Monthly Traffic Safety Analysis

4,024 CRASHES IN
IOWA, IA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, Iowa recorded 4,024 motor vehicle crashes, a 2.0% decrease from the 4,104 crashes in January 2025. Despite the overall reduction in collisions, the number of fatalities increased by 35.3%, rising from 17 to 23 year-over-year. This increase in fatalities during a period of fewer total crashes represents the most significant shift in the data.

4,024

▼ -1.9%was 4,104

Total Crash Events

23

▲ 35.3%was 17

Persons Killed

1,071

▼ -1.1%was 1,083

Persons Injured

21

▲ 23.5%was 17

Fatal Crash Events

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic collisions shows a slight decrease year-over-year. Total crashes fell by 2.0% from 4,104 in January 2025 to 4,024 in January 2026. The number of people injured in these crashes also saw a minor decline of 1.1%, from 1,083 to 1,071.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 2→0.0%

0

Cyclists Killed

Prior: 0→0.0%

21

Motorists Killed

Prior: 15↑40.0%

0

Other Killed

Prior: 0→0.0%

23

Pedestrians Injured

Prior: 35↓-34.3%

5

Cyclists Injured

Prior: 3↑66.7%

1,039

Motorists Injured

Prior: 1,042↓-0.3%

4

Other Injured

Prior: 3↑33.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. The peak day for crashes moved from Thursday (941 crashes) in the prior year to Friday (694 crashes) in the current period. Similarly, the peak hour for collisions shifted earlier, from the 5 p.m. hour in the prior period (362 crashes) to the 3 p.m. hour in the current period (356 crashes). The weekly pattern also changed from a mid-week peak in the prior year to a peak at the end of the week in the current year.

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of crashes decreased, the severity of outcomes worsened. The number of fatal crashes rose from 17 to 21, and the fatal crash rate per 100 crashes increased from 0.41 to 0.52. In contrast, the proportions of injury-related crashes remained stable. Serious injury crashes accounted for 1.5% of all crashes in both periods, while minor injury crashes made up 7.5% of the total in the current period compared to 7.7% in the prior year.

Severity is per crash event (most severe injury). 21 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal21fatal crashes0.5%
↑23.5%prior 17
Serious Injury59serious injury crashes1.5%
↓-3.3%prior 61
Minor Injury301minor injury crashes7.5%
↓-4.7%prior 316
Possible Injury579possible injury crashes14.4%
↓-3.0%prior 597
No Injury3,064no injury crashes76.1%
↓-1.6%prior 3,113

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

While collisions involving an 'Animal' remained the top contributing factor in both periods, their count decreased by 17.8% from 556 to 457. Conversely, crashes attributed to 'Lost Control' increased by 26.6% in count, rising from 177 to 224 and moving from the 7th to the 5th most common factor. 'Driving too fast for conditions' also saw an increase in count of 7.8% (from 306 to 330), and 'Ran Traffic Signal' incidents rose by 19.2% (from 130 to 155).

Officer-Reported Primary Contributing Cause

Animal457 (11.4%)↓-17.8%prior 556
Followed too close352 (8.7%)↓-14.1%prior 410
Driving too fast for conditions330 (8.2%)↑7.8%prior 306
Ran off road - left316 (7.9%)↓-4.0%prior 329
Lost Control224 (5.6%)↑26.6%prior 177
FTYROW: From stop sign209 (5.2%)↑8.9%prior 192
Other (explain in narrative): Other199 (4.9%)↑5.9%prior 188
FTYROW: Making left turn163 (4.1%)↓-5.2%prior 172
Ran Traffic Signal155 (3.9%)↑19.2%prior 130
Ran off road - straight147 (3.7%)↑5.0%prior 140

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The most significant year-over-year change was in road surface conditions. The share of crashes occurring on roads with ice or frost increased from 6.9% of all crashes in the prior period to 10.5% in the current period. Correspondingly, crashes on dry surfaces decreased as a proportion of the total, from 61.8% to 58.9%. Crash distributions by lighting condition and weather remained largely consistent, though the share of crashes in clear weather decreased from 62.8% to 57.5%.

Weather

Clear2,313 (64.4%)
↓-10.3%prior 2,578
Cloudy603 (16.8%)
↑17.3%prior 514
Snow344 (9.6%)
↓-18.9%prior 424
Blowing Snow135 (3.8%)
↑365.5%prior 29
Rain74 (2.1%)
↑516.7%prior 12
Fog, smoke, smog58 (1.6%)
↑728.6%prior 7
Severe Winds36 (1.0%)
↑350.0%prior 8
Freezing rain/drizzle23 (0.6%)
↑155.6%prior 9
Other (explain in narrative)6 (0.2%)
↓-33.3%prior 9
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight2,143 (59.4%)
↓-3.5%prior 2,221
Dark - roadway lighted774 (21.4%)
↑9.0%prior 710
Dark - roadway not lighted464 (12.9%)
↑11.3%prior 417
Dusk126 (3.5%)
→0.0%prior 126
Dawn76 (2.1%)
↓-33.3%prior 114
Dark - unknown roadway lighting27 (0.7%)
↓-28.9%prior 38

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry2,372 (65.8%)
↓-6.5%prior 2,537
Snow517 (14.3%)
↑0.2%prior 516
Ice/frost424 (11.8%)
↑49.8%prior 283
Wet231 (6.4%)
↑28.3%prior 180
Gravel36 (1.0%)
↓-26.5%prior 49
Slush16 (0.4%)
↓-50.0%prior 32
Other (explain in narrative)6 (0.2%)
→0.0%prior 6
Mud, dirt3 (0.1%)
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

The primary vehicle makes involved in crashes remained consistent year-over-year, with Ford and Chevrolet products leading in both periods without significant changes in their rankings. The demographic data for persons involved in crashes also showed stability. The age distribution of individuals in crashes was nearly identical between the two periods, with no specific age group showing a notable change in its share of involvement.

Top Vehicle Makes (6,832 vehicles)

1
FORD1,087 (15.9%)
↓-2.9%prior 1,119
2
CHEV967 (14.2%)
↑2.0%prior 948
3
JEEP359 (5.3%)
↑7.8%prior 333
4
TOYT359 (5.3%)
↓-12.7%prior 411
5
CHEVROLET287 (4.2%)
↓-17.1%prior 346
6
HOND285 (4.2%)
↓-3.1%prior 294
7
NISS264 (3.9%)
↑1.5%prior 260
8
DODG222 (3.2%)
↓-0.4%prior 223
9
GMC214 (3.1%)
↓-17.7%prior 260
10
KIA213 (3.1%)
→0.0%prior 213

Source: Iowa Crash Data · ArcGIS Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (4,658 persons with recorded sex)

Male2,735 (58.7%)
↑2.2%prior 2,676
Female1,923 (41.3%)
↓-6.5%prior 2,057

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

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,024
  • Total persons involved: 7,060
  • Total vehicles involved: 6,832

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 2026." Published September 9, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/january-2026-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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