Yearly Traffic Safety Analysis

132 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Guthrie County, total crashes decreased from 135 in 2020 to 132 in 2021, a 2.2% reduction. While overall crash volume remained relatively stable, the most notable year-over-year shift was the elimination of traffic fatalities, which dropped from 3 in 2020 to zero in 2021. DUI-related crashes also saw a significant decrease, falling from 5 incidents to 1.

132

▼ -2.2%was 135

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

41

▲ 2.5%was 40

Persons Injured

0

▼ -100.0%was 3

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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Guthrie County remained relatively stable year-over-year, with total collisions decreasing slightly from 135 in 2020 to 132 in 2021. Despite this small drop in total incidents, the number of injuries remained nearly the same, rising from 40 to 41. Notably, there were no fatal crashes recorded in 2021, a significant improvement from the 3 fatal crashes that resulted in 3 deaths in the prior year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 3↓-100.0%

41

Motorists Injured

Prior: 39↑5.1%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Guthrie County showed a notable shift between the two periods. While Wednesday remained the peak day for crashes in both 2020 (29 crashes) and 2021 (24 crashes), the peak hour for incidents moved from the evening to the morning. In 2021, the highest volume of crashes occurred at 7 a.m. with 11 incidents, a clear shift from the prior year's peak at 5 p.m., which saw 14 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased in 2021 compared to the previous year. Fatal crashes were eliminated entirely, dropping from 3 incidents (2.2% of total) in 2020 to zero in 2021. The count of serious injury crashes also fell from 6 to 2. Conversely, the number of crashes resulting in minor injuries increased from 10 to 13, and possible injury crashes rose slightly from 18 to 19.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.5%
↓-66.7%prior 6
Minor Injury13minor injury crashes9.8%
↑30.0%prior 10
Possible Injury19possible injury crashes14.4%
↑5.6%prior 18
No Injury98no injury crashes74.2%
→0.0%prior 98

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, though the count of these incidents decreased from 51 in 2020 to 40 in 2021. 'Lost Control' was the second-most common factor in both years, holding steady with 14 incidents. Notably, crashes attributed to 'Driving too fast for conditions' increased from 2 incidents in 2020 to 9 in 2021. In contrast, crashes where a driver 'Ran off road - straight' decreased from 9 to 5.

Officer-Reported Primary Contributing Cause

Animal40 (30.3%)↓-21.6%prior 51
Lost Control14 (10.6%)→0.0%prior 14
Other (explain in narrative): Other10 (7.6%)↑42.9%prior 7
Driving too fast for conditions9 (6.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner7 (5.3%)↑40.0%prior 5
FTYROW: From stop sign6 (4.5%)
Ran off road - straight5 (3.8%)↓-44.4%prior 9
Exceeded authorized speed4 (3%)
Ran off road - left4 (3%)↓-50.0%prior 8
Driver Distraction: Exterior distraction4 (3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A higher proportion of crashes occurred in clear and dry conditions in 2021 compared to 2020. Crashes on dry roads rose from 75 to 81, and those in daylight increased from 58 to 65 incidents. Conversely, crashes on snowy roads decreased from 11 to 5, and incidents in dark, unlit conditions fell from 38 to 32.

Weather

Clear82 (78.1%)
↑3.8%prior 79
Cloudy14 (13.3%)
↑7.7%prior 13
Rain3 (2.9%)
Snow3 (2.9%)
↓-57.1%prior 7
Freezing rain/drizzle1 (1.0%)
Other (explain in narrative)1 (1.0%)
Blowing sand, soil, dirt1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight65 (61.3%)
↑12.1%prior 58
Dark - roadway not lighted32 (30.2%)
↓-15.8%prior 38
Dark - roadway lighted4 (3.8%)
Dusk4 (3.8%)
Dawn1 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry81 (77.1%)
↑8.0%prior 75
Gravel10 (9.5%)
→0.0%prior 10
Wet8 (7.6%)
↑33.3%prior 6
Snow5 (4.8%)
↓-54.5%prior 11
Ice/frost1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford being the most common in both years; the count of Chevrolet vehicles increased from 39 to 51, and Fords increased from 30 to 39. A notable shift occurred in the age distribution of persons involved in crashes, with the 26-34 age group seeing a significant decrease from 59 individuals in 2020 to 27 in 2021. Conversely, the involvement of the 0-15 age group increased from 4 persons to 16.

Top Vehicle Makes (183 vehicles)

1
FORD39 (21.3%)
↑30.0%prior 30
2
CHEV36 (19.7%)
↑100.0%prior 18
3
CHEVROLET15 (8.2%)
↓-28.6%prior 21
4
DODGE10 (5.5%)
↑66.7%prior 6
5
TOYOTA10 (5.5%)
6
GMC8 (4.4%)
→0.0%prior 8
7
BUIC6 (3.3%)
8
JEEP5 (2.7%)
↓-50.0%prior 10
9
DODG5 (2.7%)
10
NR3 (1.6%)
↓-40.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (147 persons with recorded sex)

Male93 (63.3%)
↓-7.0%prior 100
Female54 (36.7%)
↓-10.0%prior 60

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 132
  • Total persons involved: 241
  • Total vehicles involved: 183

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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