Monthly Traffic Safety Analysis

4,104 CRASHES IN
IOWA, IA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, there were 4,104 traffic crashes, a 25.5% decrease from the 5,512 crashes recorded in January 2024. While overall crashes and injuries declined, the number of fatalities rose from 15 to 17. A significant year-over-year shift was observed in road conditions, with crashes on snowy or icy roads decreasing substantially, corresponding with a major drop in crashes attributed to 'driving too fast for conditions'.

4,104

▼ -25.5%was 5,512

Total Crash Events

17

▲ 13.3%was 15

Persons Killed

1,083

▼ -11.7%was 1,227

Persons Injured

17

▲ 21.4%was 14

Fatal Crash Events

Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in January 2025 showed a significant downward trend, falling by 25.5% compared to the same month in the previous year. This included an 11.7% reduction in total injuries, from 1,227 to 1,083. However, fatalities bucked this trend, increasing from 15 to 17 year-over-year.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 2→0.0%

0

Cyclists Killed

Prior: 1↓-100.0%

15

Motorists Killed

Prior: 11↑36.4%

0

Other Killed

Prior: 1↓-100.0%

35

Pedestrians Injured

Prior: 24↑45.8%

3

Cyclists Injured

Prior: 4↓-25.0%

1,042

Motorists Injured

Prior: 1,199↓-13.1%

3

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes showed some changes year-over-year, with the peak day for incidents shifting from Tuesday (995 crashes) in the prior period to Thursday (941 crashes) in the current period. The 5 p.m. hour remained the single busiest time for crashes in both January 2024 and January 2025. Weekday afternoons consistently saw the highest volume of collisions in both periods.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of crashes decreased, their severity profile shifted. The number of fatal crashes increased from 14 to 17, and the fatal crash rate rose from 0.25% to 0.41% of all incidents. The proportion of crashes involving any injury also saw an increase, climbing from 21.2% in January 2024 to 24.1% in January 2025, driven partly by a rise in the share of serious injury crashes from 1.1% to 1.5%.

Outcome by Severity (Crash Events)

Fatal17fatal crashes0.4%
↑21.4%prior 14
Serious Injury61serious injury crashes1.5%
↑5.2%prior 58
Minor Injury316minor injury crashes7.7%
↑1.9%prior 310
Possible Injury597possible injury crashes14.5%
↓-23.9%prior 784
No Injury3,113no injury crashes75.9%
↓-28.4%prior 4,346

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes changed significantly compared to the prior year. 'Driving too fast for conditions,' the top factor in January 2024 with 967 crashes, saw its count drop by 68.4% to 306 incidents. Consequently, 'Animal' became the primary factor in January 2025, with its crash count increasing by 38.7% from 401 to 556. Crashes involving 'Followed too close' also rose in count by 39.5%, from 294 to 410, making it the second-most cited factor.

Officer-Reported Primary Contributing Cause

Animal556 (13.5%)↑38.7%prior 401
Followed too close410 (10%)↑39.5%prior 294
Ran off road - left329 (8%)↓-51.4%prior 677
Driving too fast for conditions306 (7.5%)↓-68.4%prior 967
FTYROW: From stop sign192 (4.7%)↓-24.1%prior 253
Other (explain in narrative): Other188 (4.6%)↓-40.7%prior 317
Lost Control177 (4.3%)↓-40.8%prior 299
FTYROW: Making left turn172 (4.2%)↓-21.8%prior 220
Ran off road - straight140 (3.4%)↓-35.8%prior 218
Ran Stop Sign138 (3.4%)↓-16.9%prior 166

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

Road & Environmental Conditions

Environmental conditions were markedly different between the two periods, strongly influencing crash patterns. In January 2024, crashes on 'Snow' (1,713) and 'Ice/frost' (1,230) road surfaces were predominant. In contrast, January 2025 saw most crashes occur on 'Dry' roads (2,537), with incidents on snowy or icy surfaces falling to 516 and 283, respectively. This shift aligns with the significant reduction in crashes attributed to driving too fast for conditions.

Weather

Clear2,578 (71.7%)
↑5.9%prior 2,435
Cloudy514 (14.3%)
↓-54.5%prior 1,130
Snow424 (11.8%)
↓-47.6%prior 809
Blowing Snow29 (0.8%)
↓-92.0%prior 364
Rain12 (0.3%)
↓-83.1%prior 71
Other (explain in narrative)9 (0.3%)
↓-70.0%prior 30
Freezing rain/drizzle9 (0.3%)
↓-90.3%prior 93
Severe Winds8 (0.2%)
↓-68.0%prior 25
Fog, smoke, smog7 (0.2%)
↓-95.8%prior 167
Sleet, hail5 (0.1%)
↓-28.6%prior 7

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

Lighting

Daylight2,221 (61.3%)
↓-28.0%prior 3,085
Dark - roadway lighted710 (19.6%)
↓-30.0%prior 1,015
Dark - roadway not lighted417 (11.5%)
↓-41.9%prior 718
Dusk126 (3.5%)
↓-28.0%prior 175
Dawn114 (3.1%)
↓-9.5%prior 126
Dark - unknown roadway lighting38 (1.0%)
↓-5.0%prior 40

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

Road Surface

Dry2,537 (70.4%)
↑107.3%prior 1,224
Snow516 (14.3%)
↓-69.9%prior 1,713
Ice/frost283 (7.8%)
↓-77.0%prior 1,230
Wet180 (5.0%)
↓-74.9%prior 717
Gravel49 (1.4%)
↑88.5%prior 26
Slush32 (0.9%)
↓-86.0%prior 229
Other (explain in narrative)6 (0.2%)
↓-14.3%prior 7
Sand3 (0.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, Ford and Chevrolet, maintained their top rankings in both periods, though their total counts decreased with the overall trend. An analysis of person demographics shows a shift in age representation among those involved in crashes. The share of individuals aged 65 and older increased from 9.5% in January 2024 to 11.8% in January 2025, while the share for the 26-34 age group decreased from 16.4% to 15.0%.

Top Vehicle Makes (6,981 vehicles)

1
FORD1,119 (16%)
↓-27.2%prior 1,538
2
CHEV948 (13.6%)
↓-26.7%prior 1,294
3
TOYT411 (5.9%)
↓-1.7%prior 418
4
CHEVROLET346 (5%)
↓-24.3%prior 457
5
JEEP333 (4.8%)
↓-16.5%prior 399
6
HOND294 (4.2%)
↓-19.2%prior 364
7
GMC260 (3.7%)
↓-25.3%prior 348
8
NISS260 (3.7%)
↓-15.9%prior 309
9
DODG223 (3.2%)
↓-30.3%prior 320
10
KIA213 (3.1%)
↓-18.1%prior 260

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

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

Sex Distribution (4,733 persons with recorded sex)

Male2,676 (56.5%)
↓-35.9%prior 4,173
Female2,057 (43.5%)
↓-20.1%prior 2,573

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-01-31 · 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 2025-01-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,104
  • Total persons involved: 7,200
  • Total vehicles involved: 6,981

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: January 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/january-2025-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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Iowa (Statewide) Crash Report — January 2025 | ThatCarHitMe.com