Monthly Traffic Safety Analysis

3,657 CRASHES IN
IOWA, IA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, there were 3,657 crashes statewide, a 9.5% decrease from the 4,043 crashes recorded in February 2025. This overall downturn included a 41.2% reduction in fatalities, which fell from 17 to 10 year-over-year. The most notable shift in crash circumstances was a sharp decline in incidents occurring on snowy or icy roads and those attributed to driving too fast for conditions.

3,657

▼ -9.5%was 4,043

Total Crash Events

10

▼ -41.2%was 17

Persons Killed

1,082

▲ 3.4%was 1,046

Persons Injured

10

▼ -37.5%was 16

Fatal Crash Events

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash volume in Iowa showed a downward trend in February 2026 compared to the same month in the prior year, decreasing by 9.5% from 4,043 to 3,657 incidents. While total crashes and fatalities (down from 17 to 10) declined, the number of people injured saw a slight increase from 1,046 to 1,082.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 2↑100.0%

0

Cyclists Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 15↓-60.0%

0

Other Killed

Prior: 0→0.0%

24

Pedestrians Injured

Prior: 16↑50.0%

8

Cyclists Injured

Prior: 7↑14.3%

1,043

Motorists Injured

Prior: 1,022↑2.1%

7

Other Injured

Prior: 1↑600.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The daily crash pattern shifted year-over-year. While the peak hour for crashes remained the 3 p.m. hour in both periods, the peak day for crashes moved from Wednesday (931 crashes) in February 2025 to Friday (759 crashes) in February 2026. The significant single-day spike in crashes on a Wednesday in the prior period was not repeated, leading to a different distribution across the weekdays in the current period.

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 16 in the prior period to 10 in the current period, with the fatal crash rate falling from 0.4% to 0.3% of all crashes. However, the proportion of crashes involving non-fatal injuries increased across the board. Crashes resulting in serious injuries rose from a 1.2% share to a 1.9% share of all incidents, and minor injury crashes increased their share from 7.5% to 8.1%.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.3%
↓-37.5%prior 16
Serious Injury70serious injury crashes1.9%
↑45.8%prior 48
Minor Injury298minor injury crashes8.1%
↓-2.3%prior 305
Possible Injury551possible injury crashes15.1%
↓-8.2%prior 600
No Injury2,728no injury crashes74.6%
↓-11.3%prior 3,074

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors changed between the two periods. Collisions involving an animal became the leading factor in February 2026 with 442 incidents, a 14.5% increase in count from 386 the previous year when it ranked third. Conversely, crashes attributed to 'Driving too fast for conditions' saw a 40.7% decrease in count, falling from 459 to 272 and dropping from first to third in rank. 'Ran off road - left' incidents also dropped by 43.4% from 458 to 259.

Officer-Reported Primary Contributing Cause

Animal442 (12.1%)↑14.5%prior 386
Followed too close321 (8.8%)↑1.9%prior 315
Driving too fast for conditions272 (7.4%)↓-40.7%prior 459
Ran off road - left259 (7.1%)↓-43.4%prior 458
FTYROW: From stop sign202 (5.5%)↑11.6%prior 181
Lost Control172 (4.7%)↓-22.5%prior 222
Other (explain in narrative): Other170 (4.6%)↓-23.4%prior 222
FTYROW: Making left turn150 (4.1%)↑17.2%prior 128
Ran Traffic Signal138 (3.8%)↑17.9%prior 117
Ran off road - straight128 (3.5%)↓-14.7%prior 150

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred year-over-year. In February 2026, a smaller proportion of crashes happened in adverse weather, with snow-related incidents making up 6.4% of crashes compared to 12.0% in the prior year. This trend is mirrored in road surface data, where crashes on snowy or icy roads accounted for a combined 18.2% of the total, down significantly from 33.6% in February 2025. Consequently, crashes on dry roads made up a larger share of the total, increasing from 49.4% to 64.9%.

Weather

Clear2,398 (73.7%)
↑5.2%prior 2,279
Cloudy433 (13.3%)
↓-21.3%prior 550
Snow233 (7.2%)
↓-52.2%prior 487
Blowing Snow84 (2.6%)
↓-8.7%prior 92
Freezing rain/drizzle57 (1.8%)
↓-72.6%prior 208
Rain16 (0.5%)
↑100.0%prior 8
Severe Winds15 (0.5%)
↓-31.8%prior 22
Sleet, hail9 (0.3%)
Other (explain in narrative)4 (0.1%)
↓-78.9%prior 19
Blowing sand, soil, dirt3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Lighting

Daylight2,086 (63.9%)
↓-13.0%prior 2,397
Dark - roadway lighted578 (17.7%)
↓-12.3%prior 659
Dark - roadway not lighted410 (12.5%)
↑0.2%prior 409
Dusk105 (3.2%)
↓-7.9%prior 114
Dawn78 (2.4%)
↓-17.0%prior 94
Dark - unknown roadway lighting10 (0.3%)
↓-71.4%prior 35

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Road Surface

Dry2,373 (72.7%)
↑18.9%prior 1,996
Snow368 (11.3%)
↓-52.6%prior 777
Ice/frost298 (9.1%)
↓-48.7%prior 581
Wet124 (3.8%)
↓-42.9%prior 217
Slush45 (1.4%)
↓-31.8%prior 66
Gravel44 (1.3%)
↓-6.4%prior 47
Other (explain in narrative)8 (0.2%)
↑33.3%prior 6
Mud, dirt5 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Vehicles & Demographics

The vehicle makes most frequently involved in crashes remained consistent year-over-year, with Ford and Chevrolet models continuing to be the top two. While the total number of people involved in crashes decreased, the demographic distribution by age saw minor shifts. The proportion of individuals aged 65 and older involved in crashes increased from 10.4% to 11.4% of the total, even as the raw count remained unchanged at 736 persons in both periods.

Top Vehicle Makes (6,197 vehicles)

1
FORD954 (15.4%)
↓-10.5%prior 1,066
2
CHEV880 (14.2%)
↓-10.8%prior 987
3
TOYT339 (5.5%)
↓-10.1%prior 377
4
JEEP284 (4.6%)
↓-15.5%prior 336
5
HOND259 (4.2%)
↓-8.5%prior 283
6
GMC242 (3.9%)
↑4.3%prior 232
7
CHEVROLET242 (3.9%)
↓-22.7%prior 313
8
DODG233 (3.8%)
↑1.7%prior 229
9
NISS214 (3.5%)
↓-7.0%prior 230
10
KIA213 (3.4%)
↓-6.2%prior 227

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records

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

Sex Distribution (4,149 persons with recorded sex)

Male2,418 (58.3%)
↓-13.2%prior 2,787
Female1,731 (41.7%)
↓-7.9%prior 1,880

Source: Iowa Crash Data · ArcGIS Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2026-02-01 through 2026-02-28 (28 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,657
  • Total persons involved: 6,432
  • Total vehicles involved: 6,197

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: February 2026." Published September 9, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/february-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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