Yearly Traffic Safety Analysis

42 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Winnebago County recorded 42 total crashes, the same number as in 2020. While the overall crash volume remained stable, the most significant year-over-year change was the occurrence of two fatalities in 2021 compared to zero in the prior year. Total injuries also increased from 18 to 25, a 38.9% rise.

42

Total Crash Events

2

Persons Killed

25

▲ 38.9%was 18

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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

The total number of crashes in Winnebago County was unchanged year-over-year, with 42 incidents reported in both 2021 and 2020. Despite the stable crash volume, the severity of outcomes worsened. Total injuries rose by 38.9% from 18 to 25, and the county recorded two fatalities in 2021 after having none in 2020.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 2↓-50.0%

24

Motorists Injured

Prior: 15↑60.0%

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

Crash timing patterns shifted between the two periods. In 2021, the peak day for crashes was Thursday with 12 incidents, a change from 2020 when Wednesday was the peak day with 9 crashes. Similarly, the peak hour for crashes moved from 10 a.m. (5 crashes) in 2020 to 11 a.m. (6 crashes) in 2021.

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 increased significantly in 2021, with two fatal crashes accounting for 4.8% of all incidents, compared to zero fatal crashes in 2020. The number of serious injury crashes remained stable at three in both years. Crashes resulting in minor injuries decreased from six to three, while possible injury crashes saw a slight increase from seven to eight.

Outcome by Severity (Crash Events)

Fatal2fatal crashes4.8%
Serious Injury3serious injury crashes7.1%
→0.0%prior 3
Minor Injury3minor injury crashes7.1%
↓-50.0%prior 6
Possible Injury8possible injury crashes19%
↑14.3%prior 7
No Injury26no injury crashes61.9%
→0.0%prior 26

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

The leading contributing factors for crashes changed notably between the two periods. In 2021, the top factors were 'Followed too close,' 'Animal,' and 'Lost Control,' each cited in 5 crashes. This contrasts with 2020, where the leading causes were 'Operating vehicle in an reckless, erratic, careless, negligent manner' and 'Ran off road - left,' each with 6 incidents. Crashes involving animals increased by 150% from 2 to 5, while those attributed to reckless operation decreased by 66.7%, from 6 to 2 incidents.

Officer-Reported Primary Contributing Cause

Followed too close5 (11.9%)
Animal5 (11.9%)
Lost Control5 (11.9%)
Driving too fast for conditions3 (7.1%)
Ran Stop Sign3 (7.1%)
Made improper turn3 (7.1%)
FTYROW: From yield sign2 (4.8%)
Driver Distraction: Inattentive/lost in thought2 (4.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner2 (4.8%)↓-66.7%prior 6
Ran off road - left2 (4.8%)↓-66.7%prior 6

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 in clear weather and daylight conditions were the most frequent scenarios in both years. However, the proportion of crashes on dry roads decreased from 64.3% (27 crashes) in 2020 to 52.4% (22 crashes) in 2021. A significant shift occurred in road surface conditions, with crashes on gravel roads increasing from 2 in 2020 to 9 in 2021. Crashes in dark, unlighted conditions also rose from 2 incidents to 7 year-over-year.

Weather

Clear30 (76.9%)
↑25.0%prior 24
Cloudy3 (7.7%)
↓-70.0%prior 10
Snow3 (7.7%)
Blowing Snow2 (5.1%)
Rain1 (2.6%)

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

Lighting

Daylight25 (64.1%)
↓-16.7%prior 30
Dark - roadway not lighted7 (17.9%)
Dark - roadway lighted3 (7.7%)
↓-57.1%prior 7
Dusk2 (5.1%)
Dawn1 (2.6%)
Dark - unknown roadway lighting1 (2.6%)

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

Road Surface

Dry22 (56.4%)
↓-18.5%prior 27
Gravel9 (23.1%)
Snow4 (10.3%)
Wet3 (7.7%)
Ice/frost1 (2.6%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford (11 vehicles) and Chevrolet (10 vehicles) leading in 2021, similar to 2020. An analysis of the age distribution of persons involved shows a demographic shift. The number of persons aged 65 and older involved in crashes increased from 12 to 17, and the 26-34 age group saw an increase from 6 to 13 persons. Conversely, involvement for the 16-20 age group decreased from 17 persons in 2020 to 12 in 2021.

Top Vehicle Makes (68 vehicles)

1
FORD11 (16.2%)
↓-21.4%prior 14
2
DODGE7 (10.3%)
3
CHEVROLET5 (7.4%)
↓-16.7%prior 6
4
CHEV5 (7.4%)
↓-54.5%prior 11
5
GMC4 (5.9%)
↓-20.0%prior 5
6
JEEP4 (5.9%)
7
TOYOTA3 (4.4%)
8
BUICK3 (4.4%)
9
NISSAN2 (2.9%)
10
TOYO2 (2.9%)

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

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

Sex Distribution (53 persons with recorded sex)

Female27 (50.9%)
↑8.0%prior 25
Male26 (49.1%)
↓-25.7%prior 35

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: 42
  • Total persons involved: 90
  • Total vehicles involved: 68

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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