Yearly Traffic Safety Analysis

103 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Kossuth County, total vehicle crashes decreased by 21.4%, from 131 incidents in 2020 to 103 in 2021. The most significant year-over-year change was the complete elimination of traffic fatalities, which dropped from four in the prior period to zero in the current period.

103

▼ -21.4%was 131

Total Crash Events

0

▼ -100.0%was 4

Persons Killed

46

▼ -8.0%was 50

Persons Injured

0

▼ -100.0%was 4

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

Overall, traffic safety trends in Kossuth County showed improvement year-over-year. The total number of crashes fell from 131 in 2020 to 103 in 2021, a 21.4% reduction. This decrease was accompanied by a drop in total injuries from 50 to 46 and a reduction in fatalities from four to zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 4↓-100.0%

46

Motorists Injured

Prior: 50↓-8.0%

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 timing of crashes shifted between the two periods. In 2021, the peak day for crashes was Thursday with 20 incidents, a change from Friday (27 incidents) in 2020. Similarly, the peak hour moved from 3 p.m. in the prior year (13 crashes) to 11 a.m. in the current year (11 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

While fatal crashes were eliminated in 2021, dropping from four in the previous year, the number of serious injury crashes more than doubled. Crashes resulting in serious injuries increased from 5 in 2020 to 11 in 2021, raising their share of total crashes from 3.8% to 10.7%. The count of minor injury crashes remained unchanged at 12, while possible injury crashes decreased from 21 to 15.

Outcome by Severity (Crash Events)

Serious Injury11serious injury crashes10.7%
↑120.0%prior 5
Minor Injury12minor injury crashes11.7%
→0.0%prior 12
Possible Injury15possible injury crashes14.6%
↓-28.6%prior 21
No Injury65no injury crashes63.1%
↓-27.0%prior 89

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 animals and drivers losing control were the top two contributing factors in both years, though their counts decreased. The number of crashes attributed to animals fell from 17 to 13, and incidents of lost control declined from 13 to 12. Conversely, crashes involving failure to yield from a stop sign increased slightly from 9 to 10 incidents, becoming the third most common factor in 2021.

Officer-Reported Primary Contributing Cause

Animal13 (12.6%)↓-23.5%prior 17
Lost Control12 (11.7%)↓-7.7%prior 13
FTYROW: From stop sign10 (9.7%)↑11.1%prior 9
Made improper turn7 (6.8%)↑40.0%prior 5
Driver Distraction: Other interior distraction6 (5.8%)↓-25.0%prior 8
Ran off road - straight6 (5.8%)
Followed too close5 (4.9%)
Other (explain in narrative): Other4 (3.9%)↓-55.6%prior 9
Improper Backing3 (2.9%)
Passing: Other passing (explain in narrative)3 (2.9%)

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

Road & Environmental Conditions

Crashes were more likely to occur in clear weather and on dry roads in 2021 compared to the prior year. The proportion of crashes in clear weather rose from 61.1% to 68.9% year-over-year. Concurrently, the number of crashes on adverse road surfaces like ice, snow, or wet pavement decreased substantially, falling from 33 incidents in 2020 to 16 in 2021. The share of crashes occurring during daylight hours remained stable at approximately 68-70% for both periods.

Weather

Clear71 (76.3%)
↓-11.3%prior 80
Cloudy15 (16.1%)
↓-28.6%prior 21
Rain3 (3.2%)
Blowing Snow1 (1.1%)
Fog, smoke, smog1 (1.1%)
Freezing rain/drizzle1 (1.1%)
Other (explain in narrative)1 (1.1%)

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

Lighting

Daylight70 (75.3%)
↓-23.9%prior 92
Dark - roadway not lighted14 (15.1%)
↑7.7%prior 13
Dark - roadway lighted4 (4.3%)
↓-55.6%prior 9
Dusk3 (3.2%)
Dawn2 (2.2%)
↓-60.0%prior 5

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

Road Surface

Dry71 (76.3%)
↓-14.5%prior 83
Wet10 (10.8%)
↓-9.1%prior 11
Gravel5 (5.4%)
Ice/frost3 (3.2%)
↓-70.0%prior 10
Snow3 (3.2%)
↓-70.0%prior 10
Mud, dirt1 (1.1%)

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

Vehicles & Demographics

The mix of vehicle makes involved in crashes changed year-over-year. Ford became the most frequently involved make with 33 vehicles in 2021, overtaking Chevrolet, which saw its involvement drop from 50 vehicles in 2020 to 27 in 2021. While the total number of persons involved in crashes decreased from 281 to 206, the proportional age distribution remained consistent, with the 35-44, 55-64, and 65+ age groups being the largest in both years.

Top Vehicle Makes (165 vehicles)

1
FORD33 (20%)
↑17.9%prior 28
2
CHEV14 (8.5%)
↓-30.0%prior 20
3
CHEVROLET13 (7.9%)
↓-56.7%prior 30
4
DODG8 (4.8%)
↓-27.3%prior 11
5
TOYT7 (4.2%)
↓-36.4%prior 11
6
GMC7 (4.2%)
↓-30.0%prior 10
7
JEEP5 (3%)
↓-16.7%prior 6
8
DODGE5 (3%)
→0.0%prior 5
9
FREIGHTLINER4 (2.4%)
10
BUIC4 (2.4%)

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

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

Sex Distribution (129 persons with recorded sex)

Male87 (67.4%)
↓-26.3%prior 118
Female42 (32.6%)
↓-40.8%prior 71

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: 103
  • Total persons involved: 206
  • Total vehicles involved: 165

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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