Yearly Traffic Safety Analysis

380 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Winneshiek County recorded 380 total vehicle crashes, a 6.1% increase from the 358 crashes reported in 2021. While total crashes and injuries rose, the number of fatalities decreased from 4 to 2. One of the most notable year-over-year shifts was a 17.4% increase in the count of crashes attributed to animals, which rose from 138 incidents in 2021 to 162 in 2022.

380

▲ 6.1%was 358

Total Crash Events

2

▼ -50.0%was 4

Persons Killed

120

▲ 15.4%was 104

Persons Injured

2

▼ -33.3%was 3

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Winneshiek County showed an increase from 2021 to 2022. Total crashes rose by 6.1%, from 358 to 380 incidents. Similarly, the number of people injured in these crashes increased by 15.4%, from 104 to 120. In contrast, the number of fatalities was halved, decreasing from 4 in 2021 to 2 in 2022.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 4↓-50.0%

120

Motorists Injured

Prior: 104↑15.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between 2021 and 2022. The peak day for crashes moved from Saturday (72 crashes) in 2021 to Tuesday (63 crashes) in 2022. The peak hour also shifted later into the evening, from 6 p.m. in the prior year (28 crashes) to 9 p.m. in the current year (30 crashes). The month with the highest crash volume changed from October (52 crashes) in 2021 to November (56 crashes) in 2022.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

In 2022, the severity of crashes showed a mixed trend compared to the previous year. The fatal crash rate decreased from 0.84 per 100 crashes in 2021 to 0.53 in 2022, with the count of fatal crashes dropping from 3 to 2. However, the number of serious injury crashes increased from 12 in 2021 to 16 in 2022, and their share of all crashes rose from 3.4% to 4.2%. Minor injury crashes also saw an increase in count from 40 to 49.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
↓-33.3%prior 3
Serious Injury16serious injury crashes4.2%
↑33.3%prior 12
Minor Injury49minor injury crashes12.9%
↑22.5%prior 40
Possible Injury30possible injury crashes7.9%
↓-11.8%prior 34
No Injury283no injury crashes74.5%
↑5.2%prior 269

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, with the count of such crashes increasing by 17.4% from 138 in 2021 to 162 in 2022. The second-most cited factor, 'Lost Control,' saw its count decrease from 33 to 30 incidents. Notably, crashes attributed to 'Driving too fast for conditions' experienced a 53.3% increase in count, rising from 15 incidents in 2021 to 23 in 2022.

Officer-Reported Primary Contributing Cause

Animal162 (42.6%)↑17.4%prior 138
Lost Control30 (7.9%)↓-9.1%prior 33
Driving too fast for conditions23 (6.1%)↑53.3%prior 15
Ran off road - straight19 (5%)→0.0%prior 19
Other (explain in narrative): Other18 (4.7%)↑28.6%prior 14
Followed too close13 (3.4%)↑62.5%prior 8
Operating vehicle in an reckless, erratic, careless, negligent manner11 (2.9%)↑83.3%prior 6
FTYROW: From stop sign11 (2.9%)↓-21.4%prior 14
FTYROW: Making left turn10 (2.6%)↑66.7%prior 6
Ran off road - left10 (2.6%)↓-41.2%prior 17

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Comparing crash conditions year-over-year reveals a notable increase in incidents occurring during adverse winter weather. Crashes on roads with snow on the surface nearly doubled from 17 in 2021 to 33 in 2022. Correspondingly, crashes reported during blowing snow conditions rose from 1 to 9. In contrast, crashes on dry road surfaces decreased from 170 to 148, and those in dark, unlighted conditions fell from 65 to 50.

Weather

Clear147 (63.4%)
↓-11.4%prior 166
Cloudy46 (19.8%)
↑4.5%prior 44
Snow12 (5.2%)
↑71.4%prior 7
Blowing Snow9 (3.9%)
Rain8 (3.4%)
↓-11.1%prior 9
Freezing rain/drizzle6 (2.6%)
↑20.0%prior 5
Other (explain in narrative)3 (1.3%)
Severe Winds1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight149 (63.4%)
↑5.7%prior 141
Dark - roadway not lighted50 (21.3%)
↓-23.1%prior 65
Dark - roadway lighted16 (6.8%)
↓-20.0%prior 20
Dusk11 (4.7%)
↑22.2%prior 9
Dawn8 (3.4%)
Dark - unknown roadway lighting1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry148 (63.0%)
↓-12.9%prior 170
Snow33 (14.0%)
↑94.1%prior 17
Wet17 (7.2%)
↓-19.0%prior 21
Gravel17 (7.2%)
↑6.3%prior 16
Ice/frost14 (6.0%)
↓-6.7%prior 15
Other (explain in narrative)4 (1.7%)
Slush2 (0.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models being the most frequent in both years. Ford vehicles were involved in 95 crashes in 2022, down from 100 in 2021. An analysis of persons involved in crashes reveals a significant demographic shift, with the number of individuals in the 26-34 age group nearly doubling from 68 in 2021 to 133 in 2022. The representation of other age groups, such as 16-20 and 65+, remained relatively stable.

Top Vehicle Makes (499 vehicles)

1
FORD95 (19%)
↓-5.0%prior 100
2
CHEV70 (14%)
↑9.4%prior 64
3
GMC38 (7.6%)
↑35.7%prior 28
4
CHEVROLET29 (5.8%)
↓-29.3%prior 41
5
DODG19 (3.8%)
↑35.7%prior 14
6
BUIC18 (3.6%)
↑28.6%prior 14
7
SUBA16 (3.2%)
↑128.6%prior 7
8
CHRY12 (2.4%)
↑71.4%prior 7
9
JEEP12 (2.4%)
↓-40.0%prior 20
10
DODGE11 (2.2%)
↑10.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (469 persons with recorded sex)

Male267 (56.9%)
↑21.4%prior 220
Female202 (43.1%)
↑33.8%prior 151

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 380
  • Total persons involved: 793
  • Total vehicles involved: 499

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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