - left5 (3.1%)
Ran off road - straight5 (3.1%)
Ran Stop Sign4 (2.5%)

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 distribution of crashes across environmental conditions remained largely stable year-over-year. In both periods, approximately half of all crashes occurred on dry roads under clear weather conditions. The proportion of crashes in daylight decreased from 52.9% in 2024 to 47.5% in 2025, while crashes on dark, unlighted roadways saw a corresponding proportional increase from 9.2% to 12.5% of total incidents.

Weather

Clear80 (76.2%)
↓-7.0%prior 86
Cloudy13 (12.4%)
↑44.4%prior 9
Sleet, hail3 (2.9%)
Rain3 (2.9%)
Blowing Snow2 (1.9%)
Freezing rain/drizzle1 (1.0%)
Severe Winds1 (1.0%)
Fog, smoke, smog1 (1.0%)
Snow1 (1.0%)
↓-80.0%prior 5

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

Lighting

Daylight76 (71.0%)
↓-17.4%prior 92
Dark - roadway not lighted20 (18.7%)
↑25.0%prior 16
Dark - roadway lighted6 (5.6%)
↓-25.0%prior 8
Dawn2 (1.9%)
Dark - unknown roadway lighting2 (1.9%)
Dusk1 (0.9%)

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

Road Surface

Dry79 (75.2%)
↓-9.2%prior 87
Wet8 (7.6%)
↓-11.1%prior 9
Snow6 (5.7%)
↑20.0%prior 5
Gravel5 (4.8%)
↓-50.0%prior 10
Ice/frost4 (3.8%)
Slush3 (2.9%)
↓-50.0%prior 6

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet and Ford leading in both years, though both saw a reduction in total vehicle involvement from 2024 to 2025. An analysis of persons involved in crashes shows a shift in age demographics. The 26-34 age group became the most frequently involved group in 2025 with 40 individuals, up from 35 in the prior year. Conversely, involvement for the 35-44 age group decreased from 43 to 34 persons, and the 16-20 age group saw its count fall from 31 to 22.

Top Vehicle Makes (222 vehicles)

1
CHEV38 (17.1%)
↓-22.4%prior 49
2
FORD29 (13.1%)
↓-32.6%prior 43
3
CHEVROLET14 (6.3%)
↑7.7%prior 13
4
JEEP11 (5%)
↓-8.3%prior 12
5
RAM11 (5%)
6
DODG9 (4.1%)
↓-18.2%prior 11
7
BUIC8 (3.6%)
→0.0%prior 8
8
GMC8 (3.6%)
↓-52.9%prior 17
9
TOYT6 (2.7%)
10
TOYO6 (2.7%)

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

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

Sex Distribution (128 persons with recorded sex)

Male87 (68.0%)
↑7.4%prior 81
Female41 (32.0%)
↓-10.9%prior 46

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: 160
  • Total persons involved: 226
  • Total vehicles involved: 222

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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